Motor Current Signature Analysis Using Robust Modulation Spectrum Correlation Gram for Gearbox Fault Detection

Junchao Guo, Qingbo He, Dong Zhen, Fengshou Gu

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Spectrum correlation (SC), as a typical demodulation algorithm, has been investigated for fault extraction by restraining interference components. However, SC ignores the uneven distribution of fault features in the entire frequency range, which makes the results vulnerable to interference components. To overcome these shortcomings, a novel robust modulation spectrum correlation (RMSC) gram is proposed. First, the signal is demodulated into a bispectral map display containing fundamental and modulation frequency through RMSC, and a finite impulse response filter on fundamental frequency is utilized to obtain RMSC subbands. Subsequently, the fault feature index of subbands under healthy and fault conditions is calculated, and its failure signature ratio (FSR) to generate RMSC gram is utilized. Finally, the RMSC with the maximum FSR is selected as an optimal subband, and envelope analysis is executed on the subband to obtain fault features. Simulations and experiments are performed to validate the effectiveness of RMSC in comparison with the state-of-the-art methods.

Original languageEnglish
Article number10195918
Pages (from-to)2671-2681
Number of pages11
JournalIEEE Transactions on Industrial Informatics
Volume20
Issue number2
Early online date27 Jul 2023
DOIs
Publication statusPublished - 1 Feb 2024

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