用户名: 密码: 验证码:
局域波分析的理论方法研究及应用
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
近年来,设备监测诊断中非平稳信号的分析一直是一个复杂而有意义的研究课题,局域波分析方法在几年的发展过程中,逐渐成为分析非平稳信号的有效方法之一。本文在总结前人研究成果基础上,结合工程实际需要,对局域波分析方法作了进一步的研究和发展,并以此为基础,在机械设备的诊断方法上进行了探索性的研究。
     针对设备监测诊断中存在的非平稳问题,引入了局域波分析方法。该方法从信号瞬时频率的角度出发,将非平稳时变信号分解成为有限个局域波分量,每一个分量描述了时变信号中不同频率和尺度范围的固有振动模式,瞬时频率可以在每一个分量中随处定义。经过Hilbert变换得到局域波时频谱能够同时提供时域和频域的信息。
     针对局域波分析方法目前的研究状况,分析了该方法中存在的问题:分解方法中的边界问题、分量的瞬时频率估计以及如何合理选择采样频率等问题。提出了基于包络均值法的改进算法;分析并验证了利用相位差分法进行瞬时频率估计的有效性和精确性;给出了进行局域波分析,信号采样频率的选择标准。
     在此基础上,研究了局域波分析的频率多分辨特性及分解的尺度滤波特性,给出了不同时频谱图的频率分辨率的计算式和滤波器的表达式。通过对加噪信号的有效去噪检验了尺度滤波的可行性。提出了基于局域波时频谱的边界谱分析,以及频带能量分析方法,并运用这些方法对旋转机械和往复机械的不同故障进行了有效的诊断。
     以一维局域波分解方法为基础,研究了二维局域波分解方法,对边界处的极值判断方法作了改进,有效的解决了插值曲面的边界摆动。制定了合理的筛选停止准则和分解停止准则。通过对图像去噪,检验了二维分解对于提取图像局域细节信息的有效性。同时,提出了基于二维局域波分解的图像诊断方法,通过对时频灰度图像的二维分解提取表征故障信息的图像细节部分,有效地实现了故障的特征提取。
     以上研究工作在一定程度上丰富和完善了局域波分析方法,诊断应用表明本文中提出的方法能够有效的识别故障,解决实际问题。
In recent years, analysis of the non-stationary signal in equipment fault diagnosis, is always a complex and significant work. With the hard research, the local wave method is gradually turned into one of the effective method to solve non-stationary problems. In this paper, based on the former achievements linking to practical project, the local wave method is deeply developed and expanded. And the fault diagnosis method on mechanical equipment is researched on the basis of former work.Local wave method is imported especially for solving non-stationary problems of the equipment diagnosis. The method, which can decompose time varying signal into several local wave functions, is based on the instantaneous frequency of signals. Every function describes different frequency and scale of the inherence oscillation mode. Instantaneous frequency can be defined everywhere in every function. By Hilbert transform, local wave time-frequency spectrum can give enough information in both time domain and frequency domain.Aimed at the research status of local wave method, the problems in this method is analysed, such as the end effect, estimate of instantaneous frequency and how to choice the sampling frequency. The way is put forward for improvement on arithmetic based on envelope mean. The validity and accuracy of phase difference method is analysed and validated. The criterion of how to choice the sampling frequency is given in local wave method.Based on the former work, the characteristic of multi-distinguish frequency analysis of local wave method and time-scale filtering is researched. The expressions of the frequency distinguish ratio in the time-frequency spectrum is given. The formula of filter can also be found in this paper. The feasibility is proved by noise canceling of signals with noise. An approach, which can be called boundary spectrum and energy of frequency belt, is proposed based on the local wave spectrum. With these methods we can find the fault in rolling machine and reciprocating machine.Two-dimensional local wave decomposition is investigated on the basis of one dimensional decomposition method. A new way to obtain the local maxima and minima at boundary is brought forward. The boundary swing problem is effectively solved. The criterions for the sifting process and decompose process to stop is also given. An examination on image de-noising is carried out. It proves that detail information of image can be obtained
    
    by two-dimensional local wave decomposition which. Image diagnosis method based on decomposition is put forward. Details of time-frequency grayer degree image with fault information can be picked up by two-dimensional decomposition. During this process, we may find the fault character.The research work mentioned above enhances the local wave method. It also proved that the methods which are introduced in the paper can effectively identify the fault and solve practical problems.
