Rolling Element Bearings Fault Diagnosis Method Based on NAMEMD and multi-scale morphology

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Journal of Vibration and Shock ›› 2016, Vol. 35 ›› Issue (4) : 127-133.

Wu Zhe1，Yang Shao-pu2，Ren Bin2，MA Xinna2，Zhang Jian-chao1,2

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Abstract

This paper proposes a rolling bearing fault diagnosis method based on multivariate empirical mode decomposition-based noise assisted multivariate empirical mode decomposition (NAMEMD) and mathematical morphology. NAMEMD, as a noise assisted data analysis-based method, could effectively avoid such shortcomings of ensemble empirical mode decomposition as mode mixing and heavy computation, thus being superior to traditional noise assisted data analysis-based method to a certain extent. This paper uses NAMEMD with multiscale morphology for rolling bearing fault diagnosis. As for the method proposed, NAMEMD is used to adaptively decompose multi-component FM and AM fault signal into a series of IMF components, of which the high-energy ones are subjected to summation & reconstruction; then, a multiscale morphological difference filter is employed to extract the fault characteristic frequency of signal. In order to verify the correctness of theory, simulation experiment and bearing fault experiment were performed to compare with EEMD and envelope demodulation-based methods; according to the result, the present technique could further alleviate mode mixing effect, significantly improve the computation speed, bring about higher detection accuracy for the faults in outer race, inner race and roller in rolling bearing, and clearly extract the frequency characteristics of fault signal.

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NAMEMD；Mode Mixing；multiscale morphology / Rolling Bearing / Fault diagnosis

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Wu Zhe1，Yang Shao-pu2，Ren Bin2，MA Xinna2，Zhang Jian-chao1,2. Rolling Element Bearings Fault Diagnosis Method Based on NAMEMD and multi-scale morphology[J]. Journal of Vibration and Shock, 2016, 35(4): 127-133

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