A main bearing fault feature enhancement method based on cyclical information extraction

被引：0
|
作者：
Luan X. [1 ]
Zhao J. [1 ]
Sha Y. [1 ]
Tong X. [1 ]
Zhang Z. [1 ]
机构：
[1] Key Laboratory of Advanced Measurement and Test Technique for Aviation Propulsion System, Liaoning Province, School of Aero-Engine, Shenyang Aerospace University, Shenyang
来源：
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | 2024年 / 45卷 / 03期
关键词：
aero engine; fault feature enhancement; feature information cycle extraction criteria; rolling bearings; wavelet packet decomposition;
D O I：
10.19650/j.cnki.cjsi.J2311990
中图分类号：
学科分类号：
摘要：
In response to the problem of insufficient feature information extraction when the main bearing of aircraft engine fails, a method for enhancing the fault characteristics of main bearings based on cyclic extraction of effective information is proposed. Firstly, the original vibration signals are decomposed using wavelet packet decomposition, and the correlation coefficient and kurtosis values of each node component are calculated and normalized, and then fused into a comprehensive parameter Pi. Secondly, a confidence interval is defined based on the feature information cyclic extraction criterion, which divides all node components into three parts: high signal-to-noise ratio signals, low signal-to-noise ratio signals, and high noise signals. Then, high signal-to-noise ratio signals are continuously selected until the termination condition is reached. Finally, all high signal-to-noise ratio signals are reconstructed, and envelope demodulation is performed to extract the weak fault characteristics of the bearings. Simulation signal verification shows that the signal-to-noise ratio of the denoised signal is improved by 11.31 dB compared to before denoising. The effectiveness of the feature information cyclic extraction method is comprehensively verified based on the data measured from a simulated test bench for intermediate shaft bearings in aircraft engines, and an analysis of the vibration signals of a certain type of aircraft engine main bearings is conducted. Practice shows that This method is suitable for feature extraction of rolling bearing under the condition of strong background noise interference, and can accurately diagnose the main bearing fault of aircraft engine. © 2024 Science Press. All rights reserved.
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页码：251 / 262
页数：11
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