Title :
Neural network analysis of structural damage due to corrosion
Author :
Furuta, Hitoshi ; Deguchi, Tsunenobu ; Kushida, Moriyoshi
Author_Institution :
Dept. of Inf., Kansai Univ., Osaka, Japan
Abstract :
We attempt to develop a practical decision support system for the damage assessment of structural corrosion. This system aims to aid inexperienced inspectors to judge whether a certain bridge should be repaired or not. For this purpose, it is attempted to apply the neural network technique for the damage assessment. The learning ability of the neural network is useful to save the working time and load necessary in the inspection and analysis
Keywords :
coatings; corrosion; decision support systems; image processing; inspection; learning (artificial intelligence); maintenance engineering; neural nets; structural engineering computing; analysis; corrosion; damage assessment; decision support system; inexperienced inspectors; inspection; learning ability; load; neural network analysis; structural damage; working time; Bridges; Computer aided manufacturing; Corrosion; Data mining; Decision support systems; Image processing; Inspection; Manufacturing processes; Neural networks; Paints;
Conference_Titel :
Uncertainty Modeling and Analysis, 1995, and Annual Conference of the North American Fuzzy Information Processing Society. Proceedings of ISUMA - NAFIPS '95., Third International Symposium on
Conference_Location :
College Park, MD
Print_ISBN :
0-8186-7126-2
DOI :
10.1109/ISUMA.1995.527678
