Wavelet-based Control Chart for Early Detection of Gear Failure
Research output: Conference Papers (RGC: 31A, 31B, 32, 33) › 32_Refereed conference paper (no ISBN/ISSN) › peer-review
Author(s)
Detail(s)
| Original language | English |
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| Publication status | Accepted/In press/Filed - 2016 |
Conference
| Title | The 29th International Congress on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2016) |
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| Location | |
| Place | China |
| City | Xi'an |
| Period | 20 - 22 August 2016 |
Link(s)
| Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(058b00d4-1347-4e02-af51-a2d88ddb96d0).html |
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Abstract
In mechanical system, the measured fault features are always surrounded with
strong noise in the early-fault-state, which makes it difficult to monitor the operating condition of the system. A novel statistical method based on wavelet transform is developed in this study for early fault detection. The measured vibration signal is decomposed by tunable Q-factor wavelet transform (TQWT) into wavelet coefficients at different stages. The energy of the wavelet coefficient at each stage is monitored by the control chart. The Hilbert envelope spectrum is incorporated to extract the fault frequency of the fault signal reconstructed by the out of control coefficient stages. Both the simulation study and the application study show the effectiveness of the proposed method.
strong noise in the early-fault-state, which makes it difficult to monitor the operating condition of the system. A novel statistical method based on wavelet transform is developed in this study for early fault detection. The measured vibration signal is decomposed by tunable Q-factor wavelet transform (TQWT) into wavelet coefficients at different stages. The energy of the wavelet coefficient at each stage is monitored by the control chart. The Hilbert envelope spectrum is incorporated to extract the fault frequency of the fault signal reconstructed by the out of control coefficient stages. Both the simulation study and the application study show the effectiveness of the proposed method.
Research Area(s)
- Statistical process control, Control chart, Wavelet, Early detection, Gearbox failure
Citation Format(s)
Wavelet-based Control Chart for Early Detection of Gear Failure. / FAN, Wei; ZHOU, Qiang; Zhu, Zhongkui.
2016. Paper presented at The 29th International Congress on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2016), Xi'an, China.Research output: Conference Papers (RGC: 31A, 31B, 32, 33) › 32_Refereed conference paper (no ISBN/ISSN) › peer-review
