Fault Detection and Diagnosis of Gearbox Oil Shortage Using Motor Current Signature

Funso Otuyemi; Xiuquan Sun; Jingyan Zhao; Zhexiang Zou; Jianguo Wang; Fengshou Gu; Andrew D. Ball

doi:10.1007/978-3-031-26193-0_82

Fault Detection and Diagnosis of Gearbox Oil Shortage Using Motor Current Signature

Funso Otuyemi, Xiuquan Sun, Jingyan Zhao, Zhexiang Zou, Jianguo Wang, Fengshou Gu, Andrew D. Ball

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

2 Citations (Scopus)

Abstract

Gearboxes are the most significant components of a motor driven system. However, they are often exposed to various abnormal working condition which causes damage to the gear. One of typical forms is oil shortage which worsen the lubrication state of gears furthermore causing the gears to get worn. Recently, several various attempts have been performed for the detection of oil shortage in gearbox using electric signatures. However, the results are not that promising. This study considered different oil level such as Baseline (BL) 2600 ml, Oil Sample (OS) 2000 ml and OS1500 ml to demonstrate the performance of motor current analysis-based oil shortage detection. It has shown by an experimental evaluation that MSB analysis yields a much better diagnostics of detecting oil shortage in gearboxes at a normal working condition. This is mainly because MSB is good at extracting small sidebands induced by oil shortage or poor lubrication in gearboxes which yields a more precise and reliable results.

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	936-947
Number of pages	12
Volume	129
ISBN (Electronic)	9783031261930
ISBN (Print)	9783031261923, 9783031261954
DOIs	https://doi.org/10.1007/978-3-031-26193-0_82
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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10.1007/978-3-031-26193-0_82Licence: Unspecified

Cite this

Otuyemi, F., Sun, X., Zhao, J., Zou, Z., Wang, J., Gu, F., & Ball, A. D. (2023). Fault Detection and Diagnosis of Gearbox Oil Shortage Using Motor Current Signature. 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. 936-947). (Mechanisms and Machine Science; Vol. 129 MMS). Springer, Cham. https://doi.org/10.1007/978-3-031-26193-0_82

Otuyemi, Funso ; Sun, Xiuquan ; Zhao, Jingyan et al. / Fault Detection and Diagnosis of Gearbox Oil Shortage Using Motor Current Signature. Proceedings of TEPEN 2022 : Efficiency and Performance Engineering Network. editor / Hao Zhang ; Yongjian Ji ; Tongtong Liu ; Xiuquan Sun ; Andrew David Ball. Vol. 129 Springer, Cham, 2023. pp. 936-947 (Mechanisms and Machine Science).

@inproceedings{8a65561e46924e54bb6342bf9e0dcb14,

title = "Fault Detection and Diagnosis of Gearbox Oil Shortage Using Motor Current Signature",

abstract = "Gearboxes are the most significant components of a motor driven system. However, they are often exposed to various abnormal working condition which causes damage to the gear. One of typical forms is oil shortage which worsen the lubrication state of gears furthermore causing the gears to get worn. Recently, several various attempts have been performed for the detection of oil shortage in gearbox using electric signatures. However, the results are not that promising. This study considered different oil level such as Baseline (BL) 2600 ml, Oil Sample (OS) 2000 ml and OS1500 ml to demonstrate the performance of motor current analysis-based oil shortage detection. It has shown by an experimental evaluation that MSB analysis yields a much better diagnostics of detecting oil shortage in gearboxes at a normal working condition. This is mainly because MSB is good at extracting small sidebands induced by oil shortage or poor lubrication in gearboxes which yields a more precise and reliable results.",

keywords = "Condition monitoring, Fault diagnosis, Motor current signal analysis, Oil shortage",

author = "Funso Otuyemi and Xiuquan Sun and Jingyan Zhao and Zhexiang Zou and Jianguo Wang and Fengshou Gu and Ball, {Andrew D.}",

note = "Funding Information: Acknowledgment. This work was supported by the National Natural Science of China (51865045). 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_82",

language = "English",

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volume = "129",

series = "Mechanisms and Machine Science",

publisher = "Springer, Cham",

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Otuyemi, F, Sun, X, Zhao, J, Zou, Z, Wang, J, Gu, F & Ball, AD 2023, Fault Detection and Diagnosis of Gearbox Oil Shortage Using Motor Current Signature. 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. 936-947, 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_82

