齿轮箱故障特征提取技术研究
|
摘要
齿轮箱作为机械设备中一种必不可少的连接和传递动力的通用零部件,在现代工业发展中具有广泛的应用。齿轮系统工作过程中发生的齿轮断齿、点蚀、滚动轴承的疲劳剥落、轴弯曲等,都会产生周期性的脉冲冲击力,产生振动信号的调制现象,在频谱上表现为在啮合频率或固有频率两侧出现间隔均匀的调制边频带。从信号中提取调制信息,分析其强度和频次就可以判断零件损伤的程度和部位,是机械故障诊断中广泛使用的一种分析零件损伤类故障的有效方法。
针对齿轮箱振动信号的振动机理和振动特点,本文以小波变换理论和循环平稳解调理论为基础,有效地提取齿轮和轴承振动信号中的故障特征量,达到识别故障、消除故障的目的,主要进行了以下几方面的工作:
1)阐述了齿轮箱故障诊断技术的发展状况,齿轮、轴承故障振动的机理和振动特点。
2)针对齿轮箱故障诊断的应用,研究了小波分析的基本理论及在齿轮箱故障振动信号中的实际应用,成功地通过小波分析和小波包分解重构技术提取了故障信号的特征信息,为识别故障类型提供了有效的分析手段。
3)提出了基于复小波变换相位功率谱的方法。该方法从复小波变换的相位角度来提取齿轮振动信号中的故障信息。
4)研究了调幅信号的循环自相关函数的解调性能,并通过仿真证明了该解调方法的优越性。
5)在结合小波包消噪性能的基础上,提出了一种小波包-循环平稳解调法新的诊断方法并给出了分析算法。
本文对文中提出的方法进行了实验验证。实验数据的分析结果表明这些方法可突出齿轮箱的故障特征,适用于齿轮及轴承的局部故障诊断,具有重要的意义。
As a necessary part of connecting and force transmission in mechanical equipment, gearbox system play a comprehensive role, with the development of modern industry. When the gear system works, periodic impulse impact force will produce owing to the faults of gear abruption or corrosive pitting, etc. So phenomena of modulation produced at this moment and spectrum of the vibration signal has symmetrical modulation side-bands besides the meshing frequency or natural frequency. Extracted modulation information and its strength and modulation frequency order can be analyzed which can be used to judge the fault parts. It is a compressively used in mechanical fault diagnosis.
In order to effectively extract the feature vector of fault in the signals of gear and bear vibration and achieve the purposes of identifying and eliminating the faults, according to the mechanism and characteristics of gearbox vibration, the following researches on the basis of the wavelet analysis and cyclostationary demodulation:
1) The development of technology of fault diagnosis for gearbox, the mechanism and characteristics of gear and bear vibration are discussed.
2) The fundamental theory of wavelet analysis and its application are introduced on the application of fault diagnosis for gearbox. Then by means of the wavelet analysis and wavelet packet transform, the fault feature vectors of fault are successfully extracted and this effective method is employed to identify the fault pattern.
3) A power spectrum analysis method based on the phase of complex- wavelet-transform, which derives fault information from gear vibration signal by phase, is presented.
4) A new conclusion is discussed that cyclic autocorrelation function possesses demodulation capability. The superiority of the demodulation is verified by the simulation.
5) A new diagnosis and analysis method were proposed, which was wavelet packet-cyclostationary demodulation, based on the organic combination of the noise elimination ability of wavelet packet transform and cyclostationary demodulation.
Experimental results show these proposed methods, which can protrude the fault character of the gearbox, are practical in gearbox local fault diagnosis and of important meaning.