引文
[1] 何正嘉,訾艳阳,孟庆丰.机械设备非平稳信号的故障诊断原理及应用.北京:高等教育出版社,2001
    [2] 马孝江,余泊,张志新.一种新的时频分析方法—局域波法.振动工程学报,2004,13 (S):219~224
    [3] 余泊.自适应时频分析方法及其在故障诊断中的应用研究.大连理工大学博士学位论文,1998
    [4] Yu Bo, Ma Xiaojiang. A new method for the Analysis of non-stationary non-linear vibration signal and its use in machine fault diagnosis. International Conference on Vibration Engineering' 98, 1998, 8
    [5] 盖强.局域波时频分析方法的理论研究与应用.大连理工大学博士学位论文,2001
    [6] 黄文虎,夏松波,刘瑞岩.设备故障诊断原理、技术及应用:科学出版社,1996
    [7] 虞和济,韩庆大,李沈.设备故障诊断工程.北京:冶金工业出版社,2001
    [8] 王琳.机械设备故障诊断与监测的常用方法及其发展趋势.武汉工业大学学报,2000,22 (3):62~64
    [9] P. W. Hills. Vibration-based Condition Monitoring-the Learning Issue. Insight, 1996, 38 (8) : 576~579
    [10] Rothberg SJ, Halliwell NA. Vibration Measurements on Rotating Machinery Using Laser Doppler Velocimeter. Trans ANSE J of Vibration and Acoustics, 1994, 116 (3) : 326~331
    [11] 黄昭毅.两年来国内设备诊断技术的某些发展特点及对若干问题的探索与思考.全国设备诊断技术学术会议—97论文集:1997
    [12] L.科恩著,白局宪译.时—频分析:理论与应用.西安:西安交通大学出版社,1998
    [13] D. Gabor. Theory of Communication. J Inst Elec Eng, 1946, 93: 429~457
    [14] R K, K DH, Y LL. The sound spectrograph. J. Acoust. Soc, 1946, 18: 19~49
    [15] K PR, G K, C GH. Visible speech. Van Nostrand. New York: 1947
    [16] Ville J. Theorie et applications de la notion de signal analytique. Cables et Transmissions, 1948, vol (2A) : 61~74
    [17] E. P. Wigner. Physical Review. 1932, 40: 749~759
    [18] 邹红星,周小波,李衍达.时频分析:回溯与前瞻.电子学报,2000,28(9):78~84
    [19] 郑建明,李言,肖继明.伸缩窗口短时Fourier分析.振动、测试与诊断,2002,20(4):254~258
    [20] Morlet J. Wave propation and sampling theory and complex waves. Geophysics, 1982, 47 (2) : 222~236
    
    [21] 李建平等.小波分析与信号处理-理论、应用及软件实现.重庆:重庆出版社,1997
    [22] N. E. Huang, Z. Shen, S. R. long, Wu MC, Shih HH, Zheng Q, et al. The Empirical Mode Decomposition and The Hilbert Spectrum for Nonlinear Non-stationary Time Series Analysis. Proc. Royal Society. London: 1998. 903~995
    [23] N. E. Huang, Z. Shen, S. R. long. A New View of Nonlinear Water Waves: The Hilbert Spectrum. Annu. Rev. Fluid Mech., 1999 (31) : 417~457
    [24] Flandrin P. Empirical Mode Decomposition as a Filter Bank. IEEE SIGNAL PROCESSING LETTERS, 2003
    [25] 谭善文,秦树人,汤宝平.Hilbert—Huang变换的滤波特性及其应用.重庆大学学报,2004,27(2):9~12
    [26] Wu Z, Huang NE. A Study of the Characteristics of White Noise Using the Empirical Mode Decomposition Method. 2003
    [27] 邓拥军,王伟,钱成春,王忠,戴德君.EMD方法及Hilbert变换中边界问题的处理.科学通报,2001,46(3):257~268
    [28] 熊学军,郭炳火,胡筱敏,刘建军.EMD方法和Hilbert谱分析法的应用与探讨.黄渤海海洋,2002,20(2):12~21
