基于统计量的潜油电泵机组状态评估方法研究
|
摘要
潜油电泵是一种大排量、高扬程的无杆抽油设备,是油田实现高产稳产的重要手段,目前,潜油电泵在我国各油田应用极为广泛。然而,潜油电泵工作环境恶劣、造价极其昂贵,一旦发生故障,将带来巨大的经济损失,因此,开展潜油电泵机组质量可靠性研究具有重要的现实意义。
本文通过对大量潜油电泵机组失效数据的统计分析,选择了机组易发生故障的主要部位为测试对象,在结合现有实验设备及现场条件的基础上,运用先进的振动测试方法,制定了试验井中潜油电泵机组振动检测方案,并采集了大量机组实验数据。
本文引入了以概率统计为基础的现代信号分析与处理方法——统计量理论,通过仿真,对其开展了从低阶统计量到高阶统计量、一般统计量到循环统计量的全面系统研究,分析了各种统计量的重要特性,并将其应用于潜油电泵机组振动状态评估中。
本文利用峰-峰值、有效值等统计量具有在时域上描述振动信号幅值大小的特性,依据概率统计理论中的“3σ”原则,制订了适合于潜油电泵机组振动相对标准。还利用功率谱统计量具有在频域上描述振动信号能量大小的特性,对潜油电泵机组进行了振动状态的评估,提取了不同状态下的机组频谱特征。最后还利用双谱、双相干谱、循环均值、循环谱密度以及循环双谱等高阶统计量和循环统计量来提取机组状态特征。结果表明:循环统计量相比于一般统计量、高阶统计量相比于低阶统计量而言,具有分辨率更高、包含信息更丰富等优点,更能准确有效的表征潜油电泵机组的状态特征,但是,它们也具有计算更复杂、物理意义更模糊等缺点,因此很难制定统一可行的潜油电泵振动评估标准。
最后,根据现场实际需要,结合本文的主要研究内容,运用Matlab丰富的函数工具箱以及VB简便的可视化编程语言,开发了潜油电泵机组振动检测与状态评估系统,通过现场实际测试,取得了良好的应用效果,证明了该系统的可靠性。
ESP (electric submersible pump) is a kind of large displacement, high-head and no pole oilpumping equipment. It is one of the most important methods for making high and steadyproduction. At recent years, the ESP is very popular in each oilfield of our country. However, itsworking condition is atrocious and its cost is expensive. Once some key part exist failure, it willoccur considerable economy losses. Therefore, it has a very important practical significance totake research on the ESP unit quality reliability.
By analyzing a large amount of the ESP unit failure data, the paper selects the mainpositions of the easily damaged as testing object. Combining with existing lab equipments,using advanced modern testing technique, research of vibration detection for the ESP unit intest-well are taken. Moreover, plenty of experiment data for the ESP unit are collected.
The statistic theory, which is based on the probability and stat., is introduced in this paper.Systemic research that from low statistic to high statistic, from general statistic to cyclic statisticis taken based on the simulation results. The important characters of each statistic are analyzedand it is applied into the vibration state assessment for the ESP unit.
Peak-peak value statistic and virtual value statistic can describe the amplitude in timedomain, so they are used for founding the relative vibration standard for the ESP unit accordingto the “3σ” principle of the probability and stat. theory. Power spectrum statistic can describe theamplitude in frequency domain, so they are used for assessing the vibration state for the ESPunit and the characters under different state are extracted. At last, bispectrum statistic,bicoherence spectrum statistic, cyclic mean statistic, cyclic spectrum density and cyclicbispectrum are also used for extracting the states for the ESP unit. The result demonstrate thatthe cyclic statistic and the high-order statistic have better resolution and include more usefulinformation than the general statistic and the low-order statistic correspondingly, so it can detectfault feature of the ESP unit more accurately and effectively. But its evaluation is still morecomplicated and the physical meaning is fuzzier, so it is difficult to formulate a uniformvibration assessment standard for the ESP unit.
Finally, acorrding to the practical need of field and combining with the main researchcontents of this paper, the software system of vibration detection and state assessment for theESP unit is developed by using the abundant function tool box of MATLAB and the simplelanguage of VB. By the local test, well application effect has been gained and reliability ofsystem is verified.
