This PDF file contains the front matter associated with SPIE Proceedings Volume 9435 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

The scope of the paper includes non–destructive assessment of the structure's material condition, for the aerospace structures during its useful lifetime. The paper presents multidisciplinary technologies devoted to development and implementation of methods and systems that realize inspection and damage detection by non–destructive methods. The paper covers several disciplines which are based on topics such as piezoelectric transducers, elastic waves propagation phenomenon, structural vibrations analysis, electro–mechanical impedance method, terahertz technique, laser induced fluorescence and 3D laser vibrometry applications. Among various techniques available the paper presents selected numerical simulations and experimental validations of considered structures. Authors address also the problem of adhesive bonding in the case of carbon fiber reinforced polymers (CFRP). Techniques for detection of weak bonds are presented together with signal processing approaches. The reported investigations concern weak adhesive bonds caused by both manufacturing (e.g. release agent, poor curing) and in–service contaminations (e.g. moisture). Also the paper provides helpful information about dispersion, mode conversion and wave scattering from stiffeners and boundaries. It addresses the problem of optimisation of excitation signal parameters and sensor placement, as well as analysis of signals reflected from damage. It also includes a variety of techniques being related to diagnostics (damage size estimation and damage type recognition) and prognostics.

Because of the relatively narrow bandwidth of the linear approaches, using nonlinear oscillators to harvest energy from ambient vibrations has been a primary trend in this field. Frequency response, used extensively in evaluating linear approaches, has been used as the primary metrics for nonlinear harvesters. Existing results have demonstrated that nonlinear devices may offer “broadband” performance. However, such “broadband” performance can only be obtained from a single-frequency excitation. It does not represent satisfactory performance of such devices under multi-frequency excitations because of the inapplicability of the principle of superposition. Conversely, existing nonlinear devices may perform worse than their linear counterparts for excitations with multiple dominant frequencies. This paper provides some new insights into the potential of using nonlinear systems to harvest energy from vibrations with multiple frequencies. A previous study has shown that a nonlinear harvester can achieve its maximum performance only at the so-called global resonance condition under which the properties of excitation matches those of the response. Through the global resonance mechanism, the energy can be dissipated and compensated in multiple frequencies with the maximum efficiency. A device design concept based on the matching between the potential well of the device and the characteristics of the excitation is proposed in this study. Numerical results are included to demonstrate the effectiveness of the proposed method. In this study, focus is placed on periodic response; chaos and response under random excitations are not considered.

Hydrocarbon extraction companies are seeking novel methods to generate and store power in down hole applications. Specifically, a robust energy harvesting system, capable of withstanding the harsh environmental and operational demands at the bottom of production wells, is desired to power commercially available well monitoring devices. The wide variety of well configurations makes this a challenging problem. Although some variables relating to the production tube are well defined by American Petroleum Institute standards, other variables may vary widely and be time dependent, such as annulus fluid properties. A first order task, then, is to characterize and understand the dynamics of a well through a study of changes in natural frequency over the broad range of inputs possessing moderate to high uncertainty.

This paper presents the results of an analytical frequency study which illustrates the effect of a select set of variables on the first natural frequency of a producing well. Specifically, axial force effects, fluid flow effects, and hydrodynamic effects, by means of a hydrodynamic function, are investigated. Due to the nature of the hydrodynamic function, the model is derived in the frequency domain and solved using the spectral element method.

Speed bumps are commonly used to control the traffic speed and to ensure the safety of pedestrians. This paper proposes a novel speed bump energy harvester (SBEH), which can generate large-scale electrical energy up to several hundred watts when the vehicle drives on it. A unique design of the motion mechanism allows the up-and-down pulse motion to drive the generator into unidirectional rotation, yielding time times more energy than the traditional design. Along with the validation of energy harvesting, this paper also addresses the advantages of this motion mechanism over the traditional design, using physical modeling and simulation. Up to 200 watts electrical peak power in one phase of three-phase generator during in-field test can be regenerated when a sedan passage car passes through the SBEH prototype at 2 km/h.

Power generation schemes that could be used downhole in an oil well to produce about 1 Watt average power with long-life (decades) are actively being developed. A variety of proposed energy harvesting schemes could be used to extract energy from this environment but each of these has their own limitations that limit their practical use. Since vibrating piezoelectric structures are solid state and can be driven below their fatigue limit, harvesters based on these structures are capable of operating for very long lifetimes (decades); thereby, possibly overcoming a principle limitation of existing technology based on rotating turbo-machinery. An initial survey [1] identified that spline nozzle configurations can be used to excite a vibrating piezoelectric structure in such a way as to convert the abundant flow energy into useful amounts of electrical power. This paper presents current flow energy harvesting designs and experimental results of specific spline nozzle/ bimorph design configurations which have generated suitable power per nozzle at or above well production analogous flow rates. Theoretical models for non-dimensional analysis and constitutive electromechanical model are also presented in this paper to optimize the flow harvesting system.

Today research on supplying of low power consumption device is highly focused on piezoelectric energy harvesting from ambient vibration. The most popular structure is a cantilever beam with piezoelectric patch to convert mechanical energy into electric energy. In the past researches, the theoretical analysis and interfacing circuit design of single cantilever beam structure is highly developed. In this study, the electrical interfacing circuit of two (or more) piezoelectric generators connected to only one load is proposed and discussed. The nonlinear synchronized switching technique SSHI (Synchronized Switching Harvesting in Inductor) is examined to increase the power efficiency effectively of each piezoelectric generator. In the multiple cantilever beam or flag structure application, the structure may be composed of many piezoelectric patches and the interfacing circuit becomes more complicated and important. From the theoretical analysis and the governing equation, the equivalent circuit of two cantilever beam will be proposed and simulated with the optimized synchronous electric charge extraction (OSECE) nonlinear technique to optimize the interfacing circuit and increase the power efficiency by using the Matlab and PSIM software. The experiments will also show the good agreement with the theoretical analysis. The interfacing circuit design concept in the two cantilever beams structure can be further used in the multi-piezoelectric patches energy harvesting system such as piezoelectric flag to optimize the circuit and increase the power efficiency.

Vehicle-based monitoring has the potential to become an accurate and cost-efficient way to monitor infrastructure assets, but a number of challenges must be addressed for such a technique to be implemented widely. The majority of vehicle-based infrastructure sensing has assumed that the vehicle’s speed profile is identical every time it passes over the asset of interest. Ultimately, however this technology will be most practical if damage detection schemes can be applied regardless of the speed of the vehicle. Thus methods must be designed to handle speed variability to make this method more practical. In this paper we investigate the effects of variable speed when monitoring infrastructure from the dynamic response of a passing vehicle, which we measure by placing accelerometers on the vehicle of interest. We have conducted a series of laboratory tests to study this phenomenon, in which a vehicle crosses over a scaled model bridge structure with a varying speed profile. We quantify the ability of several features to detect changes in the infrastructure, independent of the variable speed. We show that aligning signals to normalize for speed variability improves the classification results. This work brings us closer to the ultimate goal of using vehicle-based monitoring to ensure more efficient and more reliable infrastructure in the future.

Intelligent tires equipped with sensors as well as the monitoring of the tire/road contact conditions are in demand for improving vehicle control and safety. With the aim of identifying the coefficient of friction of tire/road contact surfaces during driving, including during cornering, we develop an identification scheme for the coefficient of friction that involves estimation of the slip angle and applied force by using a single lightweight three-axis accelerometer attached on the inner surface of the tire. To validate the developed scheme, we conduct tire-rolling tests using an accelerometer-equipped tire with various slip angles on various types of road surfaces, including dry and wet surfaces. The results of these tests confirm that the estimated slip angle and applied force are reasonable. Furthermore, the identified coefficient of friction by the developed scheme agreed with that measured by standardized tests.

In this research, an internal model based method is proposed to estimate the displacement profile of a bridge subjected to a moving traffic load using a combination of acceleration and strain measurements. The structural response is assumed to be within the linear range. The deflection profile is assumed to be dominated by the fundamental mode of the bridge, therefore only requiring knowledge of the first mode. This still holds true under a multiple vehicle loading situation as the high mode shapes don’t impact the over all response of the structure. Using the structural modal parameters and partial knowledge of the moving vehicle load, the internal models of the structure and the moving load can be respectively established, which can be used to form an autonomous state-space representation of the system. The structural displacements, velocities, and accelerations are the states of such a system, and it is fully observable when the measured output contains structural accelerations and strains. Reliable estimates of structural displacements are obtained using the standard Kalman filtering technique. The effectiveness and robustness of the proposed method has been demonstrated and evaluated via numerical simulation of a simply supported single span concrete bridge subjected to a moving traffic load.

The objective of this study is to demonstrate the application of two different system identification methods on the structural health monitoring of a bridge. The numerical simulation of bridge-vehicle interaction with road surface roughness is considered in this study for system identification. To identify the bridge dynamic characteristics Covariance-driven Stochastic Subspace Identification method (SSI-COV) in cooperated with Wavelet Packet Transform (WPT) decomposition are used to extract the natural frequencies and mode shapes of the system. For comparison, a popular blind source separation technique called Second Order Blind Identification (SOBI) is also used. Comparison between these two different identification methods is discussed. It was demonstrated that the bridge natural frequencies can be identified by the proposed two system identification techniques. Besides, the SOBI algorithm can avoid the difficulty of determining of parameters by using SSI-COV algorithm, such as system order, row of Hankel matrix, etc. Finally, a damage scenario of the bridge structure is provided and damage detection algorithms are also proposed to quantify and locate the damage.

The main goal of this study was to develop and validate the performance of a miniature and portable data acquisition (DAQ) system designed for interrogating carbon nanotube (CNT)-based thin films for real-time spatial structural sensing and damage detection. Previous research demonstrated that the electrical properties of CNT-based thin film strain sensors were linearly correlated with applied strains. When coupled with an electrical impedance tomography (EIT) algorithm, the detection and localization of damage was possible. In short, EIT required that the film or “sensing skin” be interrogated along its boundaries. Electrical current was injected across a pair of boundary electrodes, and voltage was simultaneously recorded along the remaining electrode pairs. This was performed multiple times to obtain a large dataset needed for solving the EIT spatial conductivity mapping inverse problem. However, one of the main limitations of this technique was the large amount of time required for data acquisition. In order to facilitate the adoption of this technology and for field implementation purposes, a miniature DAQ that could interrogate these CNT-based sensing skins at high sampling rates was designed and tested. The prototype DAQ featured a Howland current source that could generate stable and controlled direct current. Measurement of boundary electrode voltages and the switching of the input, output, and measurement channels were achieved using multiplexer units. The DAQ prototype was fabricated on a two-layer printed circuit board, and it was designed for integration with a prototype wireless sensing system, which is the next phase of this research.

We investigate the use of impediographic tomography to achieve high sensitivity and high resolution damage identification in plate-like structures. The impediographic approach exploits the coupled piezo-resistive and electrostatic response of the host structure to generate high sensitivity and high resolution maps of its internal electrical conductivity. Focused acoustic waves are used to generate localized electrical conductivity perturbations that allow a drastic improvement in the conditioning of the inverse problem. The localized acoustic perturbations are obtained by exploiting the concept of Frequency Selective Structures (FSS) in which intentional mistuning of periodically distributed structural features, such as thin notches, enables self-focusing and vibration localization by using a single ultrasonic transducer. The impediographic reconstruction is achieved by using two different methods: the 0-Laplacian and the Levenberg-Marquardt. Both methodologies are compared in terms of accuracy of the reconstructed electrical conductivity and of their ability to deal with important practical issues such as limited view and limited perturbation data. Numerical results show that, although both approaches perform well in terms of damage identification, localization, and sizing, the LM technique allows higher flexibility in handling imperfect data.

