Improved Holo-Hilbert Spectrum Analysis-Based Fault Diagnosis Method for Rotating Machines

Zheng, J; Ying, W; Pan, H; Tong, J; Liu, Q; Ji, J

Improved Holo-Hilbert Spectrum Analysis-Based Fault Diagnosis Method for Rotating Machines

Zheng, J Ying, W Pan, H Tong, J Liu, Q Ji, J

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Publisher:: Chinese Journal of Mechanical Engineering
Publication Type:: Journal Article
Citation:: Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2023, 59, (1), pp. 162-174
Issue Date:: 2023-01-01

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Field	Value	Language
dc.contributor.author	Zheng, J
dc.contributor.author	Ying, W
dc.contributor.author	Pan, H
dc.contributor.author	Tong, J
dc.contributor.author	Liu, Q
dc.contributor.author	Ji, J https://orcid.org/0000-0003-3280-5463
dc.date.accessioned	2023-11-07T02:17:43Z
dc.date.available	2023-11-07T02:17:43Z
dc.date.issued	2023-01-01
dc.identifier.citation	Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2023, 59, (1), pp. 162-174
dc.identifier.issn	0577-6686
dc.identifier.uri	http://hdl.handle.net/10453/173151
dc.description.abstract	Although the time-frequency analysis method can extract both the time and frequency domains information of vibration signal for the faulty equipment simultaneously, its use in reflecting the cross-scale coupling relationship between the amplitude-modulation and frequency-modulation characteristics of the nonlinear vibration signal has so far been hindered, and it is prone to be interfered by noises. On this base, the Holo-Hilbert spectral analysis (HHSA) method is innovatively introduced into mechanical fault diagnosis. The internal modulation characteristics of vibration signals can be completely described by the HHSA method with double-layer empirical mode decomposition (EMD) structure, making it an ideal tool for detecting the local faults of mechanical components. At the same time, to improve the diagnosis accuracy of HHSA and suppress the noise interference and the mode aliasing caused by EMD, an improved HHSA (IHHSA) method based on improved regenerated phase shifted sinusoidal assisted EMD (IRPSEMD) is proposed. The usefulness of the IHHSA method for local fault feature diagnosis are validated by the analysis of simulation signals. Finally, the IHHSA method is applied to the detection of gear crack fault and the diagnosis of rolling bearings with local fault. The results show that the internal modulation relationship of nonlinear fault vibration signal can be reflected by the proposed IHHSA method comprehensively, which shows a better fault identification ability.
dc.language	en
dc.publisher	Chinese Journal of Mechanical Engineering
dc.relation.ispartof	Jixie Gongcheng Xuebao/Journal of Mechanical Engineering
dc.relation.isbasedon	10.3901/JME.2023.01.162
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0913 Mechanical Engineering
dc.subject.classification	Mechanical Engineering & Transports
dc.subject.classification	4017 Mechanical engineering
dc.title	Improved Holo-Hilbert Spectrum Analysis-Based Fault Diagnosis Method for Rotating Machines
dc.type	Journal Article
utslib.citation.volume	59
utslib.for	0913 Mechanical 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	2023-11-07T02:17:41Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	59
utslib.citation.issue	1

Abstract:

Although the time-frequency analysis method can extract both the time and frequency domains information of vibration signal for the faulty equipment simultaneously, its use in reflecting the cross-scale coupling relationship between the amplitude-modulation and frequency-modulation characteristics of the nonlinear vibration signal has so far been hindered, and it is prone to be interfered by noises. On this base, the Holo-Hilbert spectral analysis (HHSA) method is innovatively introduced into mechanical fault diagnosis. The internal modulation characteristics of vibration signals can be completely described by the HHSA method with double-layer empirical mode decomposition (EMD) structure, making it an ideal tool for detecting the local faults of mechanical components. At the same time, to improve the diagnosis accuracy of HHSA and suppress the noise interference and the mode aliasing caused by EMD, an improved HHSA (IHHSA) method based on improved regenerated phase shifted sinusoidal assisted EMD (IRPSEMD) is proposed. The usefulness of the IHHSA method for local fault feature diagnosis are validated by the analysis of simulation signals. Finally, the IHHSA method is applied to the detection of gear crack fault and the diagnosis of rolling bearings with local fault. The results show that the internal modulation relationship of nonlinear fault vibration signal can be reflected by the proposed IHHSA method comprehensively, which shows a better fault identification ability.

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http://hdl.handle.net/10453/173151