Using independent component analysis scheme for helicopter main gearbox bearing defect identification
Conference paper
Duan, F, Corsar, M, Zhou, L and Mba, D (2017). Using independent component analysis scheme for helicopter main gearbox bearing defect identification. 2017 IEEE International Conference on Prognostics and Health Management (ICPHM). Texas, USA 19 - 21 Jun 2017 Institute of Electrical and Electronics Engineers (IEEE). pp. 252-259 https://doi.org/10.1109/ICPHM.2017.7998337
| Authors | Duan, F, Corsar, M, Zhou, L and Mba, D |
|---|---|
| Type | Conference paper |
| Abstract | © 2017 IEEE. Vibration signal analysis is the most common technique for helicopter health condition monitoring. It has been widely employed to detect helicopter gearbox fault and ensure the safe operation. Through the years, vibration signal analysis has a significant contribution to successfully prevent a number of accidents. However, vibration based bearing identification remains a challenge because bearing defects signatures are contaminated by strong background noise. In this paper, the independent component analysis (ICA) scheme was utilized to analyze vibration signals captured from a CS29 Category 'A' helicopter main gearbox, where bearing faults were seeded on the second epicyclic stage planetary gears bearing. The ICA scheme could separate the multichannel signals into the mutually independent components. The bearing defect signature can be clearly observed in one of the independent components. The analysis result showed that ICA scheme is a promising method for detecting the bearing fault signatures. |
| Year | 2017 |
| Journal | 2017 IEEE International Conference on Prognostics and Health Management, ICPHM 2017 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Digital Object Identifier (DOI) | https://doi.org/10.1109/ICPHM.2017.7998337 |
| Accepted author manuscript | License File Access Level Open |
| Publication dates | |
| 19 Jun 2017 | |
| Publication process dates | |
| Deposited | 05 Dec 2017 |
| Accepted | 19 Jun 2017 |
| ISBN | 9781509057108 |
| Additional information | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Page range | 252-259 |
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