Fault Detection and Diagnosis of Gearbox Oil Shortage Using Motor Current Signature. / Otuyemi, Funso; Sun, Xiuquan; Zhao, Jingyan 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. 936-947 (Mechanisms and Machine Science; Vol. 129 MMS).

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

TY - GEN

T1 - Fault Detection and Diagnosis of Gearbox Oil Shortage Using Motor Current Signature

AU - Otuyemi, Funso

AU - Sun, Xiuquan

AU - Zhao, Jingyan

AU - Zou, Zhexiang

AU - Wang, Jianguo

AU - Gu, Fengshou

AU - Ball, Andrew D.

N1 - Funding Information: Acknowledgment. This work was supported by the National Natural Science of China (51865045). Publisher Copyright: © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

PY - 2023/3/4

Y1 - 2023/3/4

N2 - Gearboxes are the most significant components of a motor driven system. However, they are often exposed to various abnormal working condition which causes damage to the gear. One of typical forms is oil shortage which worsen the lubrication state of gears furthermore causing the gears to get worn. Recently, several various attempts have been performed for the detection of oil shortage in gearbox using electric signatures. However, the results are not that promising. This study considered different oil level such as Baseline (BL) 2600 ml, Oil Sample (OS) 2000 ml and OS1500 ml to demonstrate the performance of motor current analysis-based oil shortage detection. It has shown by an experimental evaluation that MSB analysis yields a much better diagnostics of detecting oil shortage in gearboxes at a normal working condition. This is mainly because MSB is good at extracting small sidebands induced by oil shortage or poor lubrication in gearboxes which yields a more precise and reliable results.

AB - Gearboxes are the most significant components of a motor driven system. However, they are often exposed to various abnormal working condition which causes damage to the gear. One of typical forms is oil shortage which worsen the lubrication state of gears furthermore causing the gears to get worn. Recently, several various attempts have been performed for the detection of oil shortage in gearbox using electric signatures. However, the results are not that promising. This study considered different oil level such as Baseline (BL) 2600 ml, Oil Sample (OS) 2000 ml and OS1500 ml to demonstrate the performance of motor current analysis-based oil shortage detection. It has shown by an experimental evaluation that MSB analysis yields a much better diagnostics of detecting oil shortage in gearboxes at a normal working condition. This is mainly because MSB is good at extracting small sidebands induced by oil shortage or poor lubrication in gearboxes which yields a more precise and reliable results.

KW - Condition monitoring

KW - Fault diagnosis

KW - Motor current signal analysis

KW - Oil shortage

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UR - https://link.springer.com/book/10.1007/978-3-031-26193-0

U2 - 10.1007/978-3-031-26193-0_82

DO - 10.1007/978-3-031-26193-0_82

M3 - Conference contribution

AN - SCOPUS:85151128390

SN - 9783031261923

SN - 9783031261954

VL - 129

T3 - Mechanisms and Machine Science

SP - 936

EP - 947

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 -

Otuyemi F, Sun X, Zhao J, Zou Z, Wang J, Gu F et al. Fault Detection and Diagnosis of Gearbox Oil Shortage Using Motor Current Signature. In Zhang H, Ji Y, Liu T, Sun X, Ball AD, editors, Proceedings of TEPEN 2022 : Efficiency and Performance Engineering Network. Vol. 129. Springer, Cham. 2023. p. 936-947. (Mechanisms and Machine Science). Epub 2023 Mar 3. doi: 10.1007/978-3-031-26193-0_82

Fault Detection and Diagnosis of Gearbox Oil Shortage Using Motor Current Signature

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