本文通过对大量潜油电泵机组失效数据的统计分析,选择了机组易发生故障的主要部位为测试对象,在结合现有实验设备及现场条件的基础上,运用先进的振动测试方法,制定了试验井中潜油电泵机组振动检测方案,并采集了大量机组实验数据。
本文引入了以概率统计为基础的现代信号分析与处理方法——统计量理论,通过仿真,对其开展了从低阶统计量到高阶统计量、一般统计量到循环统计量的全面系统研究,分析了各种统计量的重要特性,并将其应用于潜油电泵机组振动状态评估中。
本文利用峰-峰值、有效值等统计量具有在时域上描述振动信号幅值大小的特性,依据概率统计理论中的“3σ”原则,制订了适合于潜油电泵机组振动相对标准。还利用功率谱统计量具有在频域上描述振动信号能量大小的特性,对潜油电泵机组进行了振动状态的评估,提取了不同状态下的机组频谱特征。最后还利用双谱、双相干谱、循环均值、循环谱密度以及循环双谱等高阶统计量和循环统计量来提取机组状态特征。结果表明:循环统计量相比于一般统计量、高阶统计量相比于低阶统计量而言,具有分辨率更高、包含信息更丰富等优点,更能准确有效的表征潜油电泵机组的状态特征,但是,它们也具有计算更复杂、物理意义更模糊等缺点,因此很难制定统一可行的潜油电泵振动评估标准。
最后,根据现场实际需要,结合本文的主要研究内容,运用Matlab丰富的函数工具箱以及VB简便的可视化编程语言,开发了潜油电泵机组振动检测与状态评估系统,通过现场实际测试,取得了良好的应用效果,证明了该系统的可靠性。
ESP (electric submersible pump) is a kind of large displacement, high-head and no pole oilpumping equipment. It is one of the most important methods for making high and steadyproduction. At recent years, the ESP is very popular in each oilfield of our country. However, itsworking condition is atrocious and its cost is expensive. Once some key part exist failure, it willoccur considerable economy losses. Therefore, it has a very important practical significance totake research on the ESP unit quality reliability.
By analyzing a large amount of the ESP unit failure data, the paper selects the mainpositions of the easily damaged as testing object. Combining with existing lab equipments,using advanced modern testing technique, research of vibration detection for the ESP unit intest-well are taken. Moreover, plenty of experiment data for the ESP unit are collected.
The statistic theory, which is based on the probability and stat., is introduced in this paper.Systemic research that from low statistic to high statistic, from general statistic to cyclic statisticis taken based on the simulation results. The important characters of each statistic are analyzedand it is applied into the vibration state assessment for the ESP unit.
Peak-peak value statistic and virtual value statistic can describe the amplitude in timedomain, so they are used for founding the relative vibration standard for the ESP unit accordingto the “3σ” principle of the probability and stat. theory. Power spectrum statistic can describe theamplitude in frequency domain, so they are used for assessing the vibration state for the ESPunit and the characters under different state are extracted. At last, bispectrum statistic,bicoherence spectrum statistic, cyclic mean statistic, cyclic spectrum density and cyclicbispectrum are also used for extracting the states for the ESP unit. The result demonstrate thatthe cyclic statistic and the high-order statistic have better resolution and include more usefulinformation than the general statistic and the low-order statistic correspondingly, so it can detectfault feature of the ESP unit more accurately and effectively. But its evaluation is still morecomplicated and the physical meaning is fuzzier, so it is difficult to formulate a uniformvibration assessment standard for the ESP unit.
Finally, acorrding to the practical need of field and combining with the main researchcontents of this paper, the software system of vibration detection and state assessment for theESP unit is developed by using the abundant function tool box of MATLAB and the simplelanguage of VB. By the local test, well application effect has been gained and reliability ofsystem is verified.
引文
[1] 师世刚等编著.潜油电泵采油技术[M].北京:石油工业出版社,1993.50~67
[2] 李洪周,朱法银,邹积举.潜油电泵振动故障分析及振动模型[J].石油机械,1999,25(12):24~26
[3] 席文厚,朱善正,李勇梅.斜井用潜油电泵机组的研制及应用[J].石油机械,2000,28(4):35~37
[4] Graham Anderson,梁保伟,梁保升.海上潜油电泵采油新技术的成功应用[J].国外油田工程,2001,17(9):28~30
[5] 杨玉民,贺明华.在射孔层下使用电潜泵[J].国外石油机械,1998.8,9(4):42~43
[6] 杨元建,张艳秋,路江安.潜油电泵在油田注水中的应用[J].油气田地面工程,1997.3,16(2):7~8
[7] 春刚.双流电潜泵和井下油水分离器[J].石油机械,2000,28(3):57
[8] 梁明熙,杜滔.定向井双油管及潜油电泵完井技术[J].西部探矿工程,1994.1,6(1):28~31
[9] 李维兰.潜油电泵机组关键件——“电缆头”可靠性与环境应力[J].环境技术,1994,2:28~30
[10] 冯耀忠,袁英,李继康.电潜泵用的调频电机[J].国外石油机械,1998.6,9(3):46~48
[11] 夏华.改进型电潜泵 AC 变频电驱动装置[J].石油机械,1999,5:56
[12] 李振智,唐周怀,龚兴云,汪金周,张素敏.变频器在潜油电泵井上的应用[J].钻采工艺,2001,24(3):45~47
[13] 李武生.变频装置在潜油电泵井的应用[J].油气田地面工程,1999.7,18(4):21~22
[14] 张玉斌,于海春,周平.电潜泵机组可靠性评定[J].石油机械,2003,31(5):6~9
[15] 邹积举,胡再杰,李洪周.潜油电泵联接螺栓的可靠性设计[J].油田设备,1998,27(5):24~27
[16] 朱宗元,李邦俊,李玉青.潜油电泵轴断裂失效分析[J].理化检验-物理分册,2000.1,36(1):34~36
[17] 梁宗红,黄三弥.振动测试技术在旋转机械故障诊断中的应用[J].工业科技,2004,33(1):45~46
[18] 郭向前. 设备振动诊断技术初步(七)——第五讲 振动测试技术[J].设备管理与维修,1994,4:80~82
[19] 黄长艺,严普强.机械工程测试技术基础[M].机械工业出版社,2001.1:2~3
[20] 武和雷.集成智能故障诊断策略及其应用研究[M].浙江大学博士学位论文,2003.12:3
[21] 张贤达.现代信号处理[M].北京:清华大学出版社,1995
[22] 孟庆丰等.数字滤波在机械故障诊断方法中的应用技术[J].动态分析与测试技术,1994,4:5~10
[23] 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,2001.6,14(2):125~134
[24] J.R. Fonolosa and C.L. Nikias,“Wigner Higher order Moment Spectra:Definition,Properities , Computation and Application to Transient Signal Analysis ”, IEEE Trans.Signal Processing.1993,41:245~266.
