基于自适应共振解调技术的滚动轴承故障诊断

潘阳; 陈安华; 蒋玲莉; 李学军

doi:10.13433/j.cnki.1003-8728.2015.0217

基于自适应共振解调技术的滚动轴承故障诊断

doi: 10.13433/j.cnki.1003-8728.2015.0217

1.
湖南科技大学机械设备健康维护湖南省重点实验室, 湘潭 411201

基金项目:

国家自然科学基金项目（51105138，51175169）、湖南省教育厅科学研究优秀青年项目（14B057）及湖南省高校科技创新团队支持计划项目资助

详细信息

作者简介:
潘阳（1986-），硕士研究生，研究方向为设备状态监测与故障诊断，ypan86@163.com

通讯作者:
陈安华，教授，博士生导师，ahchen@hnust.edu.cn

计量
- 文章访问数: 158
- HTML全文浏览量: 26
- PDF下载量: 9
- 被引次数: 0
出版历程
- 收稿日期: 2013-07-23
- 刊出日期: 2015-02-05

Fault Diagnosis of Rolling Bearing Based on Adaptive Resonance Demodulation Technique

1.
Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan 411201

摘要

摘要: 针对现有共振解调技术中高频共振中心频率及滤波带宽确定方法不成熟的问题，提出了自适应共振解调技术。利用经验模态分解将故障信号分解成若干个固有模态函数，通过信息熵最小的固有模态函数分量确定高频共振频率，自适应选取带通滤波器的中心频率和带宽。利用Hilbert变换对滤波后的信号进行解调分析，得到包含故障特征信息的低频包络信号，提取故障特征频率，实现故障辨识。与现有共振解调方法相比，自适应共振解调方法在工程实际中应用性更强。
- 自适应共振解调 /
- EMD /
- 滚动轴承 /
- 故障诊断 /
- 信息熵
Abstract: Aiming at the difficult problems of determining center frequency of high-frequency resonance and selecting bandwidth of the band-pass filter in the current resonance demodulation technique, an adaptive resonance demodulation technique was used to overcome the drawbacks. The key point of the method is to select adaptively center frequency and bandwidth of band-pass filter. Firstly, the fault signal is decomposed into several intrinsic mode functions (IMF) by empirical mode decomposition (EMD) technique; then, the information entropy of IMF component is calculated, the smallest component of information entropy to determine high-frequency resonance frequency is selected; finaly, the Hilbert transform is used to demodulate the envelope signals after band-pass filter, which obtain low-frequency signal of fault characteristic information. Compared with the existing resonance demodulation method, the adaptive resonance demodnlation method shows better for rolling bearing fault diagnosis in engineering practice.
- adaptive resonance demodulation /
- bandpass filters /
- bandwidth /
- dernodulation /
- diagnosis

HTML全文

参考文献(9)

[1]	唐德尧.共振解调技术在机械故障诊断中的应用和发展(一)[J].设备管理与维修,1991,85(11):22-24 Tang D Y. The technology of resonant demodulation in application and development of the mechanical fault diagnosis(一)[J]. Equipment Management and Maintenance,1991,85(11):22-24 (in Chinese)
[2]	王平,廖明夫.滚动轴承故障诊断的自适应共振解调技术[J].航空动力学报,2005,20(4):606-612 Wang P, Liao M F. Adaptive demodulated resonance technique for the rolling bearing fault diagnosis[J].Journal of Aerospace Power,2005,20(4):606-612 (in Chinese)
[3]	朱汉明,谭永红.EMD共振解调在滚动轴承故障诊断中的应用[J].上海师范大学学报,2011,40(3):254-258 Zhu H M, Tan Y H. Application of EMD and resonance demodulation in rolling bearing fault diagnosis[J]. Journal of Shanghai Normal University,2011,40(3):254-258 (in Chinese)
[4]	傅祖芸.信息论基础[M].北京:电子工业出版社,1986 Fu Z Y. Information theory basis[M]. Beijing:Electronic Industry Press,1986 (in Chinese)
[5]	Huang N E,Shen Z,Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Royal Society of London Proceedings Series A,1998,454(3)
[6]	蒋玲莉,刘义伦,李学军,等.EMD-模糊聚类法及在滚动轴承故障诊断中的应用[J].机械强度,2011,33(5):650-654 Jiang L L, Liu Y L, Li X J, et al. Fault diagnosis of roller bearing based on EMD and fuzzy cluster[J]. Journal of Mechanical Strength,2011,33(5):650-654 (in Chinese)
[7]	韩中和,韩悦,朱霄珣.基于IMF信息熵与SVM的转子振动故障智能诊断方法[J].华北电力大学学报,2012,39(4):81-85 Han Z H, Han Y, Zhu X X.A fault diagnosis method for rotor vibration based on IMF information entropy and SVM[J]. Journal of North China Electric Power University,2012,39(4):81-85 (in Chinese)
[8]	马波,魏强,徐春林,等.基于Hilbert变换的包络分析及其在滚动轴承故障诊断中的应用[J].北京化工大学学报,2004,31(4):95-97 Ma B, Wei Q, Xu C L, et al. Envelope analysis based on Hilbert transformation and its application in ball bearing fault diagnosis[J]. Journal of Beijing University of Chemical Technology,2004,31(4):95-97 (in Chinese)
[9]	Liu W, Yan Y H, Wang R l. Application of hilbert-huang transform and svm to coal gangue interface detection [J]. Journal of Computers,2011,6(6):1262-1269