Reliable early-stage damage detection requires continuous structural health monitoring (SHM) over large areas of structure, and with high spatial resolution of sensors. This paper presents the development stage of prototype strain sensing sheets based on Large Area Electronics (LAE), in which thin-film strain gauges and control circuits are integrated on the flexible electronics and deposited on a polyimide sheet that can cover large areas. These sensing sheets were applied for fatigue crack detection on small-scale steel plates. Two types of sensing-sheet interconnects were designed and manufactured, and dense arrays of strain gauge sensors were assembled onto the interconnects. In total, four (two for each design type) strain sensing sheets were created and tested, which were sensitive to strain at virtually every point over the whole sensing sheet area. The sensing sheets were bonded to small-scale steel plates, which had a notch on the boundary so that fatigue cracks could be generated under cyclic loading. The fatigue tests were carried out at the Carleton Laboratory of Columbia University, and the steel plates were attached through a fixture to the loading machine that applied cyclic fatigue load. Fatigue cracks then occurred and propagated across the steel plates, leading to the failure of these test samples. The strain sensor that was close to the notch successfully detected the initialization of fatigue crack and localized the damage on the plate. The strain sensor that was away from the crack successfully detected the propagation of fatigue crack based on the time history of measured strain. Overall, the results of the fatigue tests validated general principles of the strain sensing sheets for crack detection.

The work is devoted to the study on elastic wave propagation in graphene nanoribbons, performed with peridynamics. Graphene nanoribbons have recently gained dramatic increase of interest in the fields of nanoelectronics and nanoelectromechanical systems. They can play a key role as either modern metallic or semiconductor materials, depending on the edge structure, with zigzag or armchair layout, respectively. Moreover, graphene opens new perspectives for the millimeter wave-based measurements systems. The authors present a peridynamic model used as alternative approach to analyze the dynamic behavior of a graphene nanoribbon. The model is considered as a periodic structure, i.e. an assembly of fundamental structural elements, with the first Brillouin zone under study, which undergoes propagation of elastic wave. The commonly applied auxiliary atomistic-continuum model for a C-C bond is used to set equivalent elastic properties, which are applied to find reference dispersion relation via FE model to study the behavior of the peridynamic model. The paper discusses its capability of recovering the physical nature of the reactions at the atomic scale present in a graphene applying dispersion characteristics. The peridynamic model of the graphene nanoribbon results from upscaling process carried out for a small-scale atomic model, making use of reference dispersion curve. The material properties are homogenized over studied domain indirectly by tuning the phase velocity for longitudinal in-plane elastic waves. As shown, nonlocal nature of peridynamics allows to preserve the lengthscale effect, local small-scale inhomogeneity and wave dispersion. Hence, the effect of spatial discretization at nano scale, arising from the distribution of atoms of carbon in the structure of graphene, may be represented with a nonlocal peridynamic model effectively.

A photonic crystal (PhC) is a periodic structure with periodicity comparable with the wavelength of light, having a photonic band gap in the visible range. In this contribution we discuss the possible use of PhCs as strain sensors, based on the observation that a distortion in the crystal structure produces a change in the reflected bandwidth. First, we demonstrate the feasible fabrication of a PhC having sub-micrometric polystyrene colloidal spheres in a PDMS matrix on a rubber substrate, and we demonstrate that the photonic properties change with substrate elongation according to theoretical prediction. The crystal sensitivity to strain depends directly on interplanar spacing and on Poisson’s ratio. To enhance the crystal strain resolution, we propose to fabricate inverse photonic crystals with FCC structure, which are known from the literature to exhibit a high negative Poisson's ratio. We carried out a theoretical investigation to predict the opto-mechanical response of inverse PhCs, and carried out preliminary tests to demonstrate their fabrication feasibility.

We use a recently developed class of metamaterials based on geometric inhomogeneities to design acoustic lenses embedded in thin-walled structural element. The geometric inhomogeneity is based on the concept of Acoustic Black Hole (ABH) that is an exponential taper fully integrated in the supporting structure. The ABH is an element able to bend and, eventually, trap acoustic waves by creating areas with carefully engineered phase velocity gradients. Periodic lattices of ABHs are first studied in terms of their dispersion characteristics and then embedded in thin-plate structures to create lenses for ultrasonic focusing and collimation. Numerical simulations show the ability of the ABH lens to create focusing and collimation effects in an extended operating range that goes from the metamaterial to the phononic regime.

Slender beams subjected to compressive stress are common in civil and mechanical engineering. The rapid in-situ measurement of this stress may prevent structural anomalies. In this paper, we describe the coupling mechanism between highly nonlinear solitary waves (HNSWs) propagating along an L-shaped granular system and a beam in contact with the granular medium. We evaluate the use of HNSWs as a tool to measure stress in thermally loaded structures and to estimate the neutral temperature, i.e. the temperature at which this stress is null. We investigated numerically and experimentally one and two L-shaped chains of spherical particles in contact with a prismatic beam subjected to heat. We found that certain features of the solitary waves are affected by the beam’s stress. In the future, these findings may help developing a novel sensing system for the nondestructive prediction of neutral temperature and thermal buckling.

This work is focused on design and testing of a novel class of transducers for Structural Health Monitoring (SHM), able to perform directional interrogation of plate-like structures. These transducers leverage guided waves (GWs), and in particular Lamb waves, that have emerged as a very prominent option for assessing the state of a structure during operation. GW-SHM approaches greatly benefit from the use of transducers with controllable directional characteristics, so that selective scanning of a surface can be performed to locate damage, impacts, or cracks. In the concepts that we propose, continuous beam steering and directional actuation are achieved through proper selection of the excitation frequency. The design procedure takes advantage of the wavenumber representation of the device, and formulates the problem using a Fourier-based approach. The active layer of the transducer is made of piezoelectric fibers embedded into an epoxy matrix, allowing the device to be flexible, and thus suitable for application on non{ at surfaces. Proper shaping of the electrodes pattern through a compensation function allows taking into account the anisotropy level introduced by the active layer. The resulting spiral frequency steerable acoustic actuator is a configuration that features (i) enhanced performance, (ii) reduced complexity, and (iii) reduced hardware requirements of such devices.

This study presents nonlinear ultrasonic wave modulations that can be effectively used for crack detection in thin structural components. Fatigue cracks occur when structure is exposed to repeated load although the load causes the smaller stress than the yield stress. The existence of cracks deteriorates the integrity of structures and reduces the safety. To detect these cracks, several kinds of nonlinear ultrasonic wave modulation techniques have been proposed for many years. However, the fundamental reason of the nonlinearity has not been well explained theoretically yet. Mostly, the phenomenon has been investigated experimentally. In order to find the reasons of the observed modulation, numerical studies are performed considering a variety of sizes of crack widths and depths using a commercial FEA program.

This paper presents theoretical predictive modeling and experimental evaluation of the structural health monitoring capability of piezoelectric wafer active sensors (PWAS) at elevated temperatures. Electromechanical impedance spectroscopy (EMIS) method is first qualified using circular PWAS resonators under traction-free boundary condition and in an ambience with increasing temperature. The theoretical study is conducted regarding temperature dependence of the electrical parameters, the capacitance C₀, d₃₁ and g₃₁; and the elastic parameters, the in-plane compliance s₁₁ and Young’s modulus c₁₁, of piezoelectric materials. The Curie transition temperature must be well above the operating temperature; otherwise, the piezoelectric material may depolarize under combined temperature and pressure conditions. The material degradation is investigated by introducing the temperature effects on the material parameters that are obtained from experimental observations as well as from related work in literature. The preliminary results from the analytical 2-D circular PWAS-EMIS simulations are presented and validated by the experimental PWAS-EMIS measurements at elevated temperatures. Temperature variation may produce pyro-electric charges, which may interfere with the piezoelectric effect. Therefore, analytical simulations are carried out to simulate the pyro-electric response from the temperature effects on a free circular PWAS-EMIS in in-plane mode. For the experimental validation, PWAS transducers are placed in a fixture that provides the traction-free boundary condition. The fixture is then located in an oven integrated with PID temperature controller. The EMIS measurement is conducted during the temperature increase and the first resonance frequency peak in admittance and impedance spectra was acquired.

This paper discusses a data management infrastructure framework for bridge monitoring applications. As sensor technologies mature and become economically affordable, their deployment for bridge monitoring will continue to grow. Data management becomes a critical issue not only for storing the sensor data but also for integrating with the bridge model to support other functions, such as management, maintenance and inspection. The focus of this study is on the effective data management of bridge information and sensor data, which is crucial to structural health monitoring and life cycle management of bridge structures. We review the state-of-the-art of bridge information modeling and sensor data management, and propose a data management framework for bridge monitoring based on NoSQL database technologies that have been shown useful in handling high volume, time-series data and to flexibly deal with unstructured data schema. Specifically, Apache Cassandra and Mongo DB are deployed for the prototype implementation of the framework. This paper describes the database design for an XML-based Bridge Information Modeling (BrIM) schema, and the representation of sensor data using Sensor Model Language (SensorML). The proposed prototype data management framework is validated using data collected from the Yeongjong Bridge in Incheon, Korea.

Stochastic subspace identification method (SSI) has been proven to be an efficient algorithm for the identification of liner-time-invariant system using multivariate measurements. Generally, the estimated modal parameters through SSI may be afflicted with statistical uncertainty, e.g. undefined measurement noises, non-stationary excitation, finite number of data samples etc. Therefore, the identified results are subjected to variance errors. Accordingly, the concept of the stabilization diagram can help users to identify the correct model, i.e. through removing the spurious modes. Modal parameters are estimated at successive model orders where the physical modes of the system are extracted and separated from the spurious modes. Besides, an uncertainty computation scheme was derived for the calculation of uncertainty bounds for modal parameters at some given model order. The uncertainty bounds of damping ratios are particularly interesting, as the estimation of damping ratios are difficult to obtain. In this paper, an automated stochastic subspace identification algorithm is addressed. First, the identification of modal parameters through covariance-driven stochastic subspace identification from the output-only measurements is used for discussion. A systematic way of investigation on the criteria for the stabilization diagram is presented. Secondly, an automated algorithm of post-processing on stabilization diagram is demonstrated. Finally, the computation of uncertainty bounds for each mode with all model order in the stabilization diagram is utilized to determine system natural frequencies and damping ratios. Demonstration of this study on the system identification of a three-span steel bridge under operation condition is presented. It is shown that the proposed new operation procedure for the automated covariance-driven stochastic subspace identification can enhance the robustness and reliability in structural health monitoring.

To improve the simulation accuracy of the finite-element (FE) model of an as-built structure, measurement data from the actual structure can be utilized for updating the model parameters, which is termed as FE model updating. During the past few decades, most efforts on FE model updating intend to update the entire structure model altogether, while using measurement data from sensors installed throughout the structure. When applied on large and complex structural models, the typical model updating approaches may fail due to computational challenges and convergence issues. In order to reduce the computational difficulty, this paper studies a decentralized FE model updating approach that intends to update one substructure at a time. The approach divides the entire structure into a substructure (currently being instrumented and updated) and the residual structure. The Craig-Bampton transform is adopted to condense the overall structural model. The optimization objective is formulated to minimize the modal dynamic residuals from the eigenvalue equations in structural dynamics involving natural frequencies and mode shapes. This paper investigates the effects of different substructure locations and sizes on updating performance. A space frame example, which is based on an actual pedestrian bridge on Georgia Tech campus, is used to study the substructure location and size effects. Keywords: substructure

This paper presents a sequential structural damage detection algorithm that is based on a statistical model for the wavelet transform of the structural responses. The detector uses the coefficients of the wavelet model and does not require prior knowledge of the structural properties. Principal Component Analysis is applied to select and extract the most sensitive features from the wavelet coefficients as the damage sensitive features. The damage detection algorithm is validated using the simulation data collected from a four-story steel moment frame. Various features have been explored and the detection algorithm was able to identify damage. Additionally, we show that for a desired probability of false alarm, the proposed detector is asymptotically optimal on the expected delay.

This paper describes a novel framework that combines advanced mechanics-based nonlinear (hysteretic) finite element (FE) models and stochastic filtering techniques to estimate unknown time-invariant parameters of nonlinear inelastic material models used in the FE model. Using input-output data recorded during earthquake events, the proposed framework updates the nonlinear FE model of the structure. The updated FE model can be directly used for damage identification and further used for damage prognosis. To update the unknown time-invariant parameters of the FE model, two alternative stochastic filtering methods are used: the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). A three-dimensional, 5-story, 2-by-1 bay reinforced concrete (RC) frame is used to verify the proposed framework. The RC frame is modeled using fiber-section displacement-based beam-column elements with distributed plasticity and is subjected to the ground motion recorded at the Sylmar station during the 1994 Northridge earthquake. The results indicate that the proposed framework accurately estimate the unknown material parameters of the nonlinear FE model. The UKF outperforms the EKF when the relative root-mean-square error of the recorded responses are compared. In addition, the results suggest that the convergence of the estimate of modeling parameters is smoother and faster when the UKF is utilized.

