基于时频分析的轴承故障自动检测方法研究
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摘要
随着科学技术和生产的发展,机械设备朝着大型化、高速化、连续化以及结构复杂化的方向发展,一旦设备发生故障就可能引起灾难性的毁坏。因此故障诊断技术日益引起重视,并在理论和实践方面得到迅猛的发展。科学技术的发展,特别是非平稳信号处理技术不断完善,为机械设备故障诊断技术提供了良好的诊断方法。
本文主要围绕时频分析方法在滚动轴承故障诊断方面的问题进行了研究。研究短时傅立叶变换、Wigner-ville变换和小波变换的特点,并通过仿真信号验证。在时频分析的基础上提出了一种新的瞬态特征信号的自动检测方法,该方法将小波变换与自动检测方法结合起来检测信号特征,使小波变换系数周期性的叠加在极坐标上,从而达到特征增强和平滑噪声的目的;将该方法应用于滚动轴承故障信号的周期性瞬态特征的检测,有效的检测出了轴承在局部故障引起的瞬态特征。基于小波变换尺度图提出了一种能量系数重置法,将基于小波变换尺度图的能量系数重置法应用于设备故障诊断分析,能够有效的检测振动中反映局部故障的瞬态信号。
With development of the science and technology, machines are developing in the direction of larger size, higher speed and more complicated structure, and machine fault will bring more serious effect, so fault diagnosis is becoming more and more important for industry, and has got great development in both theory and practice. The development of science and technology, especially the fast growth of processing technology of non-stationary signal provides potential method for the machinery fault diagnosis.
This thesis mainly concerns the application of the fault diagnosis method based on time-frequency analysis in mechanical part fault diagnosis. The concept and property of STFT、WVD and CWT were expatiated via theoretical analysis and simulation and the CWT is found to be better for mechanical localized fault diagnosis. Based on the CWT representation of vibration signal, an automatic detection algorithm for signal transients is proposed, through which the periodical feature about the localized fault is overlapped and thus enhanced in the polar diagram and the feature about signal noise and about non-periodical components is de-noise oppositely. The application of the proposed algorithm in cone bearing localized fault shows that this method is rather effective in detecting the periodical transients for mechanical fault diagnosis. Based on the CWT representation, a mechanical fault diagnosis method through the reassignment of CWT coefficients, and the application of this method in cone bearing show effectiveness in representing the transient feature about the local fault in the time-scale plane.
本文主要围绕时频分析方法在滚动轴承故障诊断方面的问题进行了研究。研究短时傅立叶变换、Wigner-ville变换和小波变换的特点,并通过仿真信号验证。在时频分析的基础上提出了一种新的瞬态特征信号的自动检测方法,该方法将小波变换与自动检测方法结合起来检测信号特征,使小波变换系数周期性的叠加在极坐标上,从而达到特征增强和平滑噪声的目的;将该方法应用于滚动轴承故障信号的周期性瞬态特征的检测,有效的检测出了轴承在局部故障引起的瞬态特征。基于小波变换尺度图提出了一种能量系数重置法,将基于小波变换尺度图的能量系数重置法应用于设备故障诊断分析,能够有效的检测振动中反映局部故障的瞬态信号。
With development of the science and technology, machines are developing in the direction of larger size, higher speed and more complicated structure, and machine fault will bring more serious effect, so fault diagnosis is becoming more and more important for industry, and has got great development in both theory and practice. The development of science and technology, especially the fast growth of processing technology of non-stationary signal provides potential method for the machinery fault diagnosis.
This thesis mainly concerns the application of the fault diagnosis method based on time-frequency analysis in mechanical part fault diagnosis. The concept and property of STFT、WVD and CWT were expatiated via theoretical analysis and simulation and the CWT is found to be better for mechanical localized fault diagnosis. Based on the CWT representation of vibration signal, an automatic detection algorithm for signal transients is proposed, through which the periodical feature about the localized fault is overlapped and thus enhanced in the polar diagram and the feature about signal noise and about non-periodical components is de-noise oppositely. The application of the proposed algorithm in cone bearing localized fault shows that this method is rather effective in detecting the periodical transients for mechanical fault diagnosis. Based on the CWT representation, a mechanical fault diagnosis method through the reassignment of CWT coefficients, and the application of this method in cone bearing show effectiveness in representing the transient feature about the local fault in the time-scale plane.
