An Optimized Modulation Signal Bispectrum for Bearing Fault Diagnosis

Yuandong Xu; Yunpeng Cao; Fengshou Gu; Andrew Ball

doi:10.1007/978-3-031-26193-0_90

An Optimized Modulation Signal Bispectrum for Bearing Fault Diagnosis

Yuandong Xu, Yunpeng Cao, Fengshou Gu, Andrew Ball

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

Abstract

Rolling element bearings are widely used in rotating machines and play an important role in supporting the rotor and minimizing friction during the operation. The health conditions of bearings have a significant influence on the reliability and safety of rotating machines and hence condition monitoring of bearings is of great significance. The modulation signal bispectrum (MSB) is an outstanding approach for early fault detection and diagnosis of bearings. To further improve the performance of the MSB method, an optimized method is proposed to enhance the noise reduction capability for a more accurate fault diagnosis. The MSB matrixes are automatically selected to remove the improper estimation for the following ensemble averaging according to the amplitude and phase of the coupled components. Both simulation and experimental studies demonstrate the effectiveness of the proposed optimized MSB method for bearing.

Original language	English
Title of host publication	Proceedings of TEPEN 2022
Subtitle of host publication	Efficiency and Performance Engineering Network
Editors	Hao Zhang, Yongjian Ji, Tongtong Liu, Xiuquan Sun, Andrew David Ball
Publisher	Springer, Cham
Pages	1028-1037
Number of pages	10
Volume	129
ISBN (Electronic)	9783031261930
ISBN (Print)	9783031261923, 9783031261954
DOIs	https://doi.org/10.1007/978-3-031-26193-0_90
Publication status	Published - 4 Mar 2023
Event	International Conference of The Efficiency and Performance Engineering Network 2022 - Baotou, China Duration: 18 Aug 2022 → 21 Aug 2022 https://tepen.net/ https://tepen.net/conference/tepen2022/

Publication series

Name	Mechanisms and Machine Science
Publisher	Springer
Volume	129 MMS
ISSN (Print)	2211-0984
ISSN (Electronic)	2211-0992

Conference

Conference	International Conference of The Efficiency and Performance Engineering Network 2022
Abbreviated title	TEPEN 2022
Country/Territory	China
City	Baotou
Period	18/08/22 → 21/08/22
Internet address	https://tepen.net/ https://tepen.net/conference/tepen2022/

UN SDGs

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

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Xu, Y., Cao, Y., Gu, F., & Ball, A. (2023). An Optimized Modulation Signal Bispectrum for Bearing Fault Diagnosis. In H. Zhang, Y. Ji, T. Liu, X. Sun, & A. D. Ball (Eds.), Proceedings of TEPEN 2022 : Efficiency and Performance Engineering Network (Vol. 129, pp. 1028-1037). (Mechanisms and Machine Science; Vol. 129 MMS). Springer, Cham. https://doi.org/10.1007/978-3-031-26193-0_90

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title = "An Optimized Modulation Signal Bispectrum for Bearing Fault Diagnosis",

abstract = "Rolling element bearings are widely used in rotating machines and play an important role in supporting the rotor and minimizing friction during the operation. The health conditions of bearings have a significant influence on the reliability and safety of rotating machines and hence condition monitoring of bearings is of great significance. The modulation signal bispectrum (MSB) is an outstanding approach for early fault detection and diagnosis of bearings. To further improve the performance of the MSB method, an optimized method is proposed to enhance the noise reduction capability for a more accurate fault diagnosis. The MSB matrixes are automatically selected to remove the improper estimation for the following ensemble averaging according to the amplitude and phase of the coupled components. Both simulation and experimental studies demonstrate the effectiveness of the proposed optimized MSB method for bearing.",

keywords = "Demodulation analysis, Fault diagnosis, MSB, Rolling element bearing",

author = "Yuandong Xu and Yunpeng Cao and Fengshou Gu and Andrew Ball",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference of The Efficiency and Performance Engineering Network 2022, TEPEN 2022 ; Conference date: 18-08-2022 Through 21-08-2022",

year = "2023",

month = mar,

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doi = "10.1007/978-3-031-26193-0_90",

language = "English",

isbn = "9783031261923",

volume = "129",

series = "Mechanisms and Machine Science",

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editor = "Hao Zhang and Yongjian Ji and Tongtong Liu and Xiuquan Sun and Ball, {Andrew David}",