    [29] 杨世锡,吴昭同,严拱标.旋转机械振动信号基于EMD的HT和STFT时频分析比较.汽轮机技术,2002,44(6):336~338
    [30] 钟佑明,秦树人,汤宝平.Hilbert-Huang变换中的理论研究.振动与冲击,2002,21(4):13~17
    [31] Rilling G, Flandrin P, Goncalves P. On Empirical Mode Decomposition and its Algorithms. 2003
    [32] 陈忠,郑时雄.EMD信号分析方法边缘效应的分析.数据采集与处理,2003 (1):114~118
    [33] 刘慧婷,程家兴,张星.利用Hilbert变换提取信号瞬时特征的算法实现.微机发展,2003,13 (6):82~85
    [34] 罗奇峰,石春香.Hilbert-Huang变换理论及其计算中的问题.同济大学学报,2003,31 (6):637~640
    [35] 石春香,罗奇峰.时程信号的Hilbert-Huang变换与小波分析.地震学报,2003,25 (4):398~405
    [36] 赵犁丰,张晓亮,宋洁.利用EMD方法和小波变换进行信号奇异性检测.青岛海洋大学学报,2003,33 (5):759~763
    [37] Chenl C-H, Li C-P, Teng T-L. Surface—Wave Dispersion Measurements Using Hilbert—Huang Transform. TAO, 2002, 13 (2) : 171~184
    [38] P. J. Oonincx. Empirical Mode Decomposition: A New Tool for S-Wave Detection. In: REPORT PNA-R0203; 2002. p. 1~16
    [3
    
    [39] Zhang RR. HHT-BASED CHARACTERIZATION OF SOIL NONLINEARITY AND LIQUEFACTION IN EARTHQUAKE RECORDINGS. 2003
    [40] Zhang RR, Larner K. Rationale of HHT Data Processing for Studies of Seismology and Earthquake Engineering. 2003
    [41] Liu R. Empirical Mode Decomposition: A useful technique for neuroscience. Computational Journal Club, 2002
    [42] Chang FK. Damage Detection Using Empirical Mode Decomposition Method and a Comparison with Wavelet Analysis. Signal Processing and Diagnostic Methods: Structural Health Monitoring, 2000: 891~900
    [43] Zhong C, Yan-ming ZS-xS. Gearbox Vibration Recognition Using Empirical Mode Decomposition Method. Journal of the South China University of Techonlogy (Natural Science Edition), 2002, 30 (9) : 61~64
    [44] 韩海明,沈涛虹,宋汉文.工况模态分析的EMD方法.振动与冲击,2002,21 (4):69~72
    [45] 余德介,程军圣.EMD方法在齿轮故障诊断中的应用.湖南大学学报(自然科学版),2002,29(6):48~51
    [46] 赵犁丰,王振芬,张晓亮.基于经验模式分解的希尔伯特变换包络提取在机械故障诊断中的应用.青岛海洋大学学报,2002,36 (2):965~970
    [47] 陈忠,郑时雄.基于经验模式分解(EMD)的齿轮箱齿轮故障诊断技术研究.振动工程学报,2003,16 (2):229~232
    [48] 胡劲松,杨世锡,吴昭同,严拱标.基于EMD的旋转机械振动信号Winger分布分析.机床与液压,2003 (5):237~239
    [49] 杨世锡,胡劲松,吴昭同,严拱标.旋转机械振动信号基于EMD的希尔伯特变换和小波变换时频分析比较.中国电机工程学报,2003,23 (6):102~107
    [50] 于德介,程军圣,杨字.Hilbert能量谱及其在齿轮故障诊断中的应用.湖南大学学报(自然科学版),2003,30 (4):47~50
    [51] 胡劲松,杨世锡.基于HHT的转子横向裂纹故障诊断.动力工程,2004,24 (2):218~221
    [52] 杨宇,于德介,程军圣.基于Hilbert—Huang变换的特征能量法及其在滚动轴承故障诊断中的应用.计算机工程与应用,2004 (10):6~8
    [53] E. Huang N, Wu M-L, Qu W, R. Long S, P. Shen SS. Applications of Hilbert□Huang transform to non-stationary financial time series analysis. Appl. Stochastic Models Bus. Ind. , 2003, 361 (19) : 245~268