Structural health monitoring (SHM) systems are critical for monitoring aging infrastructure (such as buildings or bridges) in a cost-effective manner. Wireless sensor networks that sample vibration data over time are particularly appealing for SHM applications due to their flexibility and low cost. However, in order to extend the battery life of wireless sensor nodes, it is essential to minimize the amount of vibration data these sensors must collect and transmit. In recent work, we have studied the performance of the Singular Value Decomposition (SVD) applied to the collection of data and provided new finite sample analysis characterizing conditions under which this simple technique{also known as the Proper Orthogonal Decomposition (POD){can correctly estimate the mode shapes of the structure. Specifically, we provided theoretical guarantees on the number and duration of samples required in order to estimate a structure's mode shapes to a desired level of accuracy. In that previous work, however, we considered simplified Multiple-Degree-Of-Freedom (MDOF) systems with no damping. In this paper we consider MDOF systems with proportional damping and show that, with sufficiently light damping, the POD can continue to provide accurate estimates of a structure's mode shapes. We support our discussion with new analytical insight and experimental demonstrations. In particular, we study the tradeoffs between the level of damping, the sampling rate and duration, and the accuracy to which the structure's mode shapes can be estimated.

Nondestructive evaluation and sensing technology have been increasingly applied to characterize material properties and detect local damage in structures. More often than not, they generate images or data strings that are difficult to see any physical features without novel data extraction techniques. In the literature, popular data analysis techniques include Short-time Fourier Transform, Wavelet Transform, and Hilbert Transform for time efficiency and adaptive recognition. In this study, a new data analysis technique is proposed and developed by introducing an adaptive central frequency of the continuous Morlet wavelet transform so that both high frequency and time resolution can be maintained in a time-frequency window of interest. The new analysis technique is referred to as Adaptive Wavelet Analysis (AWA). This paper will be organized in several sections. In the first section, finite time-frequency resolution limitations in the traditional wavelet transform are introduced. Such limitations would greatly distort the transformed signals with a significant frequency variation with time. In the second section, Short Time Wavelet Transform (STWT), similar to Short Time Fourier Transform (STFT), is defined and developed to overcome such shortcoming of the traditional wavelet transform. In the third section, by utilizing the STWT and a time-variant central frequency of the Morlet wavelet, AWA can adapt the time-frequency resolution requirement to the signal variation over time. Finally, the advantage of the proposed AWA is demonstrated in Section 4 with a ground penetrating radar (GPR) image from a bridge deck, an analytical chirp signal with a large range sinusoidal frequency change over time, the train-induced acceleration responses of the Tsing-Ma Suspension Bridge in Hong Kong, China. The performance of the proposed AWA will be compared with the STFT and traditional wavelet transform.

Recently, Smart houses have been studied by many researchers to satisfy individual demands of residents. However, they are not feasible yet as they are very costly and require many sensors to be embedded into houses. Therefore, we suggest “Biofied Building”. In Biofied Building, sensor agent robots conduct sensing, actuation, and control in their house. The robots monitor many parameters of human lives such as walking postures and emotion continuously. In this paper, a prototype network system and a data model for practical application for Biofied Building is pro-posed. In the system, functions of robots and servers are divided according to service flows in Biofield Buildings. The data model is designed to accumulate both the building data and the residents’ data. Data sent from the robots and data analyzed in the servers are automatically registered into the database. Lastly, feasibility of this system is verified through lighting control simulation performed in an office space.

Artificial hair sensors (AHS) have been recently developed in Air Force Research Laboratory (AFRL) using carbon nanotube (CNT). The deformation of CNT in air flow causes voltage and current changes in the circuit, which can be used to quantify the dynamic pressure and aerodynamic load along the wing surface. AFRL has done a lot of essential work in design, manufacturing, and measurement of AHSs. The work in this paper is to bridge the current AFRL’s work on AHSs and their feasible applications in flight dynamics and control (e.g., the gust alleviation) of highly flexible aircraft. A highly flexible vehicle is modeled using a strain-based geometrically nonlinear beam formulation, coupled with finite-state inflow aerodynamics. A feedback control algorithm for the rejection of gust perturbations will be developed. A simplified Linear Quadratic Regulator (LQR) controller will be implemented based on the state-space representation of the linearized system. All AHS measurements will be used as the control input, i.e., wing sectional aerodynamic loads will be defined as the control output for designing the feedback gain. Once the controller is designed, closed-loop aeroelastic simulations will be performed to evaluate the performance of different controllers with the force feedback and be compared to traditional controller designs with the state feedback. From the study, the feasibility of AHSs in flight control will be assessed. The whole study will facilitate in building a fly-by-feel simulation environment for autonomous vehicles.

This paper describes a new mechanical application of the Watt-linkage for the development and implementation of mono-axial sensors aimed to low frequency motion measurement and control of spacecrafts and satellites. The basic component of these sensors is the one dimensional UNISA Folded Pendulum mechanical sensor, developed for ground-based applications, whose unique features are due to a very effective optimization of the effects of gravitational force on the folded pendulum mechanical components, that allowed the design and implementation of FP sensors compact (< 20 cm), light (< 300 g), scalable, tunable resonance frequency < 200mHz), with large band (10⁻⁶ Hz − 100Hz), high quality factor (Q > 15000 in vacuum at 1Hz), with good immunity to environmental noises and sensitivity, guaranteed by an integrated laser optical readout, and fully adaptable to the specific requirements of the application. In this paper we show how to extend the application of ground-based FP also to space, in absence of gravity, still keeping all the above interesting features and characteristics that make this class of sensors very effective in terms of large band, especially in the low frequency, sensitivity and long term reliability. Preliminary measurements on a prototype confirm the feasibility, showing also that very good performances can be relatively easily obtained.

Although originally popularized for structural health monitoring, wireless smart sensors are an attractive alternative to traditional tethered systems for structural control. Their onboard sensing, processing, and wireless communication offer all the components of a feedback control system. However, wireless smart sensors pose unique challenges for the application of centralized control, which is common in most modern control systems. Decentralized control offers several advantages to wireless structural control, including limiting the wireless communication required and the associated slow sampling rate and time delays in the control system. Previous decentralized structural control algorithms, both Ad-Hoc and Heuristic, enforce a spatial sparsity pattern during the design, which is assumed a priori. Therefore, the optimal feedback structure is not considered in the design. This work explores a decentralized optimal LQR design algorithm where the sparsity of the feedback gain is incorporated into the objective function. The control approach is compared to previous decentralized control techniques on the 20-Story control benchmark structure. Sparsity and control requirements are compared to centralized designs. The optimal sparse feedback design offers the best balance of performance, measurement feedback, and control effort. Additionally, the feedback structure identified is not easily identifiable a priori; thus, highlighting the significance of particular measurements in this feedback framework.

In this paper, a design method for a PD controller, which is a part of a new active mass damper system using a neural oscillator for high-rise buildings, is proposed. The new system mimicking the motion of bipedal mammals is a quite simple system, which has the neural oscillator synchronizing with the acceleration response of the structure. The travel distance and direction of the auxiliary mass of the active mass damper is decided by the output of the neural oscillator, and then, the auxiliary mass is transferred to the decided location by using the PD controller. Therefore, the performance of the PD controller must be evaluated by the vibration energy absorbing efficiency by the system. In order to bring the actual path driven by the PD controller in closer alignment with the ideal path, which is assumed to be a sinusoidal wave under resonance, firstly, the path of the auxiliary mass driven by the PD controller is analytically derived, and the inner product between the vector of ideal and analytical path is evaluated. And then, the PD gain is decided by the maximum value of the inner product. Finally, numerical simulations confirm the validity of the proposed design method of the PD controller.

Experimental validation of novel structural control algorithms is a vital step in both developing and building acceptance for this technology. Small-scale experimental test-beds fulfill an important role in the validation of multiple-degree-offreedom (MDOF) and distributed semi-active control systems, allowing researchers to test the control algorithms, communication topologies, and timing-critical aspects of structural control systems that do not require full-scale specimens. In addition, small-scale building specimens can be useful in combined structural health monitoring (SHM) and LQG control studies, diminishing safety concerns during experiments by using benchtop-scale rather than largescale specimens. Development of such small-scale test-beds is hampered by difficulties in actuator construction. In order to be a useful analog to full-scale structures, actuators for small-scale test-beds should exhibit similar features and limitations as their full-scale counterparts. In particular, semi-active devices, such as magneto-rheological (MR) fluid dampers, with limited authority (versus active mass dampers) and nonlinear behavior are difficult to mimic over small force scales due to issues related to fluid containment and friction. In this study, a novel extraction-type small-force (0- 10 N) MR-fluid damper which exhibits nonlinear hysteresis similar to a full-scale, MR-device is proposed. This actuator is a key development to enable the function of a small-scale structural control test-bed intended for wireless control validation studies. Experimental validation of this prototype is conducted using a 3-story scale structure subjected to simulated single-axis seismic excitation. The actuator affects the structural response commanded by a control computer that executes an LQG state feedback control law and a modified Bouc-Wen lookup table that was previously developed for full-scale MR-applications. In addition, damper dynamic limitations are characterized and presented including force output magnitude and frequency characteristics.

In recent years, a study of a semi-active isolation system named the Leverage-type Stiffness Controllable Isolation System (LSCIS) was proposed. The main concept of the LSCIS is to adjust the stiffness in the isolator for the fundamental period of the superstructure by a simple leverage mechanism. Although great performance has been achieved with the support of the least input energy method (LIEM) in far-field earthquakes, some results still reveal that the proposed system is not suitable for application in near-fault strong ground motion. To overcome this problem, two algorithms that consider the potential energy effect in the semi-active structural control system are proposed in this study. The optimal weightings between the potential and kinetic energy are first determined through a series of near-fault earthquake simulations. The proposed algorithms are then developed with the combination of the potential energy (Ep) and the kinetic energy (Ep) as the control objective to reduce the structural displacement responses efficiently. In order to demonstrate the performance of the proposed algorithm, a two-degree-of-freedom structure is used as a benchmark in both numerical simulation and experimental verification. Numerical results have shown that the dynamic response of the structure can be effectively alleviated by the proposed algorithm under both far-field and near-fault earthquakes, while the structural responses by the LIEM may be worse than the pure passive control. The feasibility of implementing the proposed system has also been experimentally verified.

Rotating shafts in drop lifts of manufacturing facilities are susceptible to fatigue cracks as they are under repetitive heavy loading and high speed spins. However, it is challenging to use conventional contact transducers to monitor these shafts as they are continuously spinning with a high speed. In this study, a noncontact crack detection technique for a rotating shaft is proposed using air-coupled transducers (ACTs). (1) Low frequency (LF) and high frequency (HF) sinusoidal inputs are simultaneously applied to a shaft using two ACTs, respectively. A fatigue crack can provide a mechanism for nonlinear ultrasonic modulation and create spectral sidebands at the modulation frequencies, which are the sum and difference of the two input frequencies Then LF and HF inputs are independently applied to the shaft using each ACT. These three ultrasonic responses are measured using another ACT. (2) The damage index (DI) is defined as the energy of the first sideband components, which corresponding to the frequency sum and difference between HF and LF inputs. (3) Steps 1 and 2 are repeated with various combinations of HF and LF inputs. Crack existence is detected through an outlier analysis of the DIs. The effectiveness of the proposed technique is investigated using a steel shaft with a real fatigue crack.

The pulse-echo method is widely used for plate and pipe thickness measurement. However, the pulse echo method does not work well for detecting localized volumetric loss in thick-wall tubes, as created by erosion damage, when the morphology of volumetric loss is irregular and can reflect ultrasonic pulses away from the transducer, making it difficult to detect an echo. In this paper, we propose a novel method using an inductively coupled transducer to generate longitudinal waves propagating in a thick-wall aluminum tube for the volumetric loss quantification. In the experiment, longitudinal waves exhibit diffraction effects during the propagation which can be explained by the Huygens-Fresnel principle. The diffractive waves are also shown to be significantly delayed by the machined volumetric loss on the inside surface of the thick-wall aluminum tube. It is also shown that the inductively coupled transducers can generate and receive similar ultrasonic waves to those from wired transducers, and the inductively coupled transducers perform as well as the wired transducers in the volumetric loss quantification when other conditions are the same.

