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Su W.-S.,Dalian University of Technology | Su W.-S.,Jiangsu Province Special Equipment Safety Supervision Inspection Institute Wuxi Branch | Wang F.-T.,Dalian University of Technology | Zhu H.,Dalian University of Technology | And 3 more authors.
Zhendong yu Chongji/Journal of Vibration and Shock | Year: 2011

Noise is inevitably present in mechanical vibration signal, which makes the extraction of weak fault information become the difficult point and hotspot of fault diagnosis. Since dual tree complex wavelet transform is of the property of approximate translation invariance while hidden Markov tree model can effectively describe the dependency between wavelet coefficients as well as the non-Gaussian nature of these coefficients, a method combining these advantages can achieve better denoising results than conventional soft or hard threshold denoising methods and hidden Markov tree model used alone in wavelet domain. Applications of simulation signals verify that Gaussian white noise can be effectively inhibited, and abnormal impact can be removed by using this method. For actual rolling bearing signal, satisfied results also can be acquired.

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