关键词: 小波变换；模态分析；端部效应；最小二乘支持向量机（LS-SVM）

Abstract:

A method that the improved Morlet wavelet was used to identify the modal parameter was described systematically, and the wavelet parameter was optimized by the wavelet entropy. In the meantime, in order to resolving the end effect of the wavelet analysis a method that the LS-SVM was used to predict the wavelet skeleton was put forward. The results of simulation analysis and experimental analysis demonstrate that the time series forecasting method based on LS-SVM is applied to resolve the end effect of modal analysis based on Morlet wavelet is effective to identify the modal parameter accurately and restrain the end effect. And the accuracy is the highest among methods based on radial basis function(RBF) neural network and based on time-varying autoregressive(TVAR).

Key words: wavelet transform, modal analysis, end effect, least squares sport vector machine(LS-SVM)