With the rapid development of portable electrical devices, the demand for batteries to power these portable devices increases dramatically. However, the development of the battery technology is slow in energy storage capability and cannot meet such requirements. This paper proposed an optimal frame design for a kind of portable piezoelectric stack energy harvesters, with large force magnification ratio and high energy transmission ratio. Two kinds of design approaches have been studied and explored, i.e., flexure compliant mechanism math based and finite element analysis (FEA) based. Prototypes are fabricated and assembled. Experiments with both static test and dynamic test have been conducted to approve the effectiveness of the proposed design. The measured force magnification ratio of 6.13 times and 21.8 times for the first-stage harvester and the dual-stage harvester are close to the design objective of 7.17 times and 24.4 times. The designed single stage harvester can generate 20.7mW/g² at resonance frequency of 160Hz with optimal resistance of 393Ω under 0.8g base excitation with 100gram top mass, and the dual stage harvester has power generation of 487mW/g² at resonance frequency of 38.9Hz with optimal resistance of 818Ω under 1.94g base excitation with 100gram top mass. The proposed two-stage PZT energy harvester can be used to develop portable power regenerator to compensate the urgent battery needs in remote area for both civic and military application.

As many countries around the world face an aging infrastructure crisis, there is an increasing need to develop more accurate monitoring and assessment techniques for reinforced concrete structures. One of the challenges associated with assessing existing infrastructure is correlating externally measured parameters such as crack widths and surface strains with reinforcement stresses as this is dependent on a number of variables. The current research investigates how the use of distributed fiber optic sensors to measure reinforcement strain can be correlated with digital image correlation measurements of crack widths to relate external crack width measurements to reinforcement stresses. An initial set of experiments was undertaken involving a series of small-scale beam specimens tested in three-point bending with variable reinforcement properties. Relationships between crack widths and internal reinforcement strains were observed including that both the diameter and number of bars affected the measured maximum strain and crack width. A model that uses measured crack width to estimate reinforcement strain was presented and compared to the experimental results. The model was found to provide accurate estimates of load carrying capacity for a given crack width, however, the model was potentially less accurate when crack widths were used to estimate the experimental reinforcement strains. The need for more experimental data to validate the conclusions of this research was also highlighted.

The most common assessment technique for reinforced concrete shear walls (RCSW) is Visual Inspection (VI). The current practice suffers from subjective and labor intensive nature as it highly relies on judgment and expertise of the inspectors. In post-earthquake events where urgent and objective decisions are crucial, failure of the conventional VI could be catastrophic. Conventional VI is mainly based on width of residual cracks. Given that cracks could close partially (e.g., due to weight of the structure, behavior of adjacent elastic members, earthquake displacement spectrum, etc.), methods based on crack width may lead to underestimating the state of damage and eventually an erroneous decision. This paper proposes a novel method to circumvent the aforementioned limitations by utilizing the information hidden in crack patterns. Crack patterns from images of the surface cracks on RCSW are extracted automatically, and Multifractal Analysis (MFA) are applied on them. Images were taken from two large scale low aspect ratio RCSW under quasi-static cyclic loading, and MFA showed clear correlation with tri-linear shear controlled behavior of walls which was observed in their backbone curves.

Based on the vibration testing principle, and taking the local vibration of steel tube at the interface separation area as the study object, a real-time monitoring and the damage detection method of the interface separation of concrete-filled steel tube by accelerometer array through quantitative transient self-excitation is proposed. The accelerometers are arranged on the steel tube area with or without void respectively, and the signals of accelerometers are collected at the same time and compared under different transient excitation points. The results show that compared with the signal of compact area, the peak value of accelerometer signal at void area increases and attenuation speed slows down obviously, and the spectrum peaks of the void area are much more and disordered and the amplitude increases obviously. whether the input point of transient excitation is on void area or not is irrelevant with qualitative identification results. So the qualitative identification of the interface separation of concrete-filled steel tube based on the signal of acceleration transducer is feasible and valid.

Over the past few decades, considerable attention has been given to structural control systems to mitigate structural vibration under natural hazards such as earthquakes and extreme weather conditions. Traditional wired structural control systems often employ a large amount of cables for communication among sensors, controllers and actuators. In such systems, implementation of wired sensors is usually quite complicated and expensive, especially on large scale structures such as bridges and buildings. To reduce the laborious installation and maintenance cost, wireless control systems (WCSs) are considered as a novel approach for structural vibration control. In this work, a WCS is developed based on the open source Arduino platform. Low cost, low power wireless sensing and communication components are built on the Arduino platform. Structural control algorithms are embedded within the wireless sensor board for feedback control. The developed WCS is first validated through a series of tests. Next, numerical simulations are performed simulating wireless control of a 3-story shear structure equipped with a semi-active control device (MR damper). Finally, experimental studies are carried out implementing the WCS on the 3-story shear structure in the Intelligent Infrastructure Systems Lab (IISL). A hydraulic shake table is used to generate seismic ground motions. The control performance is evaluated with the impact of modeling uncertainties, measurement noises as well as time delay and data loss induced by the wireless network. The developed WCS is shown to be effective in controlling structural vibrations under several historical earthquake ground motions.

A magnetorheological elastomer (MRE)-based wireless sensor is designed, developed and tested, which is capable of sensing compression and shear forces. The MRE wireless sensor system consists of a disk-shape MRE sample with two thin steel electrodes attached to both sides and two wires connected to electrodes. Electrical resistance of MRE sensor samples changes due to piezoresistance behavior of MRE as various axial and shear stresses are applied. Electrical resistance decreases as the applied compressive axial forces increases, on the other hand, the electrical resistance increases as the applied shear force increases. Different MRE sensor configurations are evaluated for design optimization.

This paper presents a compact, batteryless wireless ultrasound pitch-catch system that wirelessly transmits the excitation signals to the actuator installed on the structure, and acquires the ultrasound sensing signal from the wireless sensor. The principle of frequency conversion is used to transform the ultrasound signals to microwave signals so that it can be wirelessly transmitted without digitization. As such, the power hungry digital-to-analog data conversion at the wireless actuator is eliminated. The wireless sensor node is equipped with a low power amplifier, which can be powered continuously by a microwave energy harvester. In addition, compact microstrip patch antennas are implemented for wireless transmissions, which help to achieve a compact interrogation unit.

In wireless data transmissions processes, the problem of packet loss become an important factor that affects the robustness of wireless data transmission. In order to solve the problem, the compressive sensing (CS) based wireless data transmission approach is proposed in this paper. The specific steps that use the CS approach to reconstruct lost data are as follows: The first step is to encode the original data in a random sampling matrix. Then the original data and the encoded data are sent to the receiving side through the wireless transmission. After the data is received, if there are packets lost, it can be reconstructed by CS approach. The reconstructed data are able to compensate for the incomplete original data in a certain range. In this paper, a wireless sensor network (WSN) based on Wi-Fi is developed for verifying the effectiveness and feasibility of the CS approach. The WSN consists of small nodes with sensors, base stations, PC client. Experimental results show that the wireless sensor network is working properly and steady. Moreover, the CS approach could compensate for the packet loss effectively, and increase the robustness and the speed of wireless transmission greatly.

Cable force is one of the most important parameters in structural health monitoring system integrated on cable stayed bridges for safety evaluation. In this paper, one kind of cable force monitoring system scheme was proposed. Accelerometers inside mobile smart phones were utilized for the acceleration monitoring of cable vibration. Firstly, comparative tests were conducted in the lab. The test results showed that the accelerometers inside smartphones can detect the cable vibration, and then the cable force can be obtained. Furthermore, there is good agreement between the monitoring results of different kinds of accelerometers. Finally, the proposed cable force monitoring system was applied on one cable strayed bridge structure, the monitoring result verified the feasibility of the monitoring system.

The blossoming of sensing solutions based on the use of carbon materials and the pervasive exploration of compressed sensing (CS) for developing structural health monitoring applications suggest the possibility of combining these two research areas in a novel family of smart structures. Specifically, the authors propose an architecture for security-related applications that leverages the tunable electrical properties of a graphite oxide (GO) paper-based tamper-evident seal with a compressed-sensing (CS) encryption/authentication protocol. The electrical properties of GO are sensitive to the traditional methods that are commonly used to remove and replace paper-based tamper-evident seals (mechanical lifting, solvents, heat/cold temperature changes, steam). The sensitivity of the electro-chemical properties of GO to such malicious insults is exploited in this architecture. This is accomplished by using GO paper to physically realize the measurement matrix required to implement a compressive sampling procedure. The proposed architecture allows the seal to characterize its integrity, while simultaneously providing an encrypted/authentication feature making the seal difficult to counterfeit, spoof, or remove/replace. Traditional digital encryption/authentication techniques are often bit sensitive making them difficult to implement as part of a measurement process. CS is not bit sensitive and can tolerate deviation caused by noise and allows the seal to be robust with respect to environmental changes that can affect the electrical properties of the GO paper during normal operation. Further, the reduced amount of samples that need to be stored and transmitted makes the proposed solution highly attractive for power constrained applications where the seal is interrogated by a remote reader.

The authors have developed a capacitive-based thin film sensor for monitoring strain on mesosurfaces. Arranged in a network configuration, the sensing system is analogous to a biological skin, where local strain can be monitored over a global area. The measurement principle is based on a measurable change in capacitance provoked by strain. In the case of bi-directional in-plane strain, the sensor output contains the additive measurement of both principal strain components. In this paper, we present an algorithm for retrieving the directional strain from measurements. The algorithm leverages the dense network application of the thin film sensor to reconstruct the surface strain map. A bi-directional shape function is assumed, and it is differentiated to obtain expressions for planar strain. A least square estimator (LSE) is used to reconstruct the planar strain map from the sensors measurement’s, after the system’s boundary conditions have been enforced in the model. The coefficients obtained by the LSE can be used to reconstruct the estimated strain map or the deflection shape directly. Results from numerical simulations and experimental investigations show good performance of the algorithm, in particular for monitoring surface strain on cantilever plates.

The University of California at San Diego (UCSD), under a Federal Railroad Administration (FRA) Office of Research and Development (R&D) grant, is developing a system for high-speed and non-contact rail defect detection. A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection, paired with a real-time statistical analysis algorithm, has been realized. This system requires a specialized filtering approach based on electrical impedance matching due to the inherently poor signal-to-noise ratio of air-coupled ultrasonic measurements in rail steel. Various aspects of the prototype have been designed with the aid of numerical analyses. In particular, simulations of ultrasonic guided wave propagation in rails have been performed using a Local Interaction Simulation Approach (LISA) algorithm. The system’s operating parameters were selected based on Receiver Operating Characteristic (ROC) curves, which provide a quantitative manner to evaluate different detection performances based on the trade-off between detection rate and false positive rate. Results from the first field test of the non-contact air-coupled defect detection prototype conducted at the Transportation Technology Center (TTC) in Pueblo, Colorado, in October 2014 are presented and discussed in this paper. The results indicate that the prototype is able to detect internal cracks with high reliability.

This paper studies impact induced delamination detection and quantification methods via guided wavefield data and spatial wavenumber imaging. In this study, the complex geometry impact-like delamination damage in a composite laminate is created through the quasi-static indention technique. To detect and quantify the delamination damage, the guided ultrasonic waves are excited through a piezoelectric actuator, and the guided wavefields are measured by a scanning laser Doppler vibrometer. The acquired guided wavefields contain a wealth of information regarding the wave propagation in the composite plate and complex wave interaction at the delamination region. To process the wavefield data and evaluate the delamination damage, the measured wavefields are analyzed through the spatial wavenumber imaging method which can generate an image containing the dominant local wavenumber at each spatial location. For a proof of concept, the approach is first applied to a single Teflon insert simulating a delamination, and then to the complex geometry impact-like delamination damage. The results show that the spatial wavenumber imaging can not only determine the delamination location, but also provide quantitative information regarding the delamination size and shape. The detection results for the impact induced delamination are compared to an ultrasonic C-scan image and wavenumber images are studied for two different excitation frequencies. Fairly good agreement is observed for portions of the delamination, and differences in wavenumber are observed at the two different frequencies. Results demonstrate that the spatial wavenumber imaging is a promising technique for yielding delamination location and size information.

