A novel condition indicator for bearing fault detection within helicopter transmission
| dc.contributor.author | Elasha, F. | |
| dc.contributor.author | Li, X. | |
| dc.contributor.author | Mba, D. | |
| dc.contributor.author | Ojolo, S.J. | |
| dc.contributor.author | Ogundare, A.A. | |
| dc.date.accessioned | 2020-11-13T08:20:07Z | |
| dc.date.available | 2020-11-13T08:20:07Z | |
| dc.date.issued | 2020-06-13 | |
| dc.description | Staff Publications | en_US |
| dc.description.abstract | Helicopter usage and monitoring system (HUMS) is one of the critical systems for helicopter’s safety and reliability. Whilst HUMS has proven to be effective in detecting gears’ defects, bearing failures are not adequately detected using current monitoring indicators. Detection of bearing faults in helicopter gearboxes is made challenging by the presence of the complicated signal transmission path attenuating the monitored signal to the receiving sensor. To ensure safe operation of helicopters, this research proposes a novel condition indicator to detect bearing faults in helicopter gearboxes. For this purpose, vibration measurements captured from a CS-29 category ‘A’ helicopters test rig were utilized for detecting a bearing defect that has occurred in the epicyclic module of the main gearbox. Signals of rolling element bearings under various fault conditions were collected, and an adaptive filter algorithm was utilized to separate the random component of the signal. The resultant signatures were then further processed using wavelet analysis to extract the bearing signal of interest. Results showed that this new indicator successfully detect bearing faults. Besides, the impulse energy indicator responds consistently to the fault severity compared to the traditional indicators such as RMS and kurtosis. A technique to extract frequency band corresponding to the bearing fault impulses has been developed and tested. The technique employs the adaptive filter signal separation, wavelet packet decomposition and the combination of RMS and kurtosis to select the optimum filter band. | en_US |
| dc.identifier.citation | Faris Elasha, Xiaochuan Li, David Mba, Adebayo Ogundare, Sunday Ojolo (2020). A Novel Condition Indicator for Bearing Fault Detection Within Helicopter Transmission. Journal of Vibration Engineering & Technologies, | en_US |
| dc.identifier.issn | 2523-3920 | |
| dc.identifier.uri | https://ir.unilag.edu.ng/handle/123456789/8922 | |
| dc.language.iso | en | en_US |
| dc.publisher | Springer | en_US |
| dc.relation.ispartofseries | Journal of Vibration Engineering & Technologies; | |
| dc.subject | Bearing | en_US |
| dc.subject | Signal sepration | en_US |
| dc.subject | Vibration | en_US |
| dc.subject | Fault detection | en_US |
| dc.subject | Research Subject Categories::TECHNOLOGY::Engineering mechanics | en_US |
| dc.title | A novel condition indicator for bearing fault detection within helicopter transmission | en_US |
| dc.type | Article | en_US |