Vibration Signature Analysis for Broken Rotor Bar Diagnosis in Induction Motors Based on Cyclic Modulation Spectrum

Zuolu Wang; Haiyang Li; Dong Zhen; Fengshou Gu; Andrew Ball

doi:10.1007/978-3-030-75793-9_59

Vibration Signature Analysis for Broken Rotor Bar Diagnosis in Induction Motors Based on Cyclic Modulation Spectrum

Zuolu Wang, Haiyang Li, Dong Zhen, Fengshou Gu, Andrew Ball

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

1 Citation (Scopus)

Abstract

Broken rotor bar (BRB) is a common fault in induction motors (IM), which results in devastating consequences in the stator and reduces system reliability if not detected in a timely manner. An effective monitoring method of BRB is desired to guarantee production efficiency and service life of IM. Currently, most of the detection methods face low recognition accuracy among different BRB fault types, hence the accurate and reliable diagnosis of BRB faults is still a challenging task. Vibration signal contains substantial information reflecting the real working conditions of IM. Therefore, this paper presents an optimized application of cyclic modulation spectrum (CMS) based on vibration analysis to improve the BRB diagnosis, in which the spectral coherence and enhanced envelop spectrum (EES) is used to extract fault features more clearly. The STFT is a critical step in CMS analysis, therefore it is essential to determine the appropriate window function utilized in STFT according to BRB fault signatures in IM. Finally, the experimental analysis under a wide range of working conditions reveals the CMS with selected Kaiser (β = 3) window function can provide more accurate diagnostic information for different BRB severity compared to the popular envelope analysis.

Original language	English
Title of host publication	Proceedings of IncoME-V & CEPE Net-2020
Subtitle of host publication	Condition Monitoring, Plant Maintenance and Reliability
Editors	Dong Zhen, Dong Wang, Tianyang Wang, Hongjun Wang, Baoshan Huang, Jyoti K. Sinha, Andrew David Ball
Place of Publication	Cham
Publisher	Springer Nature Switzerland AG
Pages	616-626
Number of pages	11
Volume	105
Edition	1st
ISBN (Electronic)	9783030757939
ISBN (Print)	9783030757922
DOIs	https://doi.org/10.1007/978-3-030-75793-9_59
Publication status	Published - 16 May 2021
Event	5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network - Zhuhai, China Duration: 23 Oct 2020 → 25 Oct 2020 Conference number: 5 https://link.springer.com/book/10.1007/978-3-030-75793-9#about

Publication series

Name	Mechanisms and Machine Science
Volume	105
ISSN (Print)	2211-0984
ISSN (Electronic)	2211-0992

Conference

Conference	5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network
Abbreviated title	IncoME-V and CEPE Net-2020
Country/Territory	China
City	Zhuhai
Period	23/10/20 → 25/10/20
Internet address	https://link.springer.com/book/10.1007/978-3-030-75793-9#about

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Wang, Z., Li, H., Zhen, D., Gu, F., & Ball, A. (2021). Vibration Signature Analysis for Broken Rotor Bar Diagnosis in Induction Motors Based on Cyclic Modulation Spectrum. In D. Zhen, D. Wang, T. Wang, H. Wang, B. Huang, J. K. Sinha, & A. D. Ball (Eds.), Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability (1st ed., Vol. 105, pp. 616-626). (Mechanisms and Machine Science; Vol. 105). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-75793-9_59

Wang, Zuolu ; Li, Haiyang ; Zhen, Dong et al. / Vibration Signature Analysis for Broken Rotor Bar Diagnosis in Induction Motors Based on Cyclic Modulation Spectrum. Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. editor / Dong Zhen ; Dong Wang ; Tianyang Wang ; Hongjun Wang ; Baoshan Huang ; Jyoti K. Sinha ; Andrew David Ball. Vol. 105 1st. ed. Cham : Springer Nature Switzerland AG, 2021. pp. 616-626 (Mechanisms and Machine Science).

@inproceedings{4ea327914eb1461a8c6c408be72f8332,

title = "Vibration Signature Analysis for Broken Rotor Bar Diagnosis in Induction Motors Based on Cyclic Modulation Spectrum",

abstract = "Broken rotor bar (BRB) is a common fault in induction motors (IM), which results in devastating consequences in the stator and reduces system reliability if not detected in a timely manner. An effective monitoring method of BRB is desired to guarantee production efficiency and service life of IM. Currently, most of the detection methods face low recognition accuracy among different BRB fault types, hence the accurate and reliable diagnosis of BRB faults is still a challenging task. Vibration signal contains substantial information reflecting the real working conditions of IM. Therefore, this paper presents an optimized application of cyclic modulation spectrum (CMS) based on vibration analysis to improve the BRB diagnosis, in which the spectral coherence and enhanced envelop spectrum (EES) is used to extract fault features more clearly. The STFT is a critical step in CMS analysis, therefore it is essential to determine the appropriate window function utilized in STFT according to BRB fault signatures in IM. Finally, the experimental analysis under a wide range of working conditions reveals the CMS with selected Kaiser (β = 3) window function can provide more accurate diagnostic information for different BRB severity compared to the popular envelope analysis.",

keywords = "Broken rotor bar, Cyclic modulation spectrum, Induction motors, Vibration signature",

author = "Zuolu Wang and Haiyang Li and Dong Zhen and Fengshou Gu and Andrew Ball",

note = "Funding Information: Acknowledgement. The research was financially supported by the Hebei Provincial International Science and Technology Cooperation Program of China (17394303D), and the National Natural Science Foundation of China (51605133; 51705127). Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network, IncoME-V and CEPE Net-2020 ; Conference date: 23-10-2020 Through 25-10-2020",

