Multifractal super order analysis method for rolling bearing fault diagnosis

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Journal of Vibration and Shock ›› 2020, Vol. 39 ›› Issue (3) : 227-232.

ZHU Yanqi, LI Shunming, PAN Gaoyuan, DU Huarong

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Abstract

Multifractal de-trend fluctuation analysis (MF-DFA) can acquire multifractal spectrum being able to characterize intrinsic dynamic mechanism of a signal, but it has problems of parameters close and state aliasing when extracting fault features in rolling bearing vibration signals to leads to analysis results being easy to be interfered by signal noise and classification results being affected.Here, to solve this problem, the multifractal super order analysis (MF-SOA) method was proposed.Firstly, the extreme value increment method was introduced into MF-DFA, and extreme value operations were done for time series.Then, multifractal features of extreme value increment sequence obtained were calculated and analyzed.Features obtained with MF-SOA method could more clearly reveal internal dynamic mechanism of sequence.Finally, the proposed method was applied in fault diagnosis of rolling bearings.The test data analysis results showed that the proposed method is very sensitive to irregular degree of a signal, and can effectively improve defects of the MF-DFA method; it has a better discrimination degree for fault types with similar modes, and improves the accuracy of rolling bearing fault diagnosis.

Key words

multifractal / DFA / extreme value increment / rolling bearing / fault diagnosis

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ZHU Yanqi, LI Shunming, PAN Gaoyuan, DU Huarong. Multifractal super order analysis method for rolling bearing fault diagnosis[J]. Journal of Vibration and Shock, 2020, 39(3): 227-232

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