Sand deposition is the major problem of Nepalese rivers and it causes substantial impact to different sectors including hydropower generation, natural resource management, and many others. Due to the typical nature of soil and sand of Nepalese mountains it has almost become impossible to predict and manage the upcoming natural disasters and hazards. Sand deposition in rivers affect landslides, aquatic life of rives, environmental disorders and many others. Sedimentation causes not only disasters but also reduces the overall efficiency of hydropower generation units as well. A systematic approach to the problem has been identified in this work. Sand particles are collected from the erosion sensitive power plants and its digital images have been acquired. Software has been developed on MATLAB 6.5 platform to extract the exact shape of sand particles collected. These shapes have further been analyzed by artificial neural network. This network has been first trained for the known input and known output. After that it is trained for unknown input and known output. Finally these networks can recognize any shape given to it and gives the shape which is nearest to the seven predefined shape. The software is trained for seven types of shapes with shape number 1 to 7 in increasing number of sharp edges. The shape with shape number seven is having large number of sharp edges and considered as most erosive where as shape with shape number one is having round edges and considered as least erosive.

Date Published: 8 November 2005
PDF: 9 pages
Proc. SPIE 5996, Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, 59960X (8 November 2005); doi: 10.1117/12.630127

Published in SPIE Proceedings Vol. 5996:
Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality
Yud-Ren Chen; George E. Meyer; Shu-I Tu, Editor(s)