| contributor author | Faris Elasha | |
| contributor author | David Mba | |
| contributor author | Matthew Greaves | |
| date accessioned | 2017-12-16T09:22:21Z | |
| date available | 2017-12-16T09:22:21Z | |
| date issued | 2017 | |
| identifier other | %28ASCE%29AS.1943-5525.0000744.pdf | |
| identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4241998 | |
| description abstract | Bearing vibration signal separation is essential for fault detection of gearboxes, especially where the vibration is nonstationary, susceptible to background noise, and subjected to an arduous transmission path from the source to the receiver. This paper presents a methodology for improving fault detection via a series of vibration signal processing techniques, including signal separation, synchronous averaging (SA), spectral kurtosis (SK), and envelope analysis. These techniques have been tested on experimentally obtained vibration data acquired from the transmission system of a CS-29 Category A helicopter gearbox operating under different bearing damage conditions. Results showed successful enhancement of bearing fault detection on the second planetary stage of the gearbox | |
| publisher | American Society of Civil Engineers | |
| title | Bearing Signal Separation Enhancement with Application to a Helicopter Transmission System | |
| type | Journal Paper | |
| journal volume | 30 | |
| journal issue | 5 | |
| journal title | Journal of Aerospace Engineering | |
| identifier doi | 10.1061/(ASCE)AS.1943-5525.0000744 | |
| tree | Journal of Aerospace Engineering:;2017:;Volume ( 030 ):;issue: 005 | |
| contenttype | Fulltext | |