Adaptive Selection of Wavelet Basis Based on Genetic Algorithm and Its Application

Abstract

An adaptive selection of wavelet basis is presented in this paper. Based on the constructive theory of orthogonal binary wavelet basis, a parameter expression equation of orthogonal wavelet basis is constructed and a adaptive goal function of de-noised effect is defined. By applying genetic optimization method, the best wavelet basis was obtained, and the correlative arithmetic is presented. Applying the optimal wavelet basis to eliminate noises from signals, and computed the correlation dimension of the de-noised signals as fault feature. Simulation and experiments show that the adaptive wavelet de-noising makes the mechanical fault feature extraction more reliable.