Structural damage identification is a challenging subject in the structural health monitoring research. The piezoelectric impedance-based damage identification, which usually utilizes the matrix inverse-based optimization, may in theory identify the damage location and damage severity. However, the sensitivity matrix is oftentimes ill-conditioned in practice, since the number of unknowns may far exceed the useful measurements/inputs. In this research, a new method based on intelligent inference framework for damage identification is presented. Bayesian inference is used to directly predict damage location and severity using impedance measurement through forward prediction and comparison. Gaussian process is employed to enrich the forward analysis result, thereby reducing computational cost. Case study is carried out to illustrate the identification performance.

In this work, a novel piezoelectric sensor for guided waves detection on laminate composite and metallic structures is presented. The sensor is composed by two electrodes (E1 and E2) on the top surface of the device, plus a common electrode (EC) on the bottom surface, which is bonded to the structure to be inspected. E1 has a circular shape, whereas E2 is shaped as a segment of a logarithmic spiral (or spira mirabilis). Because of this asymmetric shaping, the wavefront of a generic acoustic event (e.g. the one generated by an impact) hits the electrodes in two points whose distance D varies with the Direction of Arrival (DoA) of the wave itself. With a dedicated processing procedure, the information about the distance D first, and then about the DoA can be retrieved from the waveforms acquired and digitized at the two electrodes E1 and E2. In particular, the procedure computes the cross-correlation of the dispersion compensated signals, and extracts the distance D by looking at the position of the maximum of the cross-correlation envelope. Here, a first experimental test is performed to validate the effectiveness of the proposed technology.

Time reversed lamb wave based damage detection is very suitable for online Structural Health Monitoring (SHM). Non linear higher and sub harmonics are generated in the Lamb waves which are generated and sensed using partially de-bonded piezoelectric wafer transducers (PWT) from the host plate. Experimental and numerical studies of the influence of higher harmonics in time reversed reconstruction of Lamb wave in an aluminium plate are presented in this work. 2D finite element simulations are carried out using de-bonded actuator and receiver separately and the influence of actuator de-bonding is found to have more influence on time reversed reconstruction. Experiments are done for transducer de-bonding and the in uence of Lamb wave amplitude for non-linear interaction is studied. Influence of de-bonding length on change in reconstruction is also studied.

These days, various functions in the living spaces are needed because of an aging society, promotion of energy conservation, and diversification of lifestyles. To meet this requirement, we propose “Biofied Building”. The “Biofied Building” is the system learnt from living beings. The various information is accumulated in a database using small sensor agent robots as a key function of this system to control the living spaces. Among the various kinds of information about the living spaces, especially human activities can be triggers for lighting or air conditioning control. By doing so, customized space is possible. Human activities are divided into two groups, the activities consisting of single behavior and the activities consisting of multiple behaviors. For example, “standing up” or “sitting down” consists of a single behavior. These activities are accompanied by large motions. On the other hand “eating” consists of several behaviors, holding the chopsticks, catching the food, putting them in the mouth, and so on. These are continuous motions. Considering the characteristics of two types of human activities, we individually, use two methods, R transformation and variance. In this paper, we focus on the two different types of human activities, and propose the two methods of human activity recognition methods for construction of the database of living space for “Biofied Building”. Finally, we compare the results of both methods.

Robotic orthoses have the potential to provide effective rehabilitation while overcoming the availability and cost constraints of therapists. These orthoses must be characterized by the naturally safe, reliable, and controlled motion of a human therapist's muscles. Such characteristics are only possible in the natural kingdom through the pain sensing realized by the interaction of an intelligent nervous system and muscles' embedded sensing organs.

McKibben fluidic muscles or pneumatic muscle actuators (PMAs) are a popular orthosis actuator because of their inherent compliance, high force, and muscle-like load-displacement characteristics. However, the circular cross-section of PMA increases their profile. PMA are also notoriously unreliable and difficult to control, lacking the intelligent pain sensing systems of their biological muscle counterparts.

Here the Peano fluidic muscle, a new low profile yet high-force soft actuator is introduced. This muscle is smart, featuring bioinspired embedded pressure and soft capacitive strain sensors. Given this pressure and strain feedback, experimental validation shows that a lumped parameter model based on the muscle geometry and material parameters can be used to predict its force for quasistatic motion with an average error of 10 - 15N. Combining this with a force threshold pain sensing algorithm sets a precedent for flexible orthosis actuation that uses embedded sensors to prevent damage to the actuator and its environment.

In performing an effective structural analysis for wind turbine, the simulation of turbine aerodynamic loads is of great importance. The interaction between the wake flow and the blades may impact turbine blades loading condition, energy yield and operational behavior. Direct experimental measurement of wind flow field and wind profiles around wind turbines is very helpful to support the wind turbine design. However, with the growth of the size of wind turbines for higher energy output, it is not convenient to obtain all the desired data in wind-tunnel and field tests. In this paper, firstly the modeling of dynamic responses of large-span wind turbine blades will consider nonlinear aeroelastic effects. A strain-based geometrically nonlinear beam formulation will be used for the basic structural dynamic modeling, which will be coupled with unsteady aerodynamic equations and rigid-body rotations of the rotor. Full wind turbines can be modeled by using the multi-connected beams. Then, a hybrid simulation experimental framework is proposed to potentially address this issue. The aerodynamic-dominant components, such as the turbine blades and rotor, are simulated as numerical components using the nonlinear aeroelastic model; while the turbine tower, where the collapse of failure may occur under high level of wind load, is simulated separately as the physical component. With the proposed framework, dynamic behavior of NREL’s 5MW wind turbine blades will be studied and correlated with available numerical data. The current work will be the basis of the authors’ further studies on flow control and hazard mitigation on wind turbine blades and towers.

In this research, model reference adaptive control is examined for the pitch control of wind turbines that may suffer from reduced life owing to extreme loads and fatigue when operated under a high wind speed. Specifically, we aim at making a trade-off between the maximum energy captured and the load induced. The adaptive controller is designed to track the optimal generator speed and at the same time to mitigate component loads under turbulent wind field and other uncertainties. The proposed algorithm is tested on the NREL offshore 5-MW baseline wind turbine, and its performance is compared with that those of the gain scheduled proportional integral (GSPI) control and the disturbance accommodating control (DAC). The results show that the blade root flapwise load can be reduced at a slight expense of optimal power output. The generator speed regulation under adaptive controller is better than DAC.

As an optical fiber is able to act as a sensing medium, a Brillouin-based sensor provides continuous strain information along an optical fiber. The sensor has been used in a wide range of civil engineering applications because no other tool can satisfactorily detect discontinuity such as a crack. Cracking generates a local strain change on the embedded optical fiber, thus Brillouin optical correlation domain analysis (BOCDA), which offers a high spatial resolution by stimulated Brillouin scattering, is expected to detect a fine crack on concrete structures. The author installed the surface-mounted optical fiber on a concrete deck and periodically monitored strain distribution for seven years. This paper demonstrates how a BOCDA-based strain sensor can be employed to monitor cracks in a concrete surface. Additionally, focusing on another advantage of the sensor, the natural frequency of the deck is successfully measured by dynamic strain history.

Corrosion is a leading cause of failure in metallic transmission pipelines. It significantly impacts the reliability and safety of metallic pipelines. An accurate assessment of corrosion status of the pipelines would contribute to timely pipeline maintenance and repair and extend the service life of the associated pipelines. To assess pipeline corrosion, various technologies have been investigated and the pipe-to-soil voltage potential measurement was commonly applied. However, remote and real-time corrosion assessment approaches are in urgent needs but yet achieved. Fiber optic sensors, especially, fiber Bragg gating (FBG) sensors, with unique advantages of real-time sensing, compactness, immune to EMI and moisture, capability of quasi-distributed sensing, and long life cycle, will be a perfect candidate for longterm pipeline corrosion assessment. In this study, FBG sensors are embedded inside pipeline external coating for corrosion monitoring of on-shore buried metallic transmission pipelines. Detail sensing principle, sensor calibration and embedment are introduced in this paper together with experimental corrosion evaluation testing ongoing. Upon validation, the developed sensing system could serve the purpose of corrosion monitoring to the numerous metallic pipelines across nation and would possibly reduce the pipeline corrosion induced tragedies.

With nearly 25% of bridge infrastructure deemed deficient, repair of concrete structures is a critical need. FRP materials as thin laminates or fabrics are appearing to be an ideal alternative to traditional repair technology, because of their high strength to weight ratios and stiffness to weight ratios. In addition, FRP materials offer significant potential for lightweight, high strength, cost-effective and durable retrofit. One drawback of using CFRP retrofitting is its brittle-type failure; caused by its nearly linear elastic nature of the stress-strain behavior. This causes a strength reduction of the retrofitted member, thus the health of the retrofit applied on the structure becomes equally important to sustain the serviceability of the structure. This paper provides a system to monitor damage on the CFRP retrofits through optical fiber sensors which are woven into the structure to provide damage sensing. Precracked reinforced concrete beams were retrofitted using CFRP laminates with the most commonly used FRP application technique. The beams were tested under constant stress to allow the retrofitting to fail while evaluating the performance of the sensing system. Debonding failure modes at a stress of 9 MPa were successfully detected by TL optical fiber sensors in addition to detection during flexural failure. Real-time failure detection of FRP strengthened beams was successfully achieved and the retrofit damage-monitoring scheme aims at providing a tool to reduce the response time and decision making involved in maintenance of deficient structures.

Ageing of materials and extreme events tend to damage structures, and ancient historical monuments are particularly vulnerable due to their age and long-term exposure to adverse events and influences. As an example, the wall paintings (frescoes) from the seventeenth century BCE found at the archaeological site of Akrotiri (Santorini, Greece) were recovered from volcanic ash in fragments with dimensions ranging from a few centimeters to a few decimeters. Identification of the fracturing patterns is helpful to the process of piecing together the fragments of frescos. Previous work has involved looking at fracturing patterns in frescos that have been reassembled. Recent work has looked at the process by which fractures develop. Current identification techniques involve experimental study of fracture development on plaster molds using a high-speed camera combined with sophisticated algorithms for pattern recognition. However, the use of a high-speed camera is challenging due to very demanding data processing and analysis and some inaccuracies in identification of fracture initialization generated by light conditions. This paper aims to evaluate whether or not short-gauge fiber optic sensors (FOS) based on Fiber Brag-Gratings (FBG), can be used to help identify the fracturing patterns of falling frescoes as a complement to high-speed cameras. In total four tests were performed using surface and embedded sensors on various plaster molds. The data taken by sensors installed on the surface of the mold were more complex to analyze and interpret than the data taken by embedded sensors, since the former reflected combined influence from fracture and bending. While their practicality is challenged by cost, moderately dense arrays of embedded FOS are found to be a plausible complement to the high speed-camera in the experiments.

The global transportation system is massive, open, and dynamic. Existing performance and condition assessments of the complex interacting networks of roadways, bridges, railroads, pipelines, waterways, airways, and intermodal ports are expensive. Hyperspectral imaging is an emerging remote sensing technique for the non-destructive evaluation of multimodal transportation infrastructure. Unlike panchromatic, color, and infrared imaging, each layer of a hyperspectral image pixel records reflectance intensity from one of dozens or hundreds of relatively narrow wavelength bands that span a broad range of the electromagnetic spectrum. Hence, every pixel of a hyperspectral scene provides a unique spectral signature that offers new opportunities for informed decision-making in transportation systems development, operations, and maintenance. Spaceborne systems capture images of vast areas in a short period but provide lower spatial resolution than airborne systems. Practitioners use manned aircraft to achieve higher spatial and spectral resolution, but at the price of custom missions and narrow focus. The rapid size and cost reduction of unmanned aircraft systems promise a third alternative that offers hybrid benefits at affordable prices by conducting multiple parallel missions. This research formulates a theoretical framework for a pushbroom type of hyperspectral imaging system on each type of data acquisition platform. The study then applies the framework to assess the relative potential utility of hyperspectral imaging for previously proposed remote sensing applications in transportation. The authors also introduce and suggest new potential applications of hyperspectral imaging in transportation asset management, network performance evaluation, and risk assessments to enable effective and objective decision- and policy-making.

