Fault diagnosis of axle box bearing of high-speed train based on adaptive VMD

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Journal of Vibration and Shock ›› 2021, Vol. 40 ›› Issue (3) : 240-245.

HUANG Yan, LIN Jianhui, LIU Zechao, HUANG Chenguang

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Abstract

Based on the recognition ability of scale space for resonance frequency band in signal spectrum, combined with the adaptive decomposition ability of variational mode decomposition (VMD), a scale space guided VMD algorithm was proposed to predict penalty factor. The core of the algorithm included dividing resonance frequency bands of signal frequency band in scale space to determine the number of intrinsic modes in VMD, estimate the initial center frequency and corresponding penalty factor of each intrinsic function of VMD according to the boundary of resonance frequency band, and improve the adaptability and accuracy of VMD. The simulation results showed that the proposed method can recognize resonance frequency bands of a faulty signal under low SNR condition and guide VMD to correctly decompose the signal; the test data of axle box bearing of high-speed train are used to verify the proposed method being able to effectively decompose different fault shocks in signal; compared to the VMD algorithm with different penalty factors, the proposed method can more accurately extract different fault shocks, and significantly improve the adaptability and accuracy of VMD.

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axle box bearing / fault diagnosis / scale space / variational mode decomposition (VMD)

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HUANG Yan, LIN Jianhui, LIU Zechao, HUANG Chenguang. Fault diagnosis of axle box bearing of high-speed train based on adaptive VMD[J]. Journal of Vibration and Shock, 2021, 40(3): 240-245

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