针对齿轮箱振动信号的振动机理和振动特点,本文以小波变换理论和循环平稳解调理论为基础,有效地提取齿轮和轴承振动信号中的故障特征量,达到识别故障、消除故障的目的,主要进行了以下几方面的工作:
1)阐述了齿轮箱故障诊断技术的发展状况,齿轮、轴承故障振动的机理和振动特点。
2)针对齿轮箱故障诊断的应用,研究了小波分析的基本理论及在齿轮箱故障振动信号中的实际应用,成功地通过小波分析和小波包分解重构技术提取了故障信号的特征信息,为识别故障类型提供了有效的分析手段。
3)提出了基于复小波变换相位功率谱的方法。该方法从复小波变换的相位角度来提取齿轮振动信号中的故障信息。
4)研究了调幅信号的循环自相关函数的解调性能,并通过仿真证明了该解调方法的优越性。
5)在结合小波包消噪性能的基础上,提出了一种小波包-循环平稳解调法新的诊断方法并给出了分析算法。
本文对文中提出的方法进行了实验验证。实验数据的分析结果表明这些方法可突出齿轮箱的故障特征,适用于齿轮及轴承的局部故障诊断,具有重要的意义。
As a necessary part of connecting and force transmission in mechanical equipment, gearbox system play a comprehensive role, with the development of modern industry. When the gear system works, periodic impulse impact force will produce owing to the faults of gear abruption or corrosive pitting, etc. So phenomena of modulation produced at this moment and spectrum of the vibration signal has symmetrical modulation side-bands besides the meshing frequency or natural frequency. Extracted modulation information and its strength and modulation frequency order can be analyzed which can be used to judge the fault parts. It is a compressively used in mechanical fault diagnosis.
In order to effectively extract the feature vector of fault in the signals of gear and bear vibration and achieve the purposes of identifying and eliminating the faults, according to the mechanism and characteristics of gearbox vibration, the following researches on the basis of the wavelet analysis and cyclostationary demodulation:
1) The development of technology of fault diagnosis for gearbox, the mechanism and characteristics of gear and bear vibration are discussed.
2) The fundamental theory of wavelet analysis and its application are introduced on the application of fault diagnosis for gearbox. Then by means of the wavelet analysis and wavelet packet transform, the fault feature vectors of fault are successfully extracted and this effective method is employed to identify the fault pattern.
3) A power spectrum analysis method based on the phase of complex- wavelet-transform, which derives fault information from gear vibration signal by phase, is presented.
4) A new conclusion is discussed that cyclic autocorrelation function possesses demodulation capability. The superiority of the demodulation is verified by the simulation.
5) A new diagnosis and analysis method were proposed, which was wavelet packet-cyclostationary demodulation, based on the organic combination of the noise elimination ability of wavelet packet transform and cyclostationary demodulation.
Experimental results show these proposed methods, which can protrude the fault character of the gearbox, are practical in gearbox local fault diagnosis and of important meaning.
引文
[1] 王善永.汽轮发电机组状态监测、信号分析与故障诊断理论及应用技术研究,博士学位论文,东南大学,2000.3
[2] 黄文虎,夏松波,刘瑞岩等.设备故障诊断原理、技术及应用,科学出版社,1997
[3] 陈新国.基于小波分析的齿轮故障诊断的研究,硕士学位论文,武汉科技大学,2004.5
[4] 孟涛.齿轮与滚动轴承故障的振动分析与诊断,博士学位论文,西北工业大学,2003
[5] 赵志宇.基于小波变换的滚动轴承故障诊断系统的研究与开发硕士学位论文,大连理工大学,2005.3
[6] 万良虹,柳亦兵,冯东亮.小波包分析方法在滚动轴承故障诊断中的应用,现代电力,Vol.21,No.1,Feb.2004,23-26
[7] Niemann G,Seitzinger K.Temperature Rise of Gears as an Indication of its Load Carrying Capacity, VDIZ,1971,113(2): 97-105
[8] Randall R B.New Method of Modelling GearFaults,ASMEJ of Mechanical Design,1982,104:259-267
[9] 明廷锋,张永祥,仰德标.齿轮故障诊断技术研究综述,第十届全国设备监测与诊断技术学术会议论文集,2000.05
[10] P.D.McFadden.Model for the vibration produced by a single point defect in a rolling element bearing,Journal of Sound and Vibration,1984.96:69-82
[11] C.Jame Li and S.M.Wu. Online severity assessment of bearing damage via defect sensitive resonance identification and matched filtering,Mechanical Systems and Signal Processing,1988,2(3):291-303
[12] J.P Dron,L.Rasolofondraibe and F.Bolaers.High-resolution method in vibratoryanalysis,application to ball bearing monitoring and production machine,International Journalof Solids and Structures,2001,38:4293-4313
[13] 杨江天,陈家骥,曾子平.双谱分析及其在机械诊断中的应用[J],中国机械工 程,2000,11(4):424-426
[14] 屈梁生,张海军.机械故障诊断的几个基本问题,中国机械工程,Vol.11,No.1-2,211-216,2000
[15] 程耕国,周凤星.一种基于小波分析的故障检测与诊断[J],控制与决策,2001(1).