Measuring static and dynamic displacements for in-service structures is an important issue for the purpose of design validation, performance monitoring and safety assessment of structures. Currently available techniques can be classified into indirect measurement and direct measurement. These methods however have their own problems and limitations Digital sampling moiré method is a newly developed vision-based technique for direct displacement measurement. It uses one camera to capture digital images containing a grating pattern. The images are subsampled and interpolated to generate moiré patterns whose phase information can then be used to calculate displacements of the grating pattern. As the moiré patterns can magnify the pattern’s movement, this technique is expected to provide more accurate displacement measurement than the other vision based approaches. In this study, a digital sampling moiré technique is proposed for measuring two-dimensional structural displacements using a designed grating pattern. The pattern contains two orthogonally inclined gratings and does not have to be perfectly aligned with the image plane. A series of simulation and laboratory tests are conducted to validate the accuracy of the proposed technique. Results show that the technique can achieve accuracy in the order of 10 micrometers in the laboratory. Also, the technique does not seem to suffer from the issue of misalignment between the camera and the pattern and exhibits a potential for accurate measurement of displacement for civil engineering structures.

The development of smart materials for embedding in aerospace composites provides enhanced functionality for future aircraft structures. Critical flight conditions like icing of the leading edges can affect the aircraft functionality and controllability. Hence, anti-icing and de-icing capabilities are used. In case of leading edges made of fibre metal laminates heater elements can be embedded between composite layers. However this local heating causes strains and stresses in the structure due to the different thermal expansion coefficients of the different laminated materials. In order to characterize the structural behaviour during thermal loading full-field strain and shape measurement can be used. In this research, a shearography instrument with three spatially-distributed shearing cameras is used to measure surface displacement gradients which give a quantitative estimation of the in- and out-of-plane surface strain components. For the experimental part, two GLARE (Glass Laminate Aluminum Reinforced Epoxy) specimens with six different embedded copper heater elements were manufactured: two copper mesh shapes (straight and S-shape), three connection techniques (soldered, spot welded and overlapped) and one straight heater element with delaminations. The surface strain behaviour of the specimens due to thermal loading was measured and analysed. The comparison of the connection techniques of heater element parts showed that the overlapped connection has the smallest effect on the surface strain distribution. Furthermore, the possibility of defect detection and defect depth characterisation close to the heater elements was also investigated.

Traditional contact sensors usually break with the failure of structures or model. To solve this issue, a stereovision-based 3D displacement measurement method is proposed to detect the whole process of structural deformations in this paper. A three-floor frame model subjected to earthquake excitation is tested with the proposed method in lab. Experiment results show good agreement with LVDT data during small deformation stage, this verifies that the presented approach is reliable. During large deformation stage, LVDT sensors are destroyed, the dynamic response curves of three-floor frame models are only acquired by the propose method. Experimental results prove that the proposed approach is feasible and useful for monitoring whole-process deformations of structures even at collapse stage.

The potential to return Martian samples to Earth for extensive analysis is in great interest of the planetary science community. It is important to make sure the mission would securely contain any microbes that may possibly exist on Mars so that they would not be able to cause any adverse effects on Earth’s environment. A brazing sealing and sterilizing technique has been proposed to break the Mars-to-Earth contamination chain. Thermal analysis of the brazing process was conducted for several conceptual designs that apply the technique. Control of the increase of the temperature of the Martian samples is a challenge. The temperature profiles of the Martian samples being sealed in the container were predicted by finite element thermal models. The results show that the sealing and sterilization process can be controlled such that the samples’ temperature is maintained below the potentially required level, and that the brazing technique is a feasible approach to break the contamination chain.

The objective of this work was to develop a wireless Spiral Passive Electromagnetic Sensor (SPES) to monitor the complex permittivity of a surrounding medium. The sensor is a self-resonating planar pattern of electrically conductive material. Investigation were conducted to demonstrate the capability of the SPES to monitor humidity and temperature gradients, and acting as an ice protection tool. An oscillating signal is used to interrogate remotely the sensor with a single loop antenna or wiring it directly to a spectrum analyser and monitoring the backscattering signal. The excited sensor responds with its own resonant frequency, amplitude and bandwidth that can be correlated to physical quantities to be monitored. Our studies showed the capability of the sensor to monitor temperature and humidity changes in composite materials and uniformly produce induction heating when the conductive path is activated by an external electric power supply that can be used for deicing of aircraft structures.

The detection of damage in structures at its earliest stages has many economical and safety benefits. Permanent monitoring systems using various forms of sensor networks and analysis methods are often employed to increase the frequency and diagnostic capabilities of inspections. Some of these techniques provide spatial/volumetric information about a given area/volume of a structure. Many of the available spatial sensing techniques can be costly and cannot be permanently deployed (e.g., IR camera thermography). For this reason intricate analysis methods using permanently deployable sensors are being developed (e.g., ultrasonic piezoelectrics, sensing skins). One approach is to leverage the low cost of heaters and temperature sensors to develop an economical, permanently installable method of spatial damage detection using heat transfer. This paper presents a method similar to that of X-ray computed tomography (CT). However, the theories for Xray CT must be adapted to properly represent heat transfer as well as account for the relatively large and immobile sensors spacing used on a structure (i.e., there is a finite number of heaters/sensors permanently installed around the perimeter of the area of interest). The derivation of heat transfer computed tomography is discussed in this paper including two methods for steering the effective heat wave. A high fidelity finite element method (FEM) model is used to verify the analytical derivation of individual steps within the method as well as simulate the complete damage detection technique. Experimental results from both damaged and undamaged aluminum plate specimens are used to validate the FEM model and to justify theoretical assumptions. The simulation results are discussed along with possible improvements and modifications to the technique.

There is a need to integrate tactile sensing into robotic manipulators performing tasks in space environments, including those used to repair satellites. Integration can be achieved by embedding specialized tactile sensors. Reliable and consistent signal interpretation can be obtained by ensuring that sensors with a suitable sensing mechanism are selected based on operational demands, and that materials used within the sensors do not change structurally under vacuum and expected applied pressures, and between temperatures of -80°C to +120°C. The sensors must be able to withstand space environmental conditions and remain adequately sensitive throughout their operating life. Additionally, it is necessary to integrate the sensors into the target system with minimum disturbance while remaining responsive to applied loads. Previous work has been completed to characterize sensors within the selected temperature and pressure ranges. The current work builds on this investigation by embedding these sensors in different geometries and testing the response measured among varying configurations. Embedding material selection was aided by using a dynamic mechanical analyzer (DMA) to determine stress/strain behavior for adhesives and compliant layers used to keep the sensors in place and distribute stresses evenly. Electromechanical characterization of the embedded sensor packages was conducted by using the DMA in tandem with an inductance-capacitance-resistance (LCR) meter. Methods for embedding the sensor packages were developed with the aid of finite element analysis and physical testing to account for specific geometrical constraints. Embedded sensor prototypes were tested within representative models of potential embedding locations to compare final embedded sensor performance.

Comb-drive transducers are made of interdigitized fingers formed by the stationary part known as stator and the moving part known as rotor, and based on the transduction principle of capacitance change. They can be designed as area-change or gap-change mechanism to convert the mechanical signal at in-plane direction into electrical output. The comb-drive transducers can be utilized to differentiate the wave motion in orthogonal directions when they are utilized with the outof- plane transducers. However, their sensitivity is weak to detect the wave motion released by newly formed damage surfaces. In this study, Micro-Electro-Mechanical System (MEMS) comb-drive Acoustic Emission (AE) transducer designs with two different mechanisms are designed, characterized and compared for sensing high frequency wave propagation. The MEMS AE transducers are manufactured using MetalMUMPs (Metal Multi-User MEMS Processes), which use electroplating technique for highly elevated microstructure geometries. Each type of the transducers is numerically modeled using COMSOL Multiphysics program in order to determine the sensitivity based on the applied load. The transducers are experimentally characterized and compared to the numerical models. The experiments include laser excitation to control the direction of the wave generation, and actual crack growth monitoring of aluminum 7075 specimens loaded under fatigue. Behavior and responses of the transducers are compared based on the parameters such as waveform signature, peak frequency, damping, sensitivity, and signal to noise ratio. The comparisons between the measured parameters are scaled according to the respective capacitance of each sensor in order to determine the most sensitive design geometry.

In this work, a small footprint, low power, and light weight sensor node for guided wave detection on laminate composite and metallic structures is presented. This device is meant as a basic building block for smart structure passive sensor networks development. It draws power from a two-wires data-over-power (DoP) network communication interface, which is also used for half-duplex data handling at 200kbps. Each node is roughly 20x24mm, consumes less than 40mW, and weights less than 20 grams, making it attractive for aerospace systems where size, power and weight reduction are crucial. Elastic waves generated from impacts and propagating on the structure are recorded by an innovative, patent-pending, dual-element piezoelectric transducer and processed by an embedded low-voltage 8-bit PIC. A 1Mbit SPI serial SRAM is used for data storage while program instruction are stored in the PIC embedded 7 KB ash. A low-voltage, high-speed, half-duplex RS485 transceiver with an internal, programmable termination resistance is used to interface the PIC to the bus through a filtering mesh of passive components. This mesh also connects to a low-dropout voltage regulator, allowing it to draw power from the DoP bus without interfering with data transmission. A separate gateway device has also been developed: it is capable to simultaneously interface and feed the DoP bus by drawing power either from the USB or from an external power supply. A network counting up to 256 nodes can be implemented and interfaced to a PC for real-time impact detection applications.

This paper presents an experimental verification of a method of evaluating local damage in steel beam-column connections using modal vibratory characteristics under ambient vibrations. First, a unique testing method is proposed to provide a vibration-test environment which enables measurements of modal vibration characteristics of steel beamcolumn connection as damage proceeds. In the testing method, a specimen of structural component is installed in a resonance frame that supports large fictitious mass and the resonance frequency of the entire system is set as the natural frequency of a mid-rise steel building. The specimen is damaged quasi-statically, and resonance vibration tests are conducted with a modal shaker. The proposed method enables evaluation of realistic damage in structural components without constructing a large specimen of an entire structural system. The transition of the neutral axis and the reduction of the root mean square (RMS) of dynamic strain response are tracked in order to quantify damage in floor slabs and steel beams, respectively. Two specimens of steel beam-column connection with or without floor slab were tested to investigate sensitivity of the damage-related features to loss of floor composite action and fractures in steel beams. In the end, by updating numerical models of the specimens using the identified damage-related features, seismic capacities of damaged specimens were estimated.

Fiber composites are becoming increasingly important in different fields of lightweight application. To guarantee the estimated demand of components made of carbon fiber reinforced plastics the use of industrial robots is suggested in production. High velocity of the layup process is addressed to significantly increase the production rate. Today, the layup of the fiber material is performed by gantry systems. They are heavy weight, slow and the variety of possible part shapes is limited. Articulated robots offer a huge operational area in relation to their construction size. Moreover, they are flexible enough to layup fiber material into different shaped molds. Thus, standard articulated robots are less accurate and more susceptible to vibration than gantry systems. Therefore, this paper illustrates an approach to classify volumetric errors to obtain a relation between the achievable speed in production and precision. The prediction of a precision at a defined speed is the result. Based on the measurement results the repeatability of the robotic unit within the workspace is calculated and presented. At the minimum speed that is applicable in production the repeatability is less than 30 mm. Subsequently, an online strategy for path error compensation is presented. The approach uses a multilateration system that consists of four laser tracer units and measures the current absolute position of a reflector mounted at the end-effector of the robot. By calculating the deviation between the planned and the actual position a compensated motion is applied. The paper concludes with a discussion for further investigations.

Emi shielding provided by metal coating on repair fibers and conductive repair chemical maintained overall emi resistance of structural panels as well as provided the basis for eddy current and ultrasonic sensing/monitoring of structural panels. The sensing/repair system was easily inserted into composite processing and survived the heat and pressure of VARTM, resin infusion /pressing and pultrusion processing. The panels were tested with a commercial emi test lab, a commercial non-destructive testing lab, and a structural testing lab, The results were positive and will be presented in the paper.

The impedance based structural health monitoring (SHM) techniques have utilized the electro-mechanical coupling property of piezoelectric materials (piezo-impedance transducers), due to their self-sensing nature (ability to act both as actuators and sensors), and its diminutive in shape and size, cost effectiveness and ease of installation. The adhesive bond acts as an elastic medium which facilitates the transfer of stresses and strains developed due to piezo displacement and also couples the impedance of PZT patch with that of the host structure. The sensitivity of the electro-mechanical impedance (EMI) technique can be enhanced by understanding shear mechanism phenomena of the adhesive layer. This paper reviews the existing shear lag models and discuss the recent advances in impedance based coupled piezo-structural model duly considering the shear lag effect with all responsible piezo-mechanical parameters.

