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

Baoshan Huang; Guojin Feng; Xiaoli Tang; James Xi Gu; Guanghua Xu; Robert Cattley; Fengshou Gu; Andrew D. Ball

doi:10.3390/en12081438

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

Baoshan Huang
, Guojin Feng^*
, Xiaoli Tang
, James Xi Gu
, Guanghua Xu
, Robert Cattley
, Fengshou Gu
, Andrew D. Ball

^*Corresponding author for this work

Mechanical, Biomedical & Design Engineering

Beijing Institute of Technology
Brunel University
University of Bolton
Xi'an Jiaotong University
University of Huddersfield

Research output: Contribution to journal › Article › peer-review

33 Citations (SciVal)

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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.

Original language	English
Article number	1438
Journal	Energies
Volume	12
Issue number	8
DOIs	https://doi.org/10.3390/en12081438
Publication status	Published - 15 Apr 2019

Bibliographical note

© 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.

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. 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.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Fault diagnosis
Gearbox
Higher order spectra
Induction motor
Modulation signal bispectrum
Reciprocating compressor

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10.3390/en12081438

A Performance Evaluation of Two Bispectrum Analysis Methods
© 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/).
Final published version, 5.79 MBLicence: CC BY 3.0

Cite this

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title = "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.",

keywords = "Fault diagnosis, Gearbox, Higher order spectra, Induction motor, Modulation signal bispectrum, Reciprocating compressor",

author = "Baoshan Huang and Guojin Feng and Xiaoli Tang and Gu, \{James Xi\} and Guanghua Xu and Robert Cattley and Fengshou Gu and Ball, \{Andrew D.\}",

note = "{\textcopyright} 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. ",

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AU - Huang, Baoshan

AU - Feng, Guojin

AU - Tang, Xiaoli

AU - Gu, James Xi

AU - Xu, Guanghua

AU - Cattley, Robert

AU - Gu, Fengshou

AU - Ball, Andrew D.

N1 - © 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.

PY - 2019/4/15

Y1 - 2019/4/15

N2 - 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.

AB - 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.

KW - Fault diagnosis

KW - Gearbox

KW - Higher order spectra

KW - Induction motor

KW - Modulation signal bispectrum

KW - Reciprocating compressor

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

Abstract

Bibliographical note

Funding

UN SDGs

Keywords

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