[16] 吴湘淇.信号、系统与信号处理(下)[M],电子工业出版社,1999
[17] 史东锋,鲍明,屈梁生.小波包络分析在滚动轴承诊断中的应用[J],中国机械工程, 2000 ,11(12):1382-1385
[18] 刘玉斌,师杭军,郭伟等.小波分析在滚动轴承状态监测振动信号分析中的应用[J],煤矿机械,2001,3:63-65
[19] 陆爽,曲守平,张小辉.小波分析在轴承故障诊断中的应用,长春大学学报,2000, 10(6)
[20] 何正嘉,李富才,杜远.小波技术在机械监测诊断领域的应用现状与进展,西安交通大学学报,2001,35(5):540-545
[21] 周剑,赵明涛.基于二进小波分辨率逼近的层析三维数字化图像边缘检测研究[J],中国机械工程,1999,10(11):1242-1245
[22] 熊联欢.香农正交小波变换的 FFT 实现[J],华中理工大学学报,1998,26(8):67-69,73.
[23] S.G.Mallat.A theory for multiresolution signal decomposition of the wavelet representation,IEEE transaction on Pattern Analysis and Machine intelligence,Vo1.11,No.3,1989: 674-693
[24] S.G.Mallat.Multifrequency channel decompositions of images and wavelet models,IEEE Trans,Acoust Speech,Signal Processing,1989,11:674-693.
[25] S.G.Mallat.Singularity Detection and Processing with wavelet,IEEE Trans,Inform.Theory,1992,38(2):617-693
[26] 王明祥,宁宇蓉,王晋国.基于 Mallat 算法的一维离散小波变换的实现[J], 西北 大学学报:自然科学版, 2006 年,36,(3):364-368
[27] 陈武帆等.小波分析及其在图像处理中的应用,北京:科学出版社,2002
[28] 程耕国,周凤星.一种高速轧机故障检测系统[J],武汉科技大学学报,2003(1)
[29] 陈新国,程耕国.实用数字音频功放的设计[J],电声技术,2003(11)
[30] 徐长发,李国宽.实用小波方法[M],华中科技大学出版社,2001
[31] H.ZENG,Z.LI and X.CHEN.Gear fault diagnosis based on continuous wavelet transform,Mechanical Systems and Signal Processing,Volume 16,Issues 2-3,March 2002,Pages 447-457
[32] B.S.Yang,T.Han and J.L.An.Artkohonen neural network for fault diagnosis of rotating machinery,Mechanical Systems and Signal Processing,Volume 18,Issues 3,May 2004,Pages 645-657
[33] 陈进,姜鸣.高阶循环统计量理论在机械故障诊断中的应用[J],振动工程学报,2001,14(2):125—134
[34] 张贤达,保铮.非平稳信号分析与处理[M],北京:国防工业出版社,1999
[35] Gardner WA.Measurement of spectral correalion[J],IEEE trans on ASSP,1986,34(5):1111-1123
[36] Gardner WA.Exploiation of spectral redundancy in cyclostationary signal[J],IEEE Signal Processing Magazine,1991,8(2):14-36
[37] Gardner WA.Spooner CM.The cumulant theory of cyclostationary time-series,Part I:fundmentaion[J],IEEE Trans on Signal Processing,1994,42(2):3387-3408
[38] Spooner CM, Gardner WA.The cumulant theory of cyclostationary time-series,Part Ⅱ:development and applicatiom[J],IEEE Trans on Signal Processing,1994, 42(2): 3409-3429
[39] Mccormick AC,Nandi AK.Cyclostationarity in rotaing machine vibrations[J], Mechanical Systems and Signal Processing,1998,12:225-242
[40] Ghoho M,Swami A,Garel B.Performance analysis of cyclic statistics for estimation of harmonics in multiplicative and additive noise[J],IEEE Trans on Signal Processing,1999,47(12):3235-3249
[41] 胥用刚,何正嘉,王太勇.基于经验模式分解的包络解调技术及其应用,西安交通大学学报,2004,38(1):1169-1172
