Using empirical mode decomposition scheme for helicopter main gearbox bearing defect identification

Conference paper


Duan, F, Corsar, M and Mba, D (2016). Using empirical mode decomposition scheme for helicopter main gearbox bearing defect identification. Prognostics and System Health Management Conference (PHM-Chengdu), 2016. Chengdu, China 19 - 21 Oct 2016 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/PHM.2016.7819829
AuthorsDuan, F, Corsar, M and Mba, D
TypeConference paper
Abstract

© 2016 IEEE. Vibration sensors for helicopter health and condition monitoring have been widely employed to ensure the safe operation. Through the years, vibration sensors are now commonly placed on helicopters and have claimed a number of successes in preventing accidents. However, vibration based bearing defect identification remains a challenge since bearing defects signatures are usually contaminated by background noise resulting from variable transmission paths from the bearing to the receiving externally mounted vibration sensors. In this paper, the empirical mode decomposition (EMD) scheme was utilized to analyze vibration signal captured from a CS29 Category 'A' helicopter main gearbox, where bearing faults were seeded on one of the planetary gears bearing of the second epicyclic stage. The EMD scheme decomposed vibration signal into a number of intrinsic mode functions (IMFs) for subsequent envelope analysis. The selection of appropriate IMFs to characterize bearing fault signatures was discussed. The analysis result showed that the bearing fault signatures were successfully characterized and revealed the efficacy of the EMD scheme.

Year2016
JournalProceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Digital Object Identifier (DOI)https://doi.org/10.1109/PHM.2016.7819829
Accepted author manuscript
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Print19 Oct 2016
Publication process dates
Deposited05 Dec 2017
Accepted19 Oct 2016
ISBN9781509027781
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https://openresearch.lsbu.ac.uk/item/871xq

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