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| Fault Feature Enhancement Method for Main Bearing of Aircraft Engine Based on Optimized Wavelet Packet Decomposition |
| Received:August 08, 2024 Revised:September 04, 2024 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7643/issn.1672-9242.2024.09.006 |
| KeyWord:main bearing optimized wavelet packet decomposition maximum correlation kurtosis deconvolutio calculation order analysis fault feature enhancement fault analysis |
| Author | Institution |
| ZHANG Zhenpeng |
Liaoning Key Laboratory of Advanced Test Technology for Aeronautical Propulsion System, Shenyang Aerospace University, Shenyang , China |
| LUAN Xiaochi |
Liaoning Key Laboratory of Advanced Test Technology for Aeronautical Propulsion System, Shenyang Aerospace University, Shenyang , China |
| SHA Yundong |
Liaoning Key Laboratory of Advanced Test Technology for Aeronautical Propulsion System, Shenyang Aerospace University, Shenyang , China |
| YANG Jie |
AECC Shenyang Engine Research Institute, Shenyang , China |
| ZHAO Fengtong |
Liaoning Key Laboratory of Advanced Test Technology for Aeronautical Propulsion System, Shenyang Aerospace University, Shenyang , China |
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| Abstract: |
| In order to solve the problem that weak fault features of main bearing of aero-engine are difficult to be identified in high background noise environment and variable speed condition, the work aims to propose an enhancement method of fault features of main bearing of aircraft engine based on optimized wavelet packet decomposition. Firstly, the vibration time domain signal was transformed into vibration angle domain signal by calculation order analysis method. Then, the vibration angle domain signal was decomposed by wavelet packet, and the effective fault feature energy ratio and optimized maximum correlation kurtosis deconvolution method were introduced to enhance the signal fault features, and the fault features were gradually extracted through cyclic iteration. Finally, the signal envelope analysis was carried out and the bearing fault diagnosis was realized by comparing with the theoretical bearing fault order. By analyzing the test data of the main bearing outer ring of the aircraft engine under test conditions, it was verified that the proposed method could effectively enhance the fault feature information in the vibration signal. The results show that compared with the traditional WPD method, the proposed method can effectively enhance the fault feature order of main bearing, and realize fault diagnosis under high background noise environment and variable speed. |
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