[42] L.Bouillaut and M.Sidahmed.Cyclostationary approach and bilinear approach: comparison,applications to early diagnosis for helicopter gearbox and classification method based on hocs,Mechanical Systems and Sinai Processing,2000,15(5):923-943
[43] 李力,屈梁生.二阶循环统计量在机械故障诊断中的应用[J],西安交通大学学报,2002,36(9):943-946
[44] 丁康,江利旗.解调分析在机械设备故障诊断中应用的三个局限性研究[J],汕头大学学报(自然科学版),2000,15(1):1-12
[45] 于云满,邵强,胡红英,胡萍,赵志宇.小波分析及其在轴承诊断中的应用[J],大连大学学报,2002,6:64-67
[46] 刘红星,林京,屈梁生,等.信号时域平均处理中的若干问题探讨[J],振动工程学报,1997,10(4):446-450
[47] 刘忠祥,邱阿瑞,刘玉伟.小波变换在滚动轴承故障诊断中的应用[J],机械工程学报,2003,3:44-46
[48] 陈峰,成新民.基于小波变换的信号去噪技术及实现[J], 现代电子技术, 2005,28(3):11-13
[49] Delyon B,Juditsky A, Benveniste A.Accuracy Analysis for Wavelet Approximation[J], IEEE Transactions on Neural Networks,1995, 6(2):3 20-350
[50] 张帆,丁康.平方解调分析原理及在机械信号故障诊断中的应用[J],汕头大学学报(自然科学版),2002,1(1):42-47
[2] 黄文虎,夏松波,刘瑞岩等.设备故障诊断原理、技术及应用,科学出版社,1997
[3] 陈新国.基于小波分析的齿轮故障诊断的研究,硕士学位论文,武汉科技大学,2004.5
[4] 孟涛.齿轮与滚动轴承故障的振动分析与诊断,博士学位论文,西北工业大学,2003
[5] 赵志宇.基于小波变换的滚动轴承故障诊断系统的研究与开发硕士学位论文,大连理工大学,2005.3
[6] 万良虹,柳亦兵,冯东亮.小波包分析方法在滚动轴承故障诊断中的应用,现代电力,Vol.21,No.1,Feb.2004,23-26
[7] Niemann G,Seitzinger K.Temperature Rise of Gears as an Indication of its Load Carrying Capacity, VDIZ,1971,113(2): 97-105
[8] Randall R B.New Method of Modelling GearFaults,ASMEJ of Mechanical Design,1982,104:259-267
[9] 明廷锋,张永祥,仰德标.齿轮故障诊断技术研究综述,第十届全国设备监测与诊断技术学术会议论文集,2000.05
[10] P.D.McFadden.Model for the vibration produced by a single point defect in a rolling element bearing,Journal of Sound and Vibration,1984.96:69-82
[11] C.Jame Li and S.M.Wu. Online severity assessment of bearing damage via defect sensitive resonance identification and matched filtering,Mechanical Systems and Signal Processing,1988,2(3):291-303
[12] J.P Dron,L.Rasolofondraibe and F.Bolaers.High-resolution method in vibratoryanalysis,application to ball bearing monitoring and production machine,International Journalof Solids and Structures,2001,38:4293-4313
[13] 杨江天,陈家骥,曾子平.双谱分析及其在机械诊断中的应用[J],中国机械工 程,2000,11(4):424-426
[14] 屈梁生,张海军.机械故障诊断的几个基本问题,中国机械工程,Vol.11,No.1-2,211-216,2000
[15] 程耕国,周凤星.一种基于小波分析的故障检测与诊断[J],控制与决策,2001(1).
[16] 吴湘淇.信号、系统与信号处理(下)[M],电子工业出版社,1999
[17] 史东锋,鲍明,屈梁生.小波包络分析在滚动轴承诊断中的应用[J],中国机械工程, 2000 ,11(12):1382-1385
[18] 刘玉斌,师杭军,郭伟等.小波分析在滚动轴承状态监测振动信号分析中的应用[J],煤矿机械,2001,3:63-65
[19] 陆爽,曲守平,张小辉.小波分析在轴承故障诊断中的应用,长春大学学报,2000, 10(6)
[20] 何正嘉,李富才,杜远.小波技术在机械监测诊断领域的应用现状与进展,西安交通大学学报,2001,35(5):540-545
[21] 周剑,赵明涛.基于二进小波分辨率逼近的层析三维数字化图像边缘检测研究[J],中国机械工程,1999,10(11):1242-1245
[22] 熊联欢.香农正交小波变换的 FFT 实现[J],华中理工大学学报,1998,26(8):67-69,73.