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}

Xu, Y, Cao, Y, Gu, F & Ball, A 2023, An Optimized Modulation Signal Bispectrum for Bearing Fault Diagnosis. in H Zhang, Y Ji, T Liu, X Sun & AD Ball (eds), Proceedings of TEPEN 2022 : Efficiency and Performance Engineering Network. vol. 129, Mechanisms and Machine Science, vol. 129 MMS, Springer, Cham, pp. 1028-1037, International Conference of The Efficiency and Performance Engineering Network 2022, Baotou, China, 18/08/22. https://doi.org/10.1007/978-3-031-26193-0_90

An Optimized Modulation Signal Bispectrum for Bearing Fault Diagnosis. / Xu, Yuandong; Cao, Yunpeng; Gu, Fengshou et al.

Proceedings of TEPEN 2022 : Efficiency and Performance Engineering Network. ed. / Hao Zhang; Yongjian Ji; Tongtong Liu; Xiuquan Sun; Andrew David Ball. Vol. 129 Springer, Cham, 2023. p. 1028-1037 (Mechanisms and Machine Science; Vol. 129 MMS).

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

TY - GEN

T1 - An Optimized Modulation Signal Bispectrum for Bearing Fault Diagnosis

AU - Xu, Yuandong

AU - Cao, Yunpeng

AU - Gu, Fengshou

AU - Ball, Andrew

PY - 2023/3/4

Y1 - 2023/3/4

N2 - Rolling element bearings are widely used in rotating machines and play an important role in supporting the rotor and minimizing friction during the operation. The health conditions of bearings have a significant influence on the reliability and safety of rotating machines and hence condition monitoring of bearings is of great significance. The modulation signal bispectrum (MSB) is an outstanding approach for early fault detection and diagnosis of bearings. To further improve the performance of the MSB method, an optimized method is proposed to enhance the noise reduction capability for a more accurate fault diagnosis. The MSB matrixes are automatically selected to remove the improper estimation for the following ensemble averaging according to the amplitude and phase of the coupled components. Both simulation and experimental studies demonstrate the effectiveness of the proposed optimized MSB method for bearing.

AB - Rolling element bearings are widely used in rotating machines and play an important role in supporting the rotor and minimizing friction during the operation. The health conditions of bearings have a significant influence on the reliability and safety of rotating machines and hence condition monitoring of bearings is of great significance. The modulation signal bispectrum (MSB) is an outstanding approach for early fault detection and diagnosis of bearings. To further improve the performance of the MSB method, an optimized method is proposed to enhance the noise reduction capability for a more accurate fault diagnosis. The MSB matrixes are automatically selected to remove the improper estimation for the following ensemble averaging according to the amplitude and phase of the coupled components. Both simulation and experimental studies demonstrate the effectiveness of the proposed optimized MSB method for bearing.

KW - Demodulation analysis

KW - Fault diagnosis

KW - MSB

KW - Rolling element bearing

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M3 - Conference contribution

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SN - 9783031261954

VL - 129

T3 - Mechanisms and Machine Science

SP - 1028

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BT - Proceedings of TEPEN 2022

A2 - Zhang, Hao

A2 - Ji, Yongjian

A2 - Liu, Tongtong

A2 - Sun, Xiuquan

A2 - Ball, Andrew David

PB - Springer, Cham

T2 - International Conference of The Efficiency and Performance Engineering Network 2022

Y2 - 18 August 2022 through 21 August 2022

ER -

An Optimized Modulation Signal Bispectrum for Bearing Fault Diagnosis

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