year = "2021",

month = may,

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doi = "10.1007/978-3-030-75793-9_59",

language = "English",

isbn = "9783030757922",

volume = "105",

series = "Mechanisms and Machine Science",

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pages = "616--626",

editor = "Dong Zhen and Dong Wang and Tianyang Wang and Hongjun Wang and Baoshan Huang and Sinha, {Jyoti K.} and Ball, {Andrew David}",

booktitle = "Proceedings of IncoME-V & CEPE Net-2020",

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Wang, Z, Li, H, Zhen, D, Gu, F & Ball, A 2021, Vibration Signature Analysis for Broken Rotor Bar Diagnosis in Induction Motors Based on Cyclic Modulation Spectrum. in D Zhen, D Wang, T Wang, H Wang, B Huang, JK Sinha & AD Ball (eds), Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. 1st edn, vol. 105, Mechanisms and Machine Science, vol. 105, Springer Nature Switzerland AG, Cham, pp. 616-626, 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network, Zhuhai, China, 23/10/20. https://doi.org/10.1007/978-3-030-75793-9_59

Vibration Signature Analysis for Broken Rotor Bar Diagnosis in Induction Motors Based on Cyclic Modulation Spectrum. / Wang, Zuolu; Li, Haiyang; Zhen, Dong et al.

Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. ed. / Dong Zhen; Dong Wang; Tianyang Wang; Hongjun Wang; Baoshan Huang; Jyoti K. Sinha; Andrew David Ball. Vol. 105 1st. ed. Cham : Springer Nature Switzerland AG, 2021. p. 616-626 (Mechanisms and Machine Science; Vol. 105).

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

TY - GEN

T1 - Vibration Signature Analysis for Broken Rotor Bar Diagnosis in Induction Motors Based on Cyclic Modulation Spectrum

AU - Wang, Zuolu

AU - Li, Haiyang

AU - Zhen, Dong

AU - Gu, Fengshou

AU - Ball, Andrew

N1 - Conference code: 5

PY - 2021/5/16

Y1 - 2021/5/16

N2 - Broken rotor bar (BRB) is a common fault in induction motors (IM), which results in devastating consequences in the stator and reduces system reliability if not detected in a timely manner. An effective monitoring method of BRB is desired to guarantee production efficiency and service life of IM. Currently, most of the detection methods face low recognition accuracy among different BRB fault types, hence the accurate and reliable diagnosis of BRB faults is still a challenging task. Vibration signal contains substantial information reflecting the real working conditions of IM. Therefore, this paper presents an optimized application of cyclic modulation spectrum (CMS) based on vibration analysis to improve the BRB diagnosis, in which the spectral coherence and enhanced envelop spectrum (EES) is used to extract fault features more clearly. The STFT is a critical step in CMS analysis, therefore it is essential to determine the appropriate window function utilized in STFT according to BRB fault signatures in IM. Finally, the experimental analysis under a wide range of working conditions reveals the CMS with selected Kaiser (β = 3) window function can provide more accurate diagnostic information for different BRB severity compared to the popular envelope analysis.

AB - Broken rotor bar (BRB) is a common fault in induction motors (IM), which results in devastating consequences in the stator and reduces system reliability if not detected in a timely manner. An effective monitoring method of BRB is desired to guarantee production efficiency and service life of IM. Currently, most of the detection methods face low recognition accuracy among different BRB fault types, hence the accurate and reliable diagnosis of BRB faults is still a challenging task. Vibration signal contains substantial information reflecting the real working conditions of IM. Therefore, this paper presents an optimized application of cyclic modulation spectrum (CMS) based on vibration analysis to improve the BRB diagnosis, in which the spectral coherence and enhanced envelop spectrum (EES) is used to extract fault features more clearly. The STFT is a critical step in CMS analysis, therefore it is essential to determine the appropriate window function utilized in STFT according to BRB fault signatures in IM. Finally, the experimental analysis under a wide range of working conditions reveals the CMS with selected Kaiser (β = 3) window function can provide more accurate diagnostic information for different BRB severity compared to the popular envelope analysis.

KW - Broken rotor bar

KW - Cyclic modulation spectrum

KW - Induction motors

KW - Vibration signature

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AN - SCOPUS:85105989873

SN - 9783030757922

VL - 105

T3 - Mechanisms and Machine Science

SP - 616

EP - 626

BT - Proceedings of IncoME-V & CEPE Net-2020

A2 - Zhen, Dong

A2 - Wang, Dong

A2 - Wang, Tianyang

A2 - Wang, Hongjun

A2 - Huang, Baoshan

A2 - Sinha, Jyoti K.

A2 - Ball, Andrew David

PB - Springer Nature Switzerland AG

CY - Cham

T2 - 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network

Y2 - 23 October 2020 through 25 October 2020

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Wang Z, Li H, Zhen D, Gu F , Ball A. Vibration Signature Analysis for Broken Rotor Bar Diagnosis in Induction Motors Based on Cyclic Modulation Spectrum. In Zhen D, Wang D, Wang T, Wang H, Huang B, Sinha JK, Ball AD, editors, Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. 1st ed. Vol. 105. Cham: Springer Nature Switzerland AG. 2021. p. 616-626. (Mechanisms and Machine Science). Epub 2021 May 16. doi: 10.1007/978-3-030-75793-9_59

Vibration Signature Analysis for Broken Rotor Bar Diagnosis in Induction Motors Based on Cyclic Modulation Spectrum

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