An Enhanced Spectral Kurtosis Methodforaero-Engine Gear Hub Fault Diagnosis

Journal of Propulsion Technology ›› 2017, Vol. 38 ›› Issue (5): 1140-1146.

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An Enhanced Spectral Kurtosis Methodforaero-Engine Gear Hub Fault Diagnosis

School of Aeronautics and Astronautics Engineering，Air Force Engineering University，Xi’an 710038，China,School of Aeronautics and Astronautics Engineering，Air Force Engineering University，Xi’an 710038，China,School of Aeronautics and Astronautics Engineering，Air Force Engineering University，Xi’an 710038，China and School of Aeronautics and Astronautics Engineering，Air Force Engineering University，Xi’an 710038，China

Published:2021-08-15

基于加强谱峭度的航空发动机齿轮毂故障诊断

钟也磐,陈卫,杜炜,巩孟林

空军工程大学航空航天工程学院，陕西西安 710038,空军工程大学航空航天工程学院，陕西西安 710038,空军工程大学航空航天工程学院，陕西西安 710038,空军工程大学航空航天工程学院，陕西西安 710038

作者简介:钟也磐，男，硕士生，研究领域为航空测试技术与故障诊断。
基金资助:
国家自然科学基金项目(51175509)。

Abstract

Abstract: As for the issues of fault diagnosis for reducer gear hub of the aero-engine，an enhanced spectral kurtosis method based on the wavelet packet transform(WPT)and cubic Hermite interpolation-local mean decomposition(CHI-LMD)was presented. Under the noise reduction of autoregressive(AR)model，firstly the signal was decomposed by WPT and the feature band with spectral kurtosis was obtained. Then，feature band was decomposed by CHI-LMD to get product functions(PFs)and finally took spectral kurtosis of PF as the final diagnostic parameters. The diagnosis adopting this method on 10 groups of undetermined signal indicated that the proposed method could determine the fault of reducer gear hub efficiently，which realized the fault diagnosis of target without dismantling aero-engine.

Key words: Aero-engine；Fault diagnosis；AR model；WPT；Spectral kurtosis

摘要： 针对航空发动机减速器一级齿轮毂故障诊断问题，提出了一种基于小波包和CHI-LMD(三次Hermite插值-局部均值分解)的加强谱峭度的故障诊断方法。在用AR(自回归)参数模型对原始信号进行降噪后，首先采用小波包对信号进行分解，并结合谱峭度找出特征频带，继而用CHI-LMD对特征频带进行再分解获得若干PF分量，最后对获得的PF分量计算谱峭度作为故障识别参数。利用此方法对10组待识别信号的诊断结果表明，该方法能有效识别减速器一级齿轮毂故障，在不拆卸发动机的情况下实现了对目标的诊断。

关键词: 航空发动机；故障诊断；AR模型；小波包；谱峭度

ZHONG Ye-pan,CHEN Wei,DU Wei,GONG Meng-lin. An Enhanced Spectral Kurtosis Methodforaero-Engine Gear Hub Fault Diagnosis[J]. Journal of Propulsion Technology, 2017, 38(5): 1140-1146.

钟也磐,陈卫,杜炜,巩孟林. 基于加强谱峭度的航空发动机齿轮毂故障诊断[J]. 推进技术, 2017, 38(5): 1140-1146.

References

[1] 何正嘉, 陈进, 王太勇, 等. 机械故障诊断理论及应用[M]. 北京:高等教育出版社, 2010: 84-85.
[2] 陶海亮, 左志涛, 高庆, 等. 基于时频分析的裂纹转子碰摩故障特征研究[J]. 推进技术, 2013, 34(4): 520-528. (TAO Hai-liang, ZUO Zhi-tao, GAO Qing, et al. Fault Analysis of Rotor with Rub-Impact and Crack Based on Time-Frequency Analysis[J]. Journal of Propulsion Technology, 2013, 34(4): 520-528.)
[3] Lei Y G, Lin J, He Z J, et al. Application of an Improved Kurtogram Method for Fault Diagnosis of Rolling Element Bearings[J]. Mechanical Systems and Signal Processing, 2011, 25: 1738-1749.
[4] Zhang X, Zhou J. Multi-Fault Diagnosis for Rolling Element Bearings Based on Ensemble Empirical Mode Decomposition and Optimized Support Vector Machines[J]. Mechanical Systems and Signal Processing, 2013, 41: 127-140.
[5] Smith J S. The Local Mean Decomposition and Its Application to EEG Perception Data[J]. Journal of the Royal Society Interface, 2005, 2(5): 443-454.
[6] WEN Chengyu, DONG Liang, JIN Xin. Feature Extraction of Bearing Vibration Signals Using Second Generation Wavelet and Spline-Based Local Mean Decomposition[J]. Shanghai Jiaotong Univ.(Sci.), 2015, 20(1): 56-60.
[7] 邓林峰, 赵荣珍. 基于CHI-LMD 方法的转子振动信号分析[J]. 振动与冲击, 2014, 33(15): 59-63.
[8] Antoni J. The Spectral Kurtosis: a Useful Tool for Characterizing Nonstationary Signals[J]. Mechanical Systems and Signal Processing, 2006, 20: 282-307.
[9] Antoni J. Fast Computation of the Kurtogram for the Detection of Transient Faults[J]. Mechanical Systems and Signal Processing, 2007, 21: 108-124.
[10] Wang D, Tse P W, Tsui K L. An Enhanced KurtogramMethod for Fault Diagnosis of Rolling Element Bearings[J]. Mechanical Systems and Signal Processing, 2013, 35: 176-199.
[11] Kay S M, Marple S L. Spectrum Analysis—a Modern Perspective[J]. Proceedings of the IEEE, 1981, 69: 1380-1419.
[12] Antoni J, Randall R B. The Spectral Kurtosis: Application to the Vibratory Surveillance and Diagnostics of Rotating Machines[J]. Mechanical Systems and Signal Processing, 2006, 20: 308-331.
[13] Antoni J. Fast Computation of the Kurtogram for the Detection of Transient Faults[J]. Mechanical Systems and Signal Processing, 2007, 21: 108-124.
[14] 韩磊, 洪杰, 王冬. 基于小波包分析的航空发动机轴承故障诊断[J]. 推进技术, 2009, 30(3): 329-332. (HAN Lei, HONG Jie, WANG Dong. Fault Diagnosis of Aero-Engine Bearings Based on Wavelet Package Analysis[J]. Journal of Propulsion Technology, 2009, 30(3): 329-332.)
[15] 程军圣, 张亢, 杨宇, 等. 局部均值分解与经验模式分解的对比研究[J]. 振动与冲击, 2009, 28(5):15-19.　　　　　　　　　　　　　*　收稿日期:2015-12-28；修订日期:2016-03-06。基金项目:国家自然科学基金项目(51175509)。作者简介:钟也磐,男,硕士生,研究领域为航空测试技术与故障诊断。E-mail: 2422156968@qq.com(编辑:田佳莹)

An Enhanced Spectral Kurtosis Methodforaero-Engine Gear Hub Fault Diagnosis

基于加强谱峭度的航空发动机齿轮毂故障诊断

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