Please use this identifier to cite or link to this item:
|Title:||Damage assessment of structures from changes in curvature damage factor using artificial neural network|
|Authors:||Tripathy, Rashmi Ranjan|
|Series/Report no.:||Int. Cl.7 G 06 N 3/06|
|Abstract:||This paper presents a neural network based approach to detect and assess the structural damage. The basic strategy applied in this study is to train a neural network to recognize the behaviour of the undamaged structure as well as the structure with various possible damaged states. Curvature damage factor (CDF) is used as a possible candidate for the damage identification by error back-propagation training algorithm (EBPTA). When this trained network is subjected to the measured response, it should be able to detect any existing damage. This idea is applied on a cantilever beam and a plane frame. The results show the efficiency of the developed algorithm.|
|ISSN:||0975-1017 (Online); 0971-4588 (Print)|
|Appears in Collections:||IJEMS Vol.11(5) [October 2004]|
Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.