Traditional modal-based methods, which identify damage based upon changes in vibration characteristics of the structure on a global basis, have received considerable attention in the past decades. However, the effectiveness of the modalbased methods is dependent on the type of damage and the accuracy of the structural model, and these methods may also have difficulties when applied to complex structures. The extended Kalman filter (EKF) algorithm which has the capability to estimate parameters and catch abrupt changes, is currently used in continuous and automatic structural damage detection to overcome disadvantages of traditional methods. Structural parameters are typically slow-changing variables under effects of operational and environmental conditions, thus it would be difficult to observe the structural damage and quantify the damage in real-time with EKF only. In this paper, a Statistical Process Control (SPC) is combined with EFK method in order to overcome this difficulty. Based on historical measurements of damage-sensitive feathers involved in the state-space dynamic models, extended Kalman filter (EKF) algorithm is used to produce real-time estimations of these features as well as standard derivations, which can then be used to form control ranges for SPC to detect any abnormality of the selected features. Moreover, confidence levels of the detection can be adjusted by choosing different times of sigma and number of adjacent out-of-range points. The proposed method is tested using simulated data of a three floors linear building in different damage scenarios, and numerical results demonstrate high damage detection accuracy and light computation of this presented method.

Changes in environmental conditions (such as temperature and humidity) and boundary conditions have been observed to have significant impact on structure's dynamic properties [1-6]. In general, environmental factors affect structures in a complicated manner such that it may result in support movement to strengthen or weaken the constraints [6]. Such changes of boundary conditions also can lead to significant variation of structure’s modal properties. However, few studies have considered the existence of both temperature and boundary condition as the combined contributing factors in changing structure’s dynamic properties.

This paper proposes a numerical study to analyze structure’s dynamic properties under combined influence of temperature and boundary condition. A beam finite element model that can consider the changes in both temperature and boundary condition is established. Numerical study is conducted to reveal the relationship between the variation of the beam’s dynamic properties and the changes of its boundary condition as well as ambient temperature. The obtained conclusion will provide insights of the influence of these two factors on future dynamic based structural health monitoring studies.

While the objective of structural design is to achieve stability with an appropriate level of reliability, the design of systems for structural health monitoring is performed to identify a configuration that enables acquisition of data with an appropriate level of accuracy in order to understand the performance of a structure or its condition state. However, a rational standardized approach for monitoring system design is not fully available. Hence, when engineers design a monitoring system, their approach is often heuristic with performance evaluation based on experience, rather than on quantitative analysis. In this contribution, we propose a probabilistic model for the estimation of monitoring system effectiveness based on information available in prior condition, i.e. before acquiring empirical data. The presented model is developed considering the analogy between structural design and monitoring system design. We assume that the effectiveness can be evaluated based on the prediction of the posterior variance or covariance matrix of the state parameters, which we assume to be defined in a continuous space. Since the empirical measurements are not available in prior condition, the estimation of the posterior variance or covariance matrix is performed considering the measurements as a stochastic variable. Moreover, the model takes into account the effects of nuisance parameters, which are stochastic parameters that affect the observations but cannot be estimated using monitoring data. Finally, we present an application of the proposed model to a real structure. The results show how the model enables engineers to predict whether a sensor configuration satisfies the required performance.

This paper describes the application on a new mechanical implementation of an inertial seismic sensor, configurable also as an force-balanced accelerometer, consisting of monolithic full symmetric Folded Pendulum equipped with an high sensitivity optical readout. The seismic sensor is, therefore, compact, light, scalable, resonant frequency tunable, with large measurement band, low thermal noise and with good immunity to environmental noises. The measured minimum displacement noise is in very good agreement with the theoretical ones. Typical applications are in the field of earthquake engineering, geophysics, civil engineering and in all applications requiring large band-low frequency performances coupled with high sensitivities.

We propose a system that controls a nap environment considering respiration rates and music tempo by using a sensor agent robot. The proposed system consists of two sub-systems. The first sub-system measures respiration rates using optical flow. We conducted preparatory experiments to verify the accuracy of this sub-system. The experimental results showed that this sub-system can measure the respiration rates accurately despite several positional relationships. It was also shown that the accuracy could be affected by clothes, movements and light. The second sub-system we constructed was the music play sub-system that chooses music with the certain tempo corresponding to the respiration rates measured by the first sub-system. We conducted verification experiments to verify the effectiveness of this music play sub-system. The experimental results showed the effectiveness of varying music tempo based on the respiration rates in taking a nap. We also demonstrated this system in a real environment; a subject entered into the room being followed by ebioNα. When the subject was considered sleeping, ebioNα started measuring respiration rates, controlling music based on the respiration rates. As a result, we showed that this system could be realized. As a next step, we would like to improve this system to a nap environment control system to be used in offices. To realize this, we need to update the first sub-system measuring respiration rates by removing disturbances. We also need to upgrade music play sub-system considering the numbers of tunes, the kinds of music and time to change music.

Although each person has own preferences, living spaces which can respond to various preferences and needs have not become reality. Focusing on the lighting environments which influence on the impression of living spaces, this research aims to offer comfortable lighting environments for each resident by a flexible control. This research examines the relationship between lighting environments and human behaviors considering colored lights. In accord with the relationship, this research proposes an illuminance-color control system which flexibly changes spatial environments responding to human conditions. Firstly, the psychological evaluation was conducted in order to build human models for various environments. As a result, preferred lighting environments for each examinee were determined for particular behaviors. Moreover, satisfaction levels of lighting environments were calculated by using seven types of impression of the environments as parameters. The results were summarized as human models. Secondly, this research proposed “Homeostasis Lighting Control System”, which employs the human models. Homeostasis lighting control system embodies the algorithm of homeostasis, which is one of the functions of the physiological adaptation. Human discomfort feelings are obtained automatically by the sensor agent robot. The system can offer comfortable lighting environments without controlling environments by residents autonomously based on the information from the robot. This research takes into accounts both illuminance and color. The robot communicates with the server which contains human models, then the system corresponds to individuals. Combining these three systems, the proposed system can effectively control the lighting environment. At last, the feasibility of the proposed system was verified by simulation experiments.

Marine transportation plays a significant role in the modern transport sector due to its advantage of low cost, large capacity. It is being attached enormous importance to all over the world. Nowadays the related areas of product development have become an existing hot spot. DSP signal processors feature micro volume, low cost, high precision, fast processing speed, which has been widely used in all kinds of monitoring systems. But traditional DSP code development process is time-consuming, inefficiency, costly and difficult. MathWorks company proposed Model-based Design (MBD) to overcome these defects. By calling the target board modules in simulink library to compile and generate the corresponding code for the target processor. And then automatically call DSP integrated development environment CCS for algorithm validation on the target processor. This paper uses the MDB to design the algorithm for the ship heave motion monitoring system. It proves the effectiveness of the MBD run successfully on the processor.

A finite element model of the hemispherical resonator gyro (HRG) is established and the natural frequencies and vibration modes are investigated. The matrix perturbation technology in the random finite element method is first introduced to analyze the statistical characteristics of the natural frequencies of HRG. The influences of random material parameters and dimensional parameters on the natural frequencies are quantitatively described based on the probability theory. The statistics expressions of the random parameters are given and the influences of three key parameters on natural frequency are pointed out. These results are important for design and improvement of high accuracy HRG.

Wireless excitation of Piezo-Wafer-Active-Sensors (PWAS) was achieved using Low-frequency coils produced via Tailored-Fiber-Placement. Carbon Fiber Reinforced Polymer behaves as conductor and depending on the frequency it shields radio waves; this effect is rising at high-frequency. A high permeability material was placed under the highfrequency antenna and re-tuning was performed to improve the quality of transmission. In this manner sensor responses were successfully transmitted wirelessly by analog amplitude modulation. The signals were evaluated to verify the functionality in presence of defects like delamination or holes. Generated power was confirmed to be enough to excite the actuator.

Fiber Bragg Grating (FBG) sensors are embedded into Stainless Steel (SS) 316 components using bespoke Selective Laser Melting (SLM) technology. SS 316 material is added on substrates by SLM, incorporating U-shaped grooves with dimensions suitable to hold nickel coated optical fibers. Coated optical fibers containing fiber Bragg gratings for strain monitoring are placed in the groove. Melting subsequent powder layer on top of the fiber completes the embedding. Strain levels exceeding 3 mε are applied to specimens and are measured by embedded fiber optic sensors. Elastic deformation of the steel component is reliably measured by the Bragg grating from within the component with high accuracy. During plastic deformation of the steel the optical fiber is slipping due to poor adhesive bonding between fused silica and metal surround.

In this paper, innovative multilayer insulation coatings are investigated to eliminate the environmental effects of spacecraft on-surface monitoring system in harsh environments and ultimately adjust the sensitivity the sensors towards the parameters needed to be sensed. The design of the composite insulation is guided through theoretical and numerical modeling analysis of heat transfer and thermal stress progressing. Detail theoretic, numerical, and experimental analysis proved the feasibility of the proposed multilayer structure of the insulation to work up to 700°C without inducing significant deformation on the top of sensor surface from heat.

Using more and more controlled systems in future aircraft the need of flexible sensors to be applied on curved aircraft structures increases. An appropriate substrate material for such flexible sensors is polyimide, which is available both as ready-made foil and as liquid polyimide to be spun-on. Latest results in producing and processing of polyimide layers with a thickness of down to 1 μm including designs for thin foil sensors are presented respectively. The successful processing of liquid polyimide is outlined first including the spin-on procedure, soft bake and curing for polymerization. Parameters for spin-on volume and rotation speed on glass substrates along with a comparison with ordinary polyimide foil are presented. High-precision structuring of the polyimide layer is performed either by etching (wet-etching as well as dry etching in a barrel etcher) or ablative removal using a femtosecond laser. In combination with a layer of silicon nitride as an inorganic diffusion barrier a reliable protection for water tunnel experiments can be realized. The fabrication of a protection layer and test results in water with protected sensors are presented. The design of a hot-film anemometric sensor array made on spin-on polyimide is demonstrated. With a thickness of down to 7 μm the sensors can be applied on the surface of wind tunnel models and water tunnel models without impacting the flow substantially. Additionally both the concept and recent results of a silicon sensor integrated in a polyimide foil substrate that can measure pressure as a complementary measurand for aeronautics are illustrated.

Based on image processing technology, a laser identification method of displacement monitoring with high-efficiency and low-cost has been proposed. Using laser spot video identification method in landslide monitoring, displacement, the main specialty of the sliding slope may be obtained and the monitoring efficiency may be improved. Fix the laser on the object and project the laser spot onto a fixed screen. When the object movement occurs, the camera fixed in front of the screen will shoot the entire movement of the laser spot on the screen. In this way, the displacement of the object will be obtained by analyzing the movement state of the spot. Experiments have been conducted, which contain static displacement experiments including cyclic loading test experiments and random loading experiments, as well as dynamic displacement. Results are proved well by comparison with the data that a laser displacement sensor collected. A great quantity of tests demonstrated that laser identification method of displacement monitoring with high-accuracy and low-cost is now what we have explored.

Recently, the number of single households is drastically increased due to the growth of the aging society and the diversity of lifestyle. Therefore, the evolution of building spaces is demanded. Biofied Building we propose can help to avoid this situation. It helps interaction between the building and residents’ conscious and unconscious information using robots. The unconscious information includes emotion, condition, and behavior. One of the important information is thermal comfort. We assume we can estimate it from human face. There are many researchs about face color analysis, but a few of them are conducted in real situations. In other words, the existing methods were not used with disturbance such as room lumps. In this study, Kinect was used with face-tracking. Room lumps and task lumps were used to verify that our method could be applicable to real situation. In this research, two rooms at 22 and 28 degrees C were prepared. We showed that the transition of thermal comfort by changing temperature can be observed from human face. Thus, distinction between the data of 22 and 28 degrees C condition from face color was proved to be possible.

