Study Of Theory And Applied Method For Structural Damage Detection Based On Artificial Neural Networks

The detection, location, and estimation problem of structural damage has been the important subject of structure engineering 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.Firstly, the principle structural damage detection using artificial neural networks (ANN) is expounded in the paper. Then, the development of ANN technique in application of structural detection is reviewed, some main achievements summarized, and the main obstacles encountered are raised. Secondly, the paper is verified theoretically that the natural frequency changes of structure contain the information such as location and degree of the damage. Finally, based on this theory, use proper computer program to simulation different damage of suspended panel, extract 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.