Abstract：Aiming at the strong background noise involved in the non-stationary signals of fault gear and the difficulty to obtain fault frequencies in practice, a new fault diagnosis method is proposed based on dual-tree complex wavelet transform and singular value difference spectrum. Firstly, original fault signals are decomposed into several different frequency band components through dual-tree complex wavelet decomposition; but it is often difficult to obtain fault frequencies exactly from components because of strong background noise. Secondly, Hankel matrix is constructed by the component which contains the fault information, and the singular value difference spectrum can be obtained after singular value decomposition. Then the number of singular value will be obtained to realize signal de-noising by the SVD reconstruction .Finally, the fault frequency can be identified accurately by hilbert envelope spectrum. The results of the experiments and engineering application show that the fault feature of gear can be separated effectively and the fault feature were extracted, the feasibility and effectiveness of the method were verified.
胥永刚;孟志鹏;陆 明;付 胜. 基于双树复小波和奇异差分谱的齿轮故障诊断研究[J]. , 2014, 33(1): 11-16.
XU Yong-gang MENG Zhi-peng LU Ming FU Sheng. Gear Fault Diagnosis Based on Dual-tree Complex Wavelet Transform and Singular Value Difference Spectrum. , 2014, 33(1): 11-16.
2014, Vol. 33 
