A cyclostationarity-based wear monitoring framework of spur gears in intelligent manufacturing systems

Feng, K; Ni, Q; Chen, Y; Ge, J; Liu, Z

A cyclostationarity-based wear monitoring framework of spur gears in intelligent manufacturing systems

Feng, K Ni, Q Chen, Y Ge, J Liu, Z

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Publisher:: SAGE Publications
Publication Type:: Journal Article
Citation:: Structural Health Monitoring, 2023, 22, (5), pp. 3092-3108
Issue Date:: 2023-09-01

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Field	Value	Language
dc.contributor.author	Feng, K
dc.contributor.author	Ni, Q
dc.contributor.author	Chen, Y
dc.contributor.author	Ge, J
dc.contributor.author	Liu, Z
dc.date.accessioned	2024-04-13T20:53:19Z
dc.date.available	2024-04-13T20:53:19Z
dc.date.issued	2023-09-01
dc.identifier.citation	Structural Health Monitoring, 2023, 22, (5), pp. 3092-3108
dc.identifier.issn	1475-9217
dc.identifier.issn	1741-3168
dc.identifier.uri	http://hdl.handle.net/10453/177888
dc.description.abstract	The gearbox is widely applied as the mechanical transmission system of intelligent manufacturing systems, such as machine tools and robotics. The harsh working environments make the gear surface prone to wear. The progression of surface wear can bring severe failures to the gear tooth, including gear tooth root crack, surface spalling of gear tooth, and tooth breaking, all of which could damage the whole transmission system. Hence, it is essential to monitor and evaluate the gear surface wear propagation. The gear wear has been proven highly relevant with the vibration second-order cyclostationary (CS2) characteristics. Therefore, this paper develops a novel cyclostationarity-based framework to monitor and evaluate gear wear propagation. More specifically, the squared envelope (SE) of the residual signal, removing deterministic components, is utilized to identify the gear wear distribution and its propagation trends, validated using the measured gear surface morphology. Moreover, a new CS2-based indicator is proposed to assess the severity of gear surface wear, achieving a high correlation with measured surface roughness: (Formula presented.) is more than 0.9. The developed cyclostationarity-based framework can comprehensively evaluate the degradation status of the gear system caused by surface wear, significantly benefiting the health management of the gear transmission system, which is of great practical value for the health management of intelligent manufacturing systems. A series of endurance tests are conducted to verify the effectiveness and superiority of the developed framework for gear wear monitoring compared with the conventional indicators.
dc.language	en
dc.publisher	SAGE Publications
dc.relation.ispartof	Structural Health Monitoring
dc.relation.isbasedon	10.1177/14759217221147018
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	09 Engineering
dc.subject.classification	Acoustics
dc.subject.classification	40 Engineering
dc.title	A cyclostationarity-based wear monitoring framework of spur gears in intelligent manufacturing systems
dc.type	Journal Article
utslib.citation.volume	22
utslib.for	09 Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2024-04-13T20:53:15Z
pubs.issue	5
pubs.publication-status	Published
pubs.volume	22
utslib.citation.issue	5

Abstract:

The gearbox is widely applied as the mechanical transmission system of intelligent manufacturing systems, such as machine tools and robotics. The harsh working environments make the gear surface prone to wear. The progression of surface wear can bring severe failures to the gear tooth, including gear tooth root crack, surface spalling of gear tooth, and tooth breaking, all of which could damage the whole transmission system. Hence, it is essential to monitor and evaluate the gear surface wear propagation. The gear wear has been proven highly relevant with the vibration second-order cyclostationary (CS2) characteristics. Therefore, this paper develops a novel cyclostationarity-based framework to monitor and evaluate gear wear propagation. More specifically, the squared envelope (SE) of the residual signal, removing deterministic components, is utilized to identify the gear wear distribution and its propagation trends, validated using the measured gear surface morphology. Moreover, a new CS2-based indicator is proposed to assess the severity of gear surface wear, achieving a high correlation with measured surface roughness: (Formula presented.) is more than 0.9. The developed cyclostationarity-based framework can comprehensively evaluate the degradation status of the gear system caused by surface wear, significantly benefiting the health management of the gear transmission system, which is of great practical value for the health management of intelligent manufacturing systems. A series of endurance tests are conducted to verify the effectiveness and superiority of the developed framework for gear wear monitoring compared with the conventional indicators.

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http://hdl.handle.net/10453/177888