The FCSIgram-based Identification Method of Optimal Demodulation Frequency Band for Rolling Bearing

doi:10.3901/JME.2025.23.108

Abstract

Abstract: The key of fault diagnosis method of rolling bearing based on resonance demodulation is to select the optimal demodulation frequency band. Aiming at the deficiency of the fixed frequency band division in Fast Kurtogram (FK) method for optimal frequency band demodulation, a novel adaptive resonance demodulation method named Fault characteristic saliency index gram (FCSIgran) is proposed. First, FCSIgran extracts the spectrum trend curve of frequency domain signal of bearing based on Fast iterative filtering (FIF) algorithm. Second, the multilevel spectrum segmentation model can be established by adjusting the filter interval size in FIF algorithm, so as to realize multilevel adaptive spectrum segmentation. Then, the fault characteristic saliency index indicator is constructed based on the Multipoint kurtosis spectrum of vibration signal, and which is used to select the optimal demodulation frequency band of bearing vibration signal. Finally, conducting band-pass filtering on the selected frequency band, and combining with square envelope demodulation analysis, the fault feature extraction and diagnosis of rolling bearing are achieved. The proposed method is applied to analyze the fault simulation and measured signals of rolling bearing with comparing with the similar methods such as Kurtogram, Autogram, and Infogram, the results show that the proposed method can not only accurately locate the optimal demodulation frequency band of the signals from faulty bearing, but also stably achieve fault feature extraction and diagnosis.

Key words: resonance demodulation, optimal demodulation frequency band, fast iterative filtering, rolling bearing, fault diagnosis

CLC Number:

TH165

ZHENG Jinde, DING Wenhai, CHENG Jian, LI Jianghong, SANG Wei. The FCSIgram-based Identification Method of Optimal Demodulation Frequency Band for Rolling Bearing[J]. Journal of Mechanical Engineering, 2025, 61(23): 108-119.

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