[25] C.L.Nikias and M.R.Raghuveer,“Bispectrum Estimation:A Digital Signal Processing framework”,Proc.IEEE,1987,75:869~891
[26] G.B.Gianaakis,“Cumulants:A Powerful tool in Signal Processing”,Proc.IEEE,1987,75:1333~1334
[27] R.W. Barker,G.A. Klute and M.J. Hinich,“Monitoring Rotaing Tool wear Using High Order Spetral Features”Transactions of the ASME:J.Engineering for Industry,1993,115:23~29
[28] J.W.A. Fcakrell,P.R. White,J.K. Hammond and R.J. Pinnington,“The Interpretation of the Bispectra of Vibration Signal-Ⅰ. Theory”,Mechanical System and Signal Processing,Mar.1995,257~266
[29] J.W.A. Fcakrell,P.R. White,J.K. Hammond and R.J. Pinnington,“The Interpretation of the Bispectra of Vibration Signal-Ⅱ. Experimental Result and Applications”,Mechanical System and Signal Processing,Mar.1995,257~266
[30] 张春梅,王尚锦,张太镒,朱长新.时频分析在旋转机械状态监测及故障诊断中的应用[J].工程热物理学报,2002.3,23(2):187~189
[31] 张贤达.非平稳信号分析与处理[M].北京:国防工业出版社,1998,1~2
[32] T.A.C.M. Classen and W.F.G. Mecklenbrauker,“The Wigner Distribution-A Tool for Time-Frequency Signal Analysis,part Ⅰ,Ⅱ,Ⅲ”,Philips Res.J,1980,35:217~250
[33] Y. Meyer,Wavelets algorithms and applications,Chapter 2:Wavelet from a historical perspective,Society for Industrial Applied Mathematics,1993
[34] Y. Meyer , Wavelets and applications. Proceedings of the Intermational Conference,Marseiile,France,1989
[35] A. Grossman,J. Morlet.Decomposition of hardy function into square integrable wavelets of constant shape. SLAM J. MATH. ANAL,1984,15(4):723~736
[36] A. Grossman , J. Morlet.Transforms associated to square integrable group representations,Ⅰ:general results. J. MATH. Phys,1985,26(10):2473~2479
[37] I. Daubechies,Orthonormal bases of compactly supported wavelet,Comm.On Pure and Appl.Math,1988,41:909~996
[38] I. Daubechies,The wavelet transform,time-frequency localization and signal analysis,IEEE Trans,1990,IT-36:961~1005
[39] I. Daubechies,Ten lectures on wavelets,SIAM.Philadelphia,Pennsyvania,1992
[40] I. Daubechies,Orthonormal bases of compactly supported wavelet,Ⅱ.Variation on a theme,SIAM J.Math.Anal,1993,24:499~519
[41] I. Daubechies,Orthonormal bases of compactly supported wavelet,Ⅲ.Better frequency resolution,SIAM J.Math.Anal,1993,24:520~527
[42] S. Mallat,A theory of multiresolution signal decomposition:the wavelet transform,IEEE Trans.Pattern Anal.Machine Intell,1989,11(7):674~693
[43] S. Mallat,Multi-frequency channel decompositions of images and wavelet models,IEEE Trans.ASSP,1989,37(12):2091~2110
[44] S. Mallat,W.L.Huang.Singularity detection and processing with wavelets,IEEE Trans.Information Theory,1992,38(2):617~643
[45] S. Mallat,S.Zhong,Characterization of signals from multiscal edges,IEEE Trans.Pattern Anal.Machine Intell,1992,14(7):710~732
[46] W.J. Wang and P.D. McFadden,“Application of Orthogonal Wavelets to early gear damage dection”,Mechanical System and Signal Processing,1995.5,9:497-507
[47] W.J. Wang and P.D. McFadden,“Application of wavelets to gearbox vibration signals for fault detection”,Journal of Sound and vibration,1996.5:927-939
[48] Y. Wu and R. Du,“Feature extraction and assement using wavelet packets for monitoring of maching processes”,Mechanical System and Signal Processing,1996.10:29~53
[49] 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