In this paper, we presented a microstrip patch antenna sensor that is capable to measure the shear and normal deformations simultaneously. The sensor was designed based on the electromagnetic interference between a microstrip patch antenna and a metallic reflector separated by a distance. By placing the reflector on top of the patch antenna, the electromagnetic wave radiated by the patch antenna is reflected by the reflector and interferes with the electromagnetic field of the radiation patch, which in turn changes the antenna resonant frequencies. Since the antenna resonant frequencies are related to the lateral and vertical positions of the metallic reflector, the shear force and normal pressure that shift the reflector laterally and vertically can be detected by monitoring the antenna resonant frequencies. The numerical simulation and experimental measurements were carried out to evaluate the relationship between the antenna resonant frequencies and the shear and normal displacements. A data processing scheme was developed to inversely determine the shear and normal displacements from the antenna resonant frequencies.

In the present state of the art, the function integration into lightweight metal structures is generally based upon adhesive bonding of sensors or actuators to the surface. A new technology enables a direct structural integration of lead-zirconatetitanate (PZT) fibers into local microstructures of metal sheets and subsequent joining by forming. This provides a complete functional integration of the piezoelectric ceramic in the metal for sensors and actuators purposes. In a further process step, the composite is shaped by deep drawing with a cup with double curvature radii of 100 mm into a complex 3D surface. During the shaping process it is expected that the PZT- fibers get damaged with the result of degradation of the piezoelectric function. This paper describes the application of various surface processing methods to improve the shaping behavior of the piezoceramic fibers.

The production of interconnected parallel fibers is based on piezoceramic plates. The plates are treated by different surface processing. One experimental series is lapped and another series is extra polished by chemical mechanical polishing (CMP). The resulting plates were examined with regard to the fracture strength and the degradation of the piezoelectric properties during manufacturing and operation. It has been shown that the lapped and polished plates have a clearly better persistence with regard to the shaping processes compared to the unprocessed plates. The best results in this process were achieved by the polished plates, which is also transferable to the fibers. Furthermore, the piezoelectric characteristics were better preserved by the lapped and polished plates and fibers.

Advancements in the aerospace, defense and energy markets are being made possible by increasingly more sophisticated systems and sub-systems which rely upon critical information to be conveyed from the physical environment being monitored through ever more specialized, extreme environment sensing components. One sensing parameter of particular interest is dynamic pressure measurement. Crossing the boundary of all three markets (i.e. aerospace, defense and energy) is dynamic pressure sensing which is used in research and development of gas turbine technology, and subsequently embedded into a control loop used for long-term monitoring. Applications include quantifying the effects of aircraft boundary layer ingestion into the engine inlet to provide a reliable and robust design. Another application includes optimization of combustor dynamics by “listening” to the acoustic signature so that fuel-to-air mixture can be adjusted in real-time to provide cost operating efficiencies and reduced NO_x emissions. With the vast majority of pressure sensors supplied today being calibrated either statically or “quasi” statically, the dynamic response characterization of the frequency dependent sensitivity (i.e. transfer function) of the pressure sensor is noticeably absent. The shock tube has been shown to be an efficient vehicle to provide frequency response of pressure sensors from extremely high frequencies down to 500 Hz. Recent development activity has lowered this starting frequency; thereby augmenting the calibration bandwidth with increased frequency resolution so that as the pressure sensor is used in an actual test application, more understanding of the physical measurement can be ascertained by the end-user.

This paper presents a novel pressure sensor consisting of a low-cost microstrip patch antenna placed a distance from a metal reflection plate. The pressure applied on the plate changes the distance between the metal plate and the patch antenna, which shifts the resonant frequency of the antenna sensor. The operation principle of the pressure sensor is firstly presented. Subsequently, the design and fabrication of the antenna sensor as well as the electromagnetic (EM) simulations of its response to the applied pressure are described. Finally, static experiments are performed to validate the performance of the pressure sensor and the results are discussed.

A Floquet-based damage detection methodology for cracked rotor systems is developed and demonstrated on a shaft-disk system. This approach utilizes measured changes in the system natural frequencies to estimate the severity and location of shaft structural cracks during operation. The damage detection algorithms are developed with the initial guess solved by least square method and iterative damage parameter vector by updating the eigenvector updating. Active Magnetic Bearing is introduced to break the symmetric structure of rotor system and the tuning range of proper stiffness/virtual mass gains is studied. The system model is built based on energy method and the equations of motion are derived by applying assumed modes method and Lagrange Principle. In addition, the crack model is based on the Strain Energy Release Rate (SERR) concept in fracture mechanics. Finally, the method is synthesized via harmonic balance and numerical examples for a shaft/disk system demonstrate the effectiveness in detecting both location and severity of the structural damage.

A two dimensional constitutive model capable of predicting the magneto-mechanical response of a magnetic shape memory alloy (MSMA) has been developed and calibrated using a zero field-variable stress test¹. This calibration approach is easy to perform and facilitates a faster evaluation of the three calibration constants required by the model (vs. five calibration constants required by previous models^2,3). The calibration constants generated with this approach facilitate good model predictions of constant field-variable stress tests, for a wide range of loading conditions¹. However, the same calibration constants yield less accurate model predictions for constant stress-variable field tests. Deployment of a separate calibration method for this type of loading, using a varying field-zero stress calibration test, also didn’t lead to improved model predictions of this loading case. As a result, a sensitivity analysis was performed on most model and material parameters to identify which of them may influence model predictions the most, in both types of loading conditions. The sensitivity analysis revealed that changing most of these parameters did not improve model predictions for all loading types. Only the anisotropy coefficient was found to improve significantly field controlled model predictions and slightly worsen model predictions for stress controlled cases. This suggests that either the value of the anisotropy coefficient (which is provided by the manufacturer) is not accurate, or that the model is missing features associated with the magnetic energy of the material.

Structural health monitoring has drawn significant attention in the past decades with numerous methodologies and applications for civil structural systems. Although many researchers have developed analytical and experimental damage detection algorithms through vibration-based methods, these methods are not widely accepted for practical structural systems because of their sensitivity to uncertain environmental and operational conditions. The primary environmental factor that influences the structural modal properties is temperature. The goal of this article is to analyze the natural frequency-temperature relationships and detect structural damage in the presence of operational and environmental variations using modal-based method. For this purpose, correlations between natural frequency and temperature are analyzed to select proper independent variables and inputs for the multiple linear regression model and neural network model. In order to capture the changes of natural frequency, confidence intervals to detect the damages for both models are generated. A long-term structural health monitoring system was installed on an in-service highway bridge located in Meriden, Connecticut to obtain vibration and environmental data. Experimental testing results show that the variability of measured natural frequencies due to temperature is captured, and the temperature-induced changes in natural frequencies have been considered prior to the establishment of the threshold in the damage warning system. This novel approach is applicable for structural health monitoring system and helpful to assess the performance of the structure for bridge management and maintenance.

To harvest energy from human motion and generate power for the emerging wearable devices, energy harvesters are required to work at very low frequency. There are several studies based on energy harvesting through human gait, which can generate significant power. However, when wearing these kind of devices, additional effort may be required and the user may feel uncomfortable when moving. The energy harvester developed here is composed of a 10 μm PZT thin-film deposited on 50 μm thick stainless steel foil by the aerosol deposition method. The PZT layer and the stainless steel foil are both very thin, thus the patch is highly flexible. The patch can be attached on the skin to harvester power through human motions such as the expansion of the chest region while breathing. The energy harvester will first be tested with a moving stage for power output measurements. The energy density can be determined for different deformation ranges and frequencies. The fabrication processes and testing results will all be detailed in this paper.

This paper focuses on the study of the effect of sensor fault when large sensor arrays (for example Fiber Bragg Grating arrays) are considered. Indeed, sensor arrays provide a distributed measurement of the structure vibrations, allowing the design of optimized control logics. Anyway, due to the large number of sensors, the reliability is lower and the malfunctioning of one or more sensors can occur. For this reason, an online identification of faults is important, so that the information can be taken into account in the definition of control law.

The effect of sensor fault on the measurement of structure vibrations will be investigated and a method for the identification of sensor faults is proposed. Numerical tests on a beam equipped with an array of FBG sensors will be reported.

Ultrasonic guided wave technology is one of the more recent developments in the field of non-destructive evaluation. In contrast to conventional ultrasonic, this technology requires exposing only the areas where the transducers will be placed, hence requiring minimal insulation removal and excavation for buried pipes. This paper discusses how this technology can be used to detect defects in pipes under different conditions. Here the experiments were performed on small diameter pipes (<5 cm diameter); which were bare pipe, buried pipe and bitumen coated pipe. The results were gathered to see the effectiveness of this technology in detecting defects. Experiments were conducted using two dry coupled piezoelectric transducers, where one of them transmitted guided waves along the pipe and the other received them. The transducers produced tangential displacement, thereby generating the fundamental torsional mode T(0,1). In order to assess whether having multiple transducers has any effect on the resultant waveform, the receiving transducer was rotated around the circumference of the pipe.

Terfenol-D resonant transducers have some advantages, such as high energy density and high vibrational amplitude, that make them suitable for working in a wide range of application. On the contrary, the main drawback is that operating frequency is fixed and correspond to the resonance frequency of the device itself. If working frequency is far away from the resonance, efficiency of the transducer decreases suddenly. In this paper, an attempt to design and simulation of a multi-resonance sonic transducer is presented. The idea is to increase the range of operating frequencies of about 1.5 kHz. This can be obtained by exploiting ΔE effect in Terfenol-D in response to changes in mechanical preload and magnetic bias. Design procedure is validated by a finite element commercial software and effects of changing resonance frequency in vibrational mode shape of the transducer are presented. The magnetic circuit of the transducer is designed to minimize flux leakage and it is simulated with ANSYS12.

Results of this paper can help to design the more flexible transducer in operating frequency and modal shape.

Terfenol-D resonance transducer has high energy-density and high vibration amplitude. These features make them good selection for using in different applications such as liquid atomizers and sonar transducers. Operating mode of the Terfenol- D transducer plays an important role in efficiency of it. It can also change some parameters of the transducer such as quality factor. In this paper, experimental comparative study between first and second longitudinal modes of vibration in the Terfenol-D transducer is presented. It contains the mechanical quality factor, band with frequency and also effect of changing Young modulus in resonance frequency and mode shape. For this purpose, a resonance transducer for working in 3 kHz in first mode and 8.25 kHz in second mode has been designed and fabricated. In design procedure, preload mechanism location is considered as nodes. Quality factor and bandwidth is calculated experimentally and resonance frequency and mode shape has been calculated both with analytical method and ANSYS12 FEM commercial software. Results show that higher quality factor in the second mode shape and this mode shows lower sensitivity with Young modulus .

Fatigue cracks have been one of the major factors for the deterioration of steel bridges. In order to maintain structural integrity, monitoring fatigue crack activities such as crack initiation and propagation is critical to prevent catastrophic failure of steel bridges due to the accumulation of fatigue damage. Measuring the strain change under cracking is an effective way of monitoring fatigue cracks. However, traditional strain sensors such as metal foil gauges are not able to capture crack development due to their small size, limited measurement range, and high failure rate under harsh environmental conditions. Recently, a newly developed soft elastomeric capacitive sensor has great promise to overcome these limitations. In this paper, crack detection capability of the capacitive sensor is demonstrated through Finite Element (FE) analysis. A nonlinear FE model of a standard ASTM compact tension specimen is created which is calibrated to experimental data to simulate its response under fatigue loading, with the goal to 1) depict the strain distribution of the specimen under the large area covered by the capacitive sensor due to cracking; 2) characterize the relationship between capacitance change and crack width; 3) quantify the minimum required resolution of data acquisition system for detecting the fatigue cracks. The minimum resolution serves as a basis for the development of a dedicated wireless data acquisition system for the capacitive strain sensor.

Magnetorheological (MR) dampers are promising for vehicle suspensions, by virtue of their adaptive properties. During the everyday use of vehicles, a lot of energy is wasted due to the energy dissipation by dampers under the road irregularities. On the other hand, extra batteries are required for the current MR damper systems. To reduce the energy waste and get rid of the dependence on extra batteries, in this paper, regenerative MR dampers are proposed for vehicle suspensions, which integrate energy harvesting and controllable damping functions. The wasted vibration energy can be converted into electrical energy and power the MR damper coil. A regenerative MR damper for vehicle suspensions is developed. Damping force and power generation characteristics of the regenerative MR damper were modeled and analyzed. Then the damper is applied to a 2 DOF suspension system for system simulation under various road conditions. Simulation results show that riding comfort can be significantly improved, while harvesting energy for other use in addition to supply power for the controlled MR damper.