Bearing Multifault Impulse Detection Using Spike Period Volatility Factor Spectrogram
IEEE Transactions on Industrial Informatics(2024)
Abstract
Aiming at multiresonance phenomena excited by bearing compound fault and the masking effect of strong shocks on weak fault shocks, a novel multifault diagnosis method is proposed based on comprehensively characterizing the impulsivity and periodicity of multifault shocks in the shared resonance frequency band. First, the adaptive redundant lifting wavelet packet is presented to decompose the vibration signal into various narrow bands. Then, spike period volatility factor (SPVF) is designed to quantify the multiperiodic impulsive characteristics of narrowband signals. Consequently, the SPVF spectrogram is constructed to highlight the shared resonance bands of multifaults. Finally, the SPVF-cyclic frequency spectrum is developed to synchronously detect the multifault characteristics frequencies. Simulation and experimental analysis showed that the proposed method can simultaneously diagnose multiple bearing faults with good sensitivity to fault-related impulses and robustness to random interferences.
MoreTranslated text
Key words
Adaptive redundant lifting wavelet packet,bearing compound fault diagnosis,optimal band filtering,spike period volatility factor
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined