Application of wavelet and neural network in dealing with dynamic testing signals of piles
Mai Rong · Shuiwen dizhi gongcheng dizhi · 2004
Based on the time-frequency locatization of wavelet transform and the nonlinear mapping of neural network, a method of dynamic testing signals combining with the advantage of wavelet analysis and neural network is presented. Some features are extracted from the frequency spectrum analysis at the various resolution of the dyadic wavelet transform. These features are taken the wavelet neural network as the input patterns for training and classifying. Then, it can be used to diagnose the faults of piles. The result of insitu test is in good agreement with numerical simulation and it show that this method can successfully be applied to the identification and diagnosis of plies faults as an intelligentized classifier.