Modulation Signal Bispectrum Analysis of Motor Current Signals for Condition Monitoring of Electromechanical Systems

Funso Otuyemi; Haiyang Li; Fulong Liu; Jiongqi Wang; Fengshou Gu; Andrew D. Ball

doi:10.1007/978-981-13-8331-1_42

Modulation Signal Bispectrum Analysis of Motor Current Signals for Condition Monitoring of Electromechanical Systems

Funso Otuyemi, Haiyang Li, Fulong Liu, Jiongqi Wang, Fengshou Gu, Andrew D. Ball

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

Induction motor is one of the most widely used prime drivers and electric energy consuming devices in industry. Accurate and timely diagnosis of faults in motors will help to maintain their operating under optimal status and avoid excessive energy consumption and severe damages to systems. In this study, instantaneous motor current and voltage signals (IMCVS) is analyzed by an advanced Modulation Signal Bispectrum (MSB) method to achieve accurate demodulations of Frequency Modulation (FM) and Amplitude Modulation (AM) by minimizing noise influence and enhancing modulation characteristics simultaneously. Firstly, the modulation effects due to motor faults and downstream mechanical components were modelled, thus finding the interaction between AM and FM effect and hence developed a scheme to use the signature of AM and FM jointly for accurate fault diagnosis. Then experimentations were carried out to verify the performance of the proposed scheme in detecting and diagnosing common mechanical faults including Shaft Misalignments(SM), Motor Rotor Broken Bar (BRB), Stator Resistance Imbalance (SRI) and compound BRB with SRI.

Original language	English
Title of host publication	Proceedings of the 13th International Conference on Damage Assessment of Structures
Editors	Magd Abdel Wahab
Publisher	Springer
Pages	566-581
Number of pages	16
ISBN (Electronic)	9789811383311
ISBN (Print)	9789811383304
DOIs	https://doi.org/10.1007/978-981-13-8331-1_42
Publication status	Published - 2019
Event	13th International Conference on Damage Assessment of Structures - University of Porto, Porto, Portugal Duration: 9 Jul 2019 → 10 Jul 2019 Conference number: 13 http://www.damas.ugent.be/

Publication series

Name	Lecture Notes in Mechanical Engineering
ISSN (Print)	2195-4356
ISSN (Electronic)	2195-4364

Conference

Conference	13th International Conference on Damage Assessment of Structures
Abbreviated title	DAMAS 2019
Country/Territory	Portugal
City	Porto
Period	9/07/19 → 10/07/19
Internet address	http://www.damas.ugent.be/

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

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Cite this

Otuyemi, F., Li, H., Liu, F., Wang, J., Gu, F., & Ball, A. D. (2019). Modulation Signal Bispectrum Analysis of Motor Current Signals for Condition Monitoring of Electromechanical Systems. In M. A. Wahab (Ed.), Proceedings of the 13th International Conference on Damage Assessment of Structures (pp. 566-581). (Lecture Notes in Mechanical Engineering). Springer. https://doi.org/10.1007/978-981-13-8331-1_42

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title = "Modulation Signal Bispectrum Analysis of Motor Current Signals for Condition Monitoring of Electromechanical Systems",

abstract = "Induction motor is one of the most widely used prime drivers and electric energy consuming devices in industry. Accurate and timely diagnosis of faults in motors will help to maintain their operating under optimal status and avoid excessive energy consumption and severe damages to systems. In this study, instantaneous motor current and voltage signals (IMCVS) is analyzed by an advanced Modulation Signal Bispectrum (MSB) method to achieve accurate demodulations of Frequency Modulation (FM) and Amplitude Modulation (AM) by minimizing noise influence and enhancing modulation characteristics simultaneously. Firstly, the modulation effects due to motor faults and downstream mechanical components were modelled, thus finding the interaction between AM and FM effect and hence developed a scheme to use the signature of AM and FM jointly for accurate fault diagnosis. Then experimentations were carried out to verify the performance of the proposed scheme in detecting and diagnosing common mechanical faults including Shaft Misalignments(SM), Motor Rotor Broken Bar (BRB), Stator Resistance Imbalance (SRI) and compound BRB with SRI.",

keywords = "Electrical motor, Fault diagnosis, Modulation signal bi-spectrum",

author = "Funso Otuyemi and Haiyang Li and Fulong Liu and Jiongqi Wang and Fengshou Gu and Ball, {Andrew D.}",

year = "2019",

doi = "10.1007/978-981-13-8331-1_42",

language = "English",

isbn = "9789811383304",

series = "Lecture Notes in Mechanical Engineering",

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pages = "566--581",

editor = "Wahab, {Magd Abdel}",

booktitle = "Proceedings of the 13th International Conference on Damage Assessment of Structures",