[23] S.G.Mallat.A theory for multiresolution signal decomposition of the wavelet representation,IEEE transaction on Pattern Analysis and Machine intelligence,Vo1.11,No.3,1989: 674-693
[24] S.G.Mallat.Multifrequency channel decompositions of images and wavelet models,IEEE Trans,Acoust Speech,Signal Processing,1989,11:674-693.
[25] S.G.Mallat.Singularity Detection and Processing with wavelet,IEEE Trans,Inform.Theory,1992,38(2):617-693
[26] 王明祥,宁宇蓉,王晋国.基于 Mallat 算法的一维离散小波变换的实现[J], 西北 大学学报:自然科学版, 2006 年,36,(3):364-368
[27] 陈武帆等.小波分析及其在图像处理中的应用,北京:科学出版社,2002
[28] 程耕国,周凤星.一种高速轧机故障检测系统[J],武汉科技大学学报,2003(1)
[29] 陈新国,程耕国.实用数字音频功放的设计[J],电声技术,2003(11)
[30] 徐长发,李国宽.实用小波方法[M],华中科技大学出版社,2001
[31] H.ZENG,Z.LI and X.CHEN.Gear fault diagnosis based on continuous wavelet transform,Mechanical Systems and Signal Processing,Volume 16,Issues 2-3,March 2002,Pages 447-457
[32] B.S.Yang,T.Han and J.L.An.Artkohonen neural network for fault diagnosis of rotating machinery,Mechanical Systems and Signal Processing,Volume 18,Issues 3,May 2004,Pages 645-657
[33] 陈进,姜鸣.高阶循环统计量理论在机械故障诊断中的应用[J],振动工程学报,2001,14(2):125—134
[34] 张贤达,保铮.非平稳信号分析与处理[M],北京:国防工业出版社,1999
[35] Gardner WA.Measurement of spectral correalion[J],IEEE trans on ASSP,1986,34(5):1111-1123
[36] Gardner WA.Exploiation of spectral redundancy in cyclostationary signal[J],IEEE Signal Processing Magazine,1991,8(2):14-36
[37] Gardner WA.Spooner CM.The cumulant theory of cyclostationary time-series,Part I:fundmentaion[J],IEEE Trans on Signal Processing,1994,42(2):3387-3408
[38] Spooner CM, Gardner WA.The cumulant theory of cyclostationary time-series,Part Ⅱ:development and applicatiom[J],IEEE Trans on Signal Processing,1994, 42(2): 3409-3429
[39] Mccormick AC,Nandi AK.Cyclostationarity in rotaing machine vibrations[J], Mechanical Systems and Signal Processing,1998,12:225-242
[40] Ghoho M,Swami A,Garel B.Performance analysis of cyclic statistics for estimation of harmonics in multiplicative and additive noise[J],IEEE Trans on Signal Processing,1999,47(12):3235-3249
[41] 胥用刚,何正嘉,王太勇.基于经验模式分解的包络解调技术及其应用,西安交通大学学报,2004,38(1):1169-1172
[42] L.Bouillaut and M.Sidahmed.Cyclostationary approach and bilinear approach: comparison,applications to early diagnosis for helicopter gearbox and classification method based on hocs,Mechanical Systems and Sinai Processing,2000,15(5):923-943
[43] 李力,屈梁生.二阶循环统计量在机械故障诊断中的应用[J],西安交通大学学报,2002,36(9):943-946
[44] 丁康,江利旗.解调分析在机械设备故障诊断中应用的三个局限性研究[J],汕头大学学报(自然科学版),2000,15(1):1-12
[45] 于云满,邵强,胡红英,胡萍,赵志宇.小波分析及其在轴承诊断中的应用[J],大连大学学报,2002,6:64-67
[46] 刘红星,林京,屈梁生,等.信号时域平均处理中的若干问题探讨[J],振动工程学报,1997,10(4):446-450
[47] 刘忠祥,邱阿瑞,刘玉伟.小波变换在滚动轴承故障诊断中的应用[J],机械工程学报,2003,3:44-46
[48] 陈峰,成新民.基于小波变换的信号去噪技术及实现[J], 现代电子技术, 2005,28(3):11-13
[49] Delyon B,Juditsky A, Benveniste A.Accuracy Analysis for Wavelet Approximation[J], IEEE Transactions on Neural Networks,1995, 6(2):3 20-350
[50] 张帆,丁康.平方解调分析原理及在机械信号故障诊断中的应用[J],汕头大学学报(自然科学版),2002,1(1):42-47