Neural Networks For Structural Damage Detection

The detection, location, and estimation problem of structural damage has been the subject of much current research in recent years. The damage identification methods have been widely used in aeronautical, civil, mechanical and nuclear structures. It is polytechnic method constructed on the damage theory, sensor technology, signal analysis, computer science and artificial networks. Relative to the traditional technology of structural damage identification, this paper mainly studies the method based on the combination of the static modal analysis and artificial networks.In this paper, it is verified theoretically that the natural frequency changes of structure contain the information such as location and degree of the damage, based on this theory, use proper computer program to simulate different damage of a frame structure and a truss bridge separately, extract the natural frequency changes and form the input parameters of the improved BP algorithm network, detect the structural damage by the trained networks, the result shows the effectiveness of this method. In the end, through a simple structural damage identification experiment, the above conclusion is farther verified.