A performance evaluation of two bispectrum analysis methods applied to electrical current signals for monitoring induction motor-driven systems

Abstract

This paper investigates the performance of the conventional bispectrum (CB) method and its new variant, the modulation signal bispectrum (MSB) method, in analysing the electrical current signals of induction machines for the condition monitoring of rotor systems driven by electrical motors. Current signal models which include the phases of the various electrical and magnetic quantities are explained first to show the theoretical relationships of spectral sidebands and their associated phases due to rotor faults. It then discusses the inefficiency of CB and the proficiency of MSB in characterising the sidebands based on simulated signals. Finally, these two methods are applied to analyse current signals measured from different rotor faults, including broken rotor bar (BRB), downstream gearbox wear progressions and various compressor faults, and the diagnostic results show that the MSB outperforms the CB method significantly in that it provides more accurate and sparse diagnostics, thanks to its unique capability of nonlinear modulation detection and random noise suppression.

Publication DOI: https://doi.org/10.3390/en12081438
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
Funding Information: The research was funded by the National Natural Science Foundation of Guangdong, China, grant number 2017A030313291, and the Tribology Science Fund of State Laboratory of Tribology, grant number SKLTKF18A05. Funding: The research was funded by the Nationa
Additional Information: © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Funding Information: Funding: The research was funded by the National Natural Science Foundation of Guangdong, China, grant number 2017A030313291, and the Tribology Science Fund of State Laboratory of Tribology, grant number SKLTKF18A05.
Uncontrolled Keywords: Fault diagnosis,Gearbox,Higher order spectra,Induction motor,Modulation signal bispectrum,Reciprocating compressor,Renewable Energy, Sustainability and the Environment,Energy Engineering and Power Technology,Energy (miscellaneous),Control and Optimization,Electrical and Electronic Engineering
Publication ISSN: 1996-1073
Last Modified: 29 Jan 2024 18:30
Date Deposited: 06 Sep 2021 11:36
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.mdp ... -1073/12/8/1438 (Publisher URL)
PURE Output Type: Article
Published Date: 2019-04-15
Accepted Date: 2019-04-09
Authors: Huang, Baoshan
Feng, Guojin
Tang, Xiaoli (ORCID Profile 0000-0003-4428-0895)
Gu, James Xi
Xu, Guanghua
Cattley, Robert
Gu, Fengshou
Ball, Andrew D.

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