STEPWISE MODEL UPDATING METHOD BASED ON SUBSTRUCTURES AND GA-ANN

The finite element model need to be updated according to actual dynamic responses in structural damage detection and health monitoring. The model updating method based on artificial neural network (ANN) is improved in this study. Because too much samples are demanded for training ANN, the uniform design method is used to produce samples to reduce the amount of samples in the process of structural damage simulation, thus the computation efficiency is enhanced. The genetic algorithm is used to optimize the initial weight of back propagation network and as a result the operation velocity is enhanced. A stepwise model updating method based on substructures and ANN is presented. A structure is divided into multilayer substructures, and the updating is taken step by step according to appropriate damage factors. A dome structure is selected as an example and two damage factors—the frequencies and the wavelet packet decomposition (WPD) energy spectrums are investigated. The results show that both factors can give accurate results by using this method but the latter is much more practicable.