Time-frequency enhancement technique for bevel gear fault diagnosis
Gear failure is one of the most common causes of breakdown in rotating machineries. It is well known that vibration signals from machineries can be effectively used to detect certain gear faults. Yet it is still not an easy task to find a symptom that reflects a particular fault from vibration signa...
| Main Authors: | , , , |
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| Format: | Article |
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Édition Diffusion Presse Sciences
2016
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| Online Access: | https://eprints.nottingham.ac.uk/47359/ |
| _version_ | 1848797525922807808 |
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| author | Hartono, Dennis Halim, Dunant Widodo, Achmad Roberts, Gethin Wyn |
| author_facet | Hartono, Dennis Halim, Dunant Widodo, Achmad Roberts, Gethin Wyn |
| author_sort | Hartono, Dennis |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Gear failure is one of the most common causes of breakdown in rotating machineries. It is well known that vibration signals from machineries can be effectively used to detect certain gear faults. Yet it is still not an easy task to find a symptom that reflects a particular fault from vibration signals. This paper presents an advanced time-frequency signal processing technique for extracting important gear fault information from the vibration signal that is heavily corrupted by measurement noise. Experiments were performed on a bevel gearbox test rig using vibration measurements. The Time Synchronous Average (TSA) was initially utilized to eliminate all asynchronous component of vibration signal obtained from the gear. The Continuous Wavelet Transform (CWT) method was then used to capture the non-stationary behaviour of the impulse signal generated from the broken bevel gear tooth. It was shown that the diagnosis method using the Continuous Wavelet Transform combined with Time Synchronous Averaging outperformed the conventional spectral analysis, capable of identifying the angular location of broken teeth in the gear. |
| first_indexed | 2025-11-14T20:05:16Z |
| format | Article |
| id | nottingham-47359 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:05:16Z |
| publishDate | 2016 |
| publisher | Édition Diffusion Presse Sciences |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-473592020-05-04T18:07:12Z https://eprints.nottingham.ac.uk/47359/ Time-frequency enhancement technique for bevel gear fault diagnosis Hartono, Dennis Halim, Dunant Widodo, Achmad Roberts, Gethin Wyn Gear failure is one of the most common causes of breakdown in rotating machineries. It is well known that vibration signals from machineries can be effectively used to detect certain gear faults. Yet it is still not an easy task to find a symptom that reflects a particular fault from vibration signals. This paper presents an advanced time-frequency signal processing technique for extracting important gear fault information from the vibration signal that is heavily corrupted by measurement noise. Experiments were performed on a bevel gearbox test rig using vibration measurements. The Time Synchronous Average (TSA) was initially utilized to eliminate all asynchronous component of vibration signal obtained from the gear. The Continuous Wavelet Transform (CWT) method was then used to capture the non-stationary behaviour of the impulse signal generated from the broken bevel gear tooth. It was shown that the diagnosis method using the Continuous Wavelet Transform combined with Time Synchronous Averaging outperformed the conventional spectral analysis, capable of identifying the angular location of broken teeth in the gear. Édition Diffusion Presse Sciences 2016-08-11 Article PeerReviewed Hartono, Dennis, Halim, Dunant, Widodo, Achmad and Roberts, Gethin Wyn (2016) Time-frequency enhancement technique for bevel gear fault diagnosis. MATEC Web of Conferences, 70 . 02003/1-02003/5. ISSN 2261-236X https://www.matec-conferences.org/articles/matecconf/abs/2016/33/matecconf_icmit2016_02003/matecconf_icmit2016_02003.html doi:10.1051/matecconf/20167002003 doi:10.1051/matecconf/20167002003 |
| spellingShingle | Hartono, Dennis Halim, Dunant Widodo, Achmad Roberts, Gethin Wyn Time-frequency enhancement technique for bevel gear fault diagnosis |
| title | Time-frequency enhancement technique for bevel gear fault diagnosis |
| title_full | Time-frequency enhancement technique for bevel gear fault diagnosis |
| title_fullStr | Time-frequency enhancement technique for bevel gear fault diagnosis |
| title_full_unstemmed | Time-frequency enhancement technique for bevel gear fault diagnosis |
| title_short | Time-frequency enhancement technique for bevel gear fault diagnosis |
| title_sort | time-frequency enhancement technique for bevel gear fault diagnosis |
| url | https://eprints.nottingham.ac.uk/47359/ https://eprints.nottingham.ac.uk/47359/ https://eprints.nottingham.ac.uk/47359/ |