A Squeezed Modulation Signal Bispectrum Method for Motor Current Signals Based Gear Fault Diagnosis

Abstract

Electromechanical systems as the prime power source are widely employed in industry. To ensure the high productivity and safety of the motor-gear system, motor current signature analysis (MCSA) becomes a cost-effective and effective approach to health condition monitoring of motors and gears simultaneously. In general, working conditions of the motor-gear system can be separated into stationary and nonstationary working conditions. The nonstationary working conditions usually refer to varying speeds, which have been broadly investigated in the angular domain analysis and time-frequency analysis. The stationary working conditions are assumed to have a constant rotating speed which is an ideal scenario, but practically, the rotating speed varies slightly with randomness. The random speed variation seems neglectable but it actually spreads the energy into adjacent frequency bins, which attenuates the amplitude of fault signatures and leads to inaccurate fault diagnosis. To address this issue, a squeezed modulation signal bispectrum (MSB) approach is developed to concentrate the leaked energy for accurately diagnosing gear faults with motor current signals. The squeezed MSB concentrates the energy in the frequency domain along the time axis to overcome the random speed oscillation induced energy leakage and then demodulates and aligns the modulation fault signatures from the squeezed spectra for ensemble averaging to further enhance fault signatures. The simulation study shows the performance of the proposed method under different levels of random speed variation, and the experimental studies demonstrate the effectiveness of the squeezed MSB for diagnosing gear tooth breakage faults under a wide range of working conditions.

Publication DOI: https://doi.org/10.1109/TIM.2022.3201549
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
Additional Information: © 2022, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: Employee welfare,Frequency modulation,Gears,Induction motors,Modulation,Oscillators,Random speed variation,Squeezed MSB,Torque,fault diagnosis,gears,motor current signature analysis,Instrumentation,Electrical and Electronic Engineering
Publication ISSN: 1557-9662
Last Modified: 28 Feb 2024 08:20
Date Deposited: 02 Sep 2022 16:30
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2022-09-09
Published Online Date: 2022-08-25
Accepted Date: 2022-08-17
Authors: Xu, Yuandong
Tang, Xiaoli (ORCID Profile 0000-0003-4428-0895)
Sun, Xiuquan
Gu, Fengshou
Ball, Andrew D.

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