Improved Holo-Hilbert Spectrum Analysis-Based Fault Diagnosis Method for Rotating Machines

doi:10.3901/JME.2023.01.162

Abstract

Abstract: Although the time-frequency analysis method can extract both the time and frequency domains information of vibration signal for the faulty equipment simultaneously, its use in reflecting the cross-scale coupling relationship between the amplitude-modulation and frequency-modulation characteristics of the nonlinear vibration signal has so far been hindered, and it is prone to be interfered by noises. On this base, the Holo-Hilbert spectral analysis (HHSA) method is innovatively introduced into mechanical fault diagnosis. The internal modulation characteristics of vibration signals can be completely described by the HHSA method with double-layer empirical mode decomposition (EMD) structure, making it an ideal tool for detecting the local faults of mechanical components. At the same time, to improve the diagnosis accuracy of HHSA and suppress the noise interference and the mode aliasing caused by EMD, an improved HHSA (IHHSA) method based on improved regenerated phase shifted sinusoidal assisted EMD (IRPSEMD) is proposed. The usefulness of the IHHSA method for local fault feature diagnosis are validated by the analysis of simulation signals. Finally, the IHHSA method is applied to the detection of gear crack fault and the diagnosis of rolling bearings with local fault. The results show that the internal modulation relationship of nonlinear fault vibration signal can be reflected by the proposed IHHSA method comprehensively, which shows a better fault identification ability.

Key words: Holo-Hilbert spectral analysis, time frequency analysis, nonlinear coupling, fault modulation, fault diagnosis

CLC Number:

TH165

ZHENG Jinde, YING Wanming, PAN Haiyang, TONG Jinyu, LIU Qingyun, JI Jinchen. Improved Holo-Hilbert Spectrum Analysis-Based Fault Diagnosis Method for Rotating Machines[J]. Journal of Mechanical Engineering, 2023, 59(1): 162-174.

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