基于最小熵解卷积的齿轮箱早期故障诊断

冷军发; 荆双喜; 禹建功

doi:10.13433/j.cnki.1003-8728.2015.0324

基于最小熵解卷积的齿轮箱早期故障诊断

doi: 10.13433/j.cnki.1003-8728.2015.0324

1.
河南理工大学机械与动力工程学院, 焦作 454000

基金项目:

国家自然科学基金项目（11272115）与河南省机械工程重点学科项目资助

详细信息

作者简介:
冷军发（1974-），副教授，博士研究生，研究方向为机械振动及故障诊断，lengjf@hpu.edu.cn

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出版历程
- 收稿日期: 2013-08-13
- 刊出日期: 2015-03-05

Incipient Fault Diagnosis of the Gear box Based on the Minimum Entropy Deconvolution

1.
School of Mechanical and Power Engineering, Henan Polytechnic University, Jiaozuo 454000

摘要

摘要: 齿轮箱发生早期故障时，其振动信号一般很微弱，且隐含的能反应出齿轮箱运转状态的冲击成分常被淹没在强烈的噪声中，直接做频谱分析或包络谱分析，很难提取其故障特征。论文将最小解卷积方法应用于炼胶机的齿轮箱故障诊断。首先利用该方法对齿轮箱振动信号进行解卷积滤波处理，然后对滤波后的信号进行包络解调分析，最后提取出了该齿轮箱轴5上齿轮8（z8=28）齿根轻微裂纹的故障特征，实现了该齿轮箱的早期诊断。应用实例验证了最小熵解卷积方法的有效性和优点。
- 齿轮箱 /
- 故障诊断 /
- 最小熵解卷积 /
- 包络分析
Abstract: Comparing with the strong background noise, the gear's vibration signal is usually very weak when occurring the incipient fault of gear box, and with concealed impulse component reflecting the operating state of the gearbox. The vibration feature is very difficult to extract through frequency spectrum or envelope spectrum analysis. The minimum entropy deconvolution (MED) was adopted to carry out the fault diagnosis of gear box for rubber refiner. The vibration signal of gearbox was firstly filtered with the MED method, then the filtered signal was demodulated with the envelope spectrum, and the fault feature of root slight crack of gear 8(z8=28) on the shaft five was successfully extracted. Therefore, the incipient fault diagnosis of the gear box was realized. The application results verify the effectiveness and advantage of MED method.
- autocorrelation /
- crack detection /
- deconvolution /
- demodulation

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参考文献(11)

[1]	李崇晟.齿轮早期疲劳裂纹的混沌检测方法[J].机械工程学报,2005,41(8):196-198 Li C S. Chaotic detection method of gear early-stage fatigue crack[J]. Chinese Journal of Mechanical Engineering,2005,41(8):196-198 (in Chinese)
[2]	杨通强,郑海起,唐力伟,等.基于角域平均和倒阶次谱分析的齿轮箱故障[J].机械科学与技术,2006,25(4):452-455 Yang T Q, Zheng H Q, Tang L W, et al. Gearbox fault diagnosis based on angle domain averaging and order cepstrum analysis[J]. Mechanical Science and Technology,2006,25(4):452-455 (in Chinese)
[3]	崔玲丽,高立新,蔡力钢,等.基于循环平稳解调的齿轮裂纹早期故障诊断研究[J].振动工程学报,2008,28(3):274-278 Cui L L, Gao L X, Cai L G, et al. Gear tooth crack early fault diagnosis based on the cyclostationary demodulation[J]. Journal of Vibration Engineering,2008,21(3):274-278 (in Chinese)
[4]	鞠萍华,秦树人,秦毅,等.多分辨EMD方法与频域平均在齿轮早期故障诊断中的研究[J].振动与冲击,2009,28(5):97-101 Ju P H, Qin S R, Qin Y, et al. Research on earlier fault diagnosis of gear by method of multi-resolution empirical mode decomposition and frequency domain averaging[J]. Journal of Vibration and Shock,2009,28(5):97-101 (in Chinese)
[5]	程军圣,杨怡,杨宇.基于LMD的谱峭度方法在齿轮故障诊断中的应用[J].振动与冲击,2012,31(18):20-24 Cheng J S, Yang Y, Yang Y. Application of spectral kurtosis approach based on local mean decomposition (LMD) in gear fault diagnosis[J]. Journal of Vibration and Shock,2012,31(18):20-24 (in Chinese)
[6]	Wiggins R A. Minimum entropy deconvolution[J]. Geoexploration,1978,16:21-35
[7]	Donoho D L. On minimum entropy deconvolution[M]. Applied Time Series Analysis Ⅱ, New York:Acodemic Press,1981:565-609
[8]	Endo H, Randall R B. Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter[J]. Mechanical Systems and Signal Processing,2007,21:906-919
[9]	Sawalhi N, Randall R B, Endo H. The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis[J]. Mechanical Systems and Signal Processing,2007,21:2616-2633
[10]	Li X, Li X B, Liang W, et al. l0-norm regularized minimum entropy deconvolution for ultrasonic NDT & E[J]. NDT & E International,2012,47:80-87
[11]	王宏超,陈进,董广明.基于最小熵解卷积与稀疏分解的滚动轴承微弱故障特征提取[J].机械工程学报,2013,49(1):88-94 Wang H C, Chen J, Dong G M. Fault diagnosis method for rolling bearing's weak fault based on minimum entropy deconvolution and sparse decomposition[J]. Journal of Mechanical Engineering,2013,49(1):88-94 (in Chinese)