address = "Germany",

note = "13th International Conference on Damage Assessment of Structures, DAMAS 2019 ; Conference date: 09-07-2019 Through 10-07-2019",

url = "http://www.damas.ugent.be/",

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Otuyemi, F, Li, H, Liu, F, Wang, J, Gu, F & Ball, AD 2019, Modulation Signal Bispectrum Analysis of Motor Current Signals for Condition Monitoring of Electromechanical Systems. in MA Wahab (ed.), Proceedings of the 13th International Conference on Damage Assessment of Structures. Lecture Notes in Mechanical Engineering, Springer, pp. 566-581, 13th International Conference on Damage Assessment of Structures, Porto, Portugal, 9/07/19. https://doi.org/10.1007/978-981-13-8331-1_42

Modulation Signal Bispectrum Analysis of Motor Current Signals for Condition Monitoring of Electromechanical Systems. / Otuyemi, Funso; Li, Haiyang; Liu, Fulong et al.

Proceedings of the 13th International Conference on Damage Assessment of Structures. ed. / Magd Abdel Wahab. Springer, 2019. p. 566-581 (Lecture Notes in Mechanical Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Modulation Signal Bispectrum Analysis of Motor Current Signals for Condition Monitoring of Electromechanical Systems

AU - Otuyemi, Funso

AU - Li, Haiyang

AU - Liu, Fulong

AU - Wang, Jiongqi

AU - Gu, Fengshou

AU - Ball, Andrew D.

N1 - Conference code: 13

PY - 2019

Y1 - 2019

N2 - Induction motor is one of the most widely used prime drivers and electric energy consuming devices in industry. Accurate and timely diagnosis of faults in motors will help to maintain their operating under optimal status and avoid excessive energy consumption and severe damages to systems. In this study, instantaneous motor current and voltage signals (IMCVS) is analyzed by an advanced Modulation Signal Bispectrum (MSB) method to achieve accurate demodulations of Frequency Modulation (FM) and Amplitude Modulation (AM) by minimizing noise influence and enhancing modulation characteristics simultaneously. Firstly, the modulation effects due to motor faults and downstream mechanical components were modelled, thus finding the interaction between AM and FM effect and hence developed a scheme to use the signature of AM and FM jointly for accurate fault diagnosis. Then experimentations were carried out to verify the performance of the proposed scheme in detecting and diagnosing common mechanical faults including Shaft Misalignments(SM), Motor Rotor Broken Bar (BRB), Stator Resistance Imbalance (SRI) and compound BRB with SRI.

AB - Induction motor is one of the most widely used prime drivers and electric energy consuming devices in industry. Accurate and timely diagnosis of faults in motors will help to maintain their operating under optimal status and avoid excessive energy consumption and severe damages to systems. In this study, instantaneous motor current and voltage signals (IMCVS) is analyzed by an advanced Modulation Signal Bispectrum (MSB) method to achieve accurate demodulations of Frequency Modulation (FM) and Amplitude Modulation (AM) by minimizing noise influence and enhancing modulation characteristics simultaneously. Firstly, the modulation effects due to motor faults and downstream mechanical components were modelled, thus finding the interaction between AM and FM effect and hence developed a scheme to use the signature of AM and FM jointly for accurate fault diagnosis. Then experimentations were carried out to verify the performance of the proposed scheme in detecting and diagnosing common mechanical faults including Shaft Misalignments(SM), Motor Rotor Broken Bar (BRB), Stator Resistance Imbalance (SRI) and compound BRB with SRI.

KW - Electrical motor

KW - Fault diagnosis

KW - Modulation signal bi-spectrum

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U2 - 10.1007/978-981-13-8331-1_42

DO - 10.1007/978-981-13-8331-1_42

M3 - Conference contribution

AN - SCOPUS:85069188061

SN - 9789811383304

T3 - Lecture Notes in Mechanical Engineering

SP - 566

EP - 581

BT - Proceedings of the 13th International Conference on Damage Assessment of Structures

A2 - Wahab, Magd Abdel

PB - Springer

T2 - 13th International Conference on Damage Assessment of Structures

Y2 - 9 July 2019 through 10 July 2019

ER -

Otuyemi F, Li H, Liu F, Wang J, Gu F , Ball AD. Modulation Signal Bispectrum Analysis of Motor Current Signals for Condition Monitoring of Electromechanical Systems. In Wahab MA, editor, Proceedings of the 13th International Conference on Damage Assessment of Structures. Springer. 2019. p. 566-581. (Lecture Notes in Mechanical Engineering). Epub 2019 Jul 5. doi: 10.1007/978-981-13-8331-1_42

Modulation Signal Bispectrum Analysis of Motor Current Signals for Condition Monitoring of Electromechanical Systems

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