    [54] 岳焕印,郭华东,韩春明,李新武,王长林,范典.经验模态分解技术在SAR干涉图滤波中的应用.高技术通讯,2001 (12):37~40
    
    [55] 韩春明,郭华东,王长林.利用经验模态分解方法抑制SAR斑点噪声.遥感学报,2002,6(4):266~271
    [56] 岳焕印,郭华东,韩春明,李新武,王长林.噪声条件下的干涉SAR相位解缠.测绘学报,2002,31 (2):151~156
    [57] 韩春明,郭华东,王长林,范典,桑会勇.基于EMD方法的多尺度边缘提取.高技术通讯,2003(6):13~17
    [58] 张贤达,保铮.非平稳信号分析与处理.北京:国防工业出版社,1998
    [59] 盖强,马孝江,张海勇,邹岩岜.几种局域波分解方法的比较研究.系统工程与电子技术,2002,24 (2):57~59
    [60] 盖强,马孝江,张海勇,邹岩崑.一种消除局域波法中边界效应的新方法.大连理工大学学报,2002,42(1):115~117
    [61] 张海勇.基于局域波法的非平稳随机信号分析中若干问题的研究.大连理工大学博士学位论文,2001
    [62] 张海勇,马孝江,盖强.一种新的时频分析方法.火力与指挥控制,2000,25 (3):39~42
    [63] L. Cohen. Time-Frequency Analysis. NJ: Prentice-Hall, Englewood Cliffs, 1995
    [64] S. Haykin. Neural networks expand SPs horizons. IEEE Signal Processing Magazine, 1996, 13: 24~29
    [65] 孙云岭,朴甲哲,张永祥.Wigner-Ville时频分布在内燃机故障诊断中的应用.中国机械工程,2004,15 (6):505~507
    [66] L. Cohen. Generalized phase-space distribution functions. Jour. Math. Phys, 1966, vol. 7: 781~786
    [67] K. Kodera. Appl. Comp. Harm. Anal. 1976, 3 (1) : 10~39
    [68] K. Kodera. IEEE Trans. ASSP, 1986, ASSP: 34: 64~76
    [69] F. Auger. IEEE Trans. SP, 1995, 43 (5) : 1068~1089
    [70] R. G. Baraniuk. Signal Processing, 1993, 32 (6) : 263~284
    [71] S. Qian, D. Chen. Signal Processing, 1994, 36 (1) : 1~11
    [72] S. Mallat, Z. Zhang. IEEE Trans. SP, 1993, 41 (12) : 3397~3415
    [73] 邹红星等.在不同特性噪声背景下Dopplerlet变换在信号恢复中的应用.电子学报,2000,28 (9):1~4
    [74] 邹红星,周小波,李衍达.采用Dopplerlet基函数的时频信号表示.清华大学学报(自然科学版),2000,40 (3):55~58
    [75] S. Mann, S. Haykin. Vision Interface. 1991 (6) : 3~7
    [76] O. Mihovilovic. Electron. Lett, 1991, 27 (13) : 1159~1161
    [77] S. Mann. IEEE Trans. SP, 1995, 43 (11) : 2745~2761
    
    [78] R. Baraniuk. Wigner-based formulation of the chirplet of the chirplet transform. IEEE Trans. SP, 1996, 44 (12) : 3129~3135
    [79] 殷勤业,倪志芳,钱世锷,陈大庞.自适应旋转投影分解法.电子学报,1997,25 (4):52~58
    [80] A. Bultan. A four-parameter atomic decomposition of chirplets. IEEE Trans. SP, 1999, 47 (3) : 731~745
    [81] 孟庆丰,屈梁生.Wigner分布及其在机械故障诊断中的应用.信号处理,1990,6 (3):155~162
    [82] Q. Meng, L. Qu. Rotating machinery fault diagnosis using wigner distribution. Mechanical Systems and Signal Processing, 1991, 5 (3) : 155~166
    [83] 孟庆丰,蒋晓玲,何正嘉,赵纪元.滚动轴承和齿轮故障的时频域识别.重型机械,1998(1):57~60
    [84] 张桂才,沈玉娣,屠荣富.齿轮疲劳裂纹特征及诊断方法.机械传动,1994,18(4):21~24
    [85] 陈章位,路甬祥.Wigner谱在往复式机械监测中的应用.机械科学与技术,1994,49 (1):98~102
    [86] K Mor ea. Prediction of spalling on a ball bearing by applying the discrete wavelet transform to vibration signals. Wear, 1996, 195: 162~168
