Abstract: A new method of detecting cardan shaft dynamic unbalance in high-speed train is proposed applying the combination between the second generation wavelet transform(SGWT) and singular value decomposition(SVD) contrary to the basic defect of overlap frequency existing in the SGWT. The vibration acceleration signals installed on gimbal next to gearbox are decomposed through the SGWT to get the different scale decomposition signal. The Hankel matrix, which is constructed throng the single scale approximate decomposition signal, is orthogonally decomposed by SVD, the key singular values are selected to reconstruct vibration sign on the base of key stacks of singular values. Fourier spectrum of the reconstructed signal through SVD is applied to detect cardan shaft dynamic unbalance in high-speed train, eliminate the effect of overlap frequency on submerging unbalance fault features and highlight the failure characteristics. The method is verified by test data in the condition of dynamic unbalance, the results show that the method can effectively seize the fault features caused by cardan shaft dynamic unbalance, such as fundamental, multiplier, divider frequency. With comparison to the traditional wavelet decomposition, the simple SGWT, the clarity and failure characterization force of Fourier spectrum are significantly improved.

Key words: high-speed train;cardan shaft;the second generation wavelet transform