引文
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2. 黄志坚,裘丽华,对现代机械故障诊断技术方法论的讨论,科学技术与辩证法,Vol.18, No.3, 26~29, 2001
3. 张瑞林,旋转机械故障机理与诊断技术[M],北京:机械工业出版社,2002
4. 王江萍等,设备状态监测与故障诊断技术及应用[M],西安:西安工业大学出版社,2003
5. 于晓红,张来斌,炼油厂烟气轮机故障诊断的现状与发展方向,石油机械,Vol. 34, No. 8, 80~81, 2006
6. 孙志林,石来德,机械故障诊断技术理论综述,专题综述,No.3, 90~93, 2004
7. 麦金森,铁路机车车辆运行故障检测诊断技术的研究与应用,中国铁路,No.3,
56~59, 2007
8. 赵荣珍,李超,机械故障智能诊断知识获取新发展问题,振动与冲击,Vol.26, No.9, 71~75, 2007
9. 杨宇,于德介,程军圣,基于 Hilbert 边际谱的滚动轴承故障诊断方法 振动与冲击,Vol.24, No.1, 41~45, 2005
10. 王文辉,刘帅,混杂系统故障诊断方法综述,系统工程与电子技术,Vol.28, No.12, 1853~1857, 2006
11. 刘建辉, 秦现生, 远程协同故障诊断综述及研究,制造技术与机床, No.2, 36~40, 2006
12. 林朝平,数控机床故障诊断技术的发展动向,新技术新工艺,No. 9, 9~11, 2003
13. 向玲,胡爱军,机械设备远程故障诊断系统的发展与实现,机床与液压,No.6, 243~245, 2006
14. 聂彩丽,赵晓顺,现代农业机械故障诊断技术的发展,农机化研究,No.9, 229~231, 2007
15. 阴妍, 鲍久圣, 机械设备状态监测及故障诊断综述,煤矿机械, No.3, 125~126, 2004
16. 于晓红,张来斌,炼油厂烟气轮机故障诊断的现状与发展方向,石油机械,Vol. 34, No. 8, 80~81, 2006
17. 聂彩丽,赵晓顺,现代农业机械故障诊断技术的发展,农机化研究,No.9, 229~231, 2007
18. 伦冠德,机械设备故障检测诊断技术现状与发展,拖拉机与农用运输车,Vol.34, No.3, 95~96, 2007
19. 董建宁,申永军,轴承故障诊断中的信号处理技术研究与展望,轴承,No.01, 43~47, 2005
20. 王祖林,周荫清,小波分析理论及其在雷达信号处理中的应用,北京航空航天大学学报,Vol.25, No.2, 130~134, 1999
21. 申永军,杨绍普,齿轮故障诊断中的信号处理技术与展望,机械传动,Vol.28, No.3, 1~6, 2004
22. P.D.McFadden&M. TOOZHY. Application of Synchronous Averaging to Vibration Monitoring of Rolling Bearings, Mechanical Systems and Signal Processing, Vol.14, No.6, 891~906, 2000
23. 徐敏等,设备故障诊断手册—机械设备状态监测和故障诊断,西安交通大学出版社,1998
24. 李洪,曲中谦,实用轴承手册,辽宁科学技术出版社,2001
25. 王德志,滚动轴承的诊断与维护,中国铁道出版社,1994
26. 杨宇,于德介,程军圣.基于 Hilbert 边际谱的滚动轴承故障诊断方法 振动与冲击,Vol.24, No.1, 41~45, 2005
27. 梅宏斌,滚动轴承振动监测与诊断理论? 方法? 系统,机械工业出版社,1995
28. 刘刚,屈梁生,应用连续小波变换提取机械故障的特征,西安交通大学学报,Vol.34, No.11, 74~77, 2000
29. 陈克兴,李川崎,设备状态监测与故障诊断技术,北京:科学技术文献出版社,1991
30. 圆柱齿轮减速器说明书,江苏省金象减速机有限公司
31. L.Cohen, Time-frequency analysis-a review, Proceedings of the IEEE, Vol.77, No.7, 941~981, 1989
32. 邹红星,周小波,时频分析:回溯与前瞻,电子学报,Vol.28, No.9, 78~84, 2000
33. 程道来,仪垂杰,基于 Wigner-ville 分布和 Wavelet 时间尺度的飞机非平稳抖杆背景声分析,机械工程学报,Vol.43, No.5, 150~155, 2007
34. 纪跃波,秦树人,基于多分辨分析的时频分析,振动与冲击,Vol.21, No.1, 12~17, 2006
35. 蒋平,贾民平,Wigner-ville 分布在机械故障诊断中的应用,制造技术与机床,No.7, 24~29, 2004
36. 刘军,张祖兴,基于短时傅立叶变换和连续小波变换的先天性心脏病心音比较分析研究,云南大学学报,Vol.28, 89~93, 2006
37. 王忠仁,林君,基于 Wigner-ville 分布的复杂时变信号的时频分析,电子学报,Vol.33, No.12, 2239~2241, 2005
38. 曹玉茹等,Wigner-ville 分布变换在全息计算中的应用,计算机工程与应用,Vol.43, No.30, 15~17, 2007
39. 陈雨红,扬长春等,几种时频分析方比较,地球物理学进展,Vol.21, No.4, 1180~1185, 2006
40. A. C. Macormick, A. K. Nandi, Cyclostationarity in rotating machine vibrations, Mechanical systems and signal processing,Vol.12, No.2, 225~242, 1998
41. L.Angrisani, P.Daponte, M.D’Apuzzo, A method for the automatic detection detection and measurement of transients. Part 1: the measurement method, Measurement Vol.25, 19~30, 1999
42. L.Angrisani, P.Daponte, M.D’Apuzzo, A method for the automatic detection detection and measurement of transients. Part 2: applications, Measurement, Vol.25, 31~40, 1999
43. Cyril Hory, Nadine Martin, Alain Chehikian, Spectrogram segmentation by means of statistical features for non-stationary signal interpretation, IEEE Transactions on signal processing, Vol.5, No.12, 2915~2925, 2002
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