    [87] 林京,屈梁生.基于连续小波变换的信号检测技术与故障诊断.机械工程学报,2000,36(12):95~100
    [88] 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.中国机械工程,2000,11(12):1382~1385
    [89] 贺银芝,沈松,应怀僬,刘正士.小波包分解及其能量谱在发动机连杆轴承故障诊断中的应用.振动工程学报,2001,14 (1):72~75
    [90] 刘献栋,李其汉.小波变换在转子系统动静件早期碰磨故障诊断中的应用.航空学报,1999,20 (3):220~223
    [91] 高强,何正嘉.谐波小波及其时频解剖面图在旋转机械诊断中的应用.西安交通大学学报,2000,34 (9):62~66
    [92] 刘世元,杜润生,杨叔子.基于小波包分析的内燃机振动诊断方法研究.华中理工大学学报,1999,27 (8):7~9
    [93] 伍学奎,陈进,周秩尘.基于小波包变换的内燃机气阀漏气诊断方法.振动工程学报,2000,13 (2):210~215
    [94] 姜万录,张淑清,王益群.液压泵故障的小波变换诊断方法.机械工程学报,2001,37 (6):34~37
    [95] 邹岩崑,马孝江.局域波法的时频分析及应用.机床与液压,2003,184 (4):190~192
    
    [96] 李宏坤,马孝江等.局域波法在船舶柴油机燃油系统故障诊断中的应用.大连理工大学学报,2003,43 (2):168~171
    [97] 王珍,马孝江,李吉.基于振动信号的柴油机故障诊断方法研究.农业机械学报,2003,34 (6):18~21
    [98] 王珍,马孝江.局域波时频分析在缸套活塞磨损诊断中的应用研究.内燃机学报,2002,20(2):157~160
    [99] 王珍,马孝江.局域波边界谱在缸盖振动信号分析中的应用研究.内燃机工程,2002,23 (3):50~53
    [100] 邹岩崑,马孝江,朱泓,蔡悦,张志新.局域波法在柴油机气缸磨损故障诊断中的研究.中国机械工程,2004,20 (15):1811~1814
    [101] 邹岩崑,马孝江,蔡悦,张志新.基于局域波法的柴油机缸套活塞磨损故障诊断.起重运输机械,2004 (2):35~37
    [102] 王奉涛,马孝江,邹岩崑,张志新.基于局域波神经网络的柴油机故障诊断方法.农业机械学报,2004,35 (3):24~27
    [103] 王凤利,马孝江.局域波法分形动力学在旋转机械故障诊断中的应用.农业机械学报,2003,34 (6):18~21
    [104] 王凤利,马孝江.局域波法在转子系统多故障诊断中的应用研究.热能动力工程,2003,104(2):139~142
    [105] 赵纪元,何正嘉,孟庆丰等.小波包—自回归谱分析及在振动诊断中的应用.振动工程学报,1995,8 (3):198~203
    [106] He Zhengjia ea. Wavelet transform in tandem with autoregressive technique for monitoring and diagnosis of machinery. Chinese Journal of Mechanical Engineering (English Edition), 1996, 9 (4) : 311~317
    [107] 张振仁,石林锁,王成栋等.基于小波分析和时序分析的柴油机气缸压力识别.内燃机学报,1999,17 (2):136~139
    [108] 李宏坤,马孝江,王珍.基于小波K-L信息量柴油机故障诊断方法的研究.农业机械学报,2004,35 (2):138~141
    [109] 夏勇,尚斌梁,张振仁等.基于小波包与图像处理的内燃机故障诊断研究.内燃机学报,2001,19 (1):62~68
    [110] 何正嘉,赵纪元,何毅斌等.小波分形技术及其工程应用.全国设备诊断技术学术会议97论文集:1997.115~119
    [111] 訾艳阳,何正嘉,张周锁.小波分性技术及其在机械设备非平稳故障诊断中的应用.西安交通大学学报,2000,34 (9):82~87
    [112] 赵纪元,何正嘉,孟庆丰等.基于小波包特征提取的模糊诊断网络建立及应用.振动与冲击, 1997,16 (3):30~34
    [1
    
    [113] 赵纪元,何正嘉,孟庆丰等.小波包模糊聚类诊断网络建立及应用.西安交通大学学报,1998,32 (2):15~20
    [114] 王珍,马孝江.基于局域波相空间往复机械故障诊断方法的应用研究.机床与液压,2003(2):237~239
    [115] 王珍,马孝江.局域波关联维数在柴油机故障诊断中的应用研究.内燃机学报,2003,21(2):183~186
    [116] 孟庆丰等.匹配跟踪信号分解与往复机械故障特征提取技术研究.西安交通大学学报,2001,35 (7):696~699
    [117] 袁小宏,史东峰.奇异值分解技术在齿轮箱故障诊断中的应用研究.化工机械,1997,24(6):324~327
    [118] 刘献栋,杨绍普等.基于奇异值分解的突变信息检测新方法及其应用.机械工程学报,2002,38 (6):102~105
    [119] 张子瑜,陈进,史习智,吴镇杨.径向高斯核函数时频分布及在故障诊断中的应用.振动工程学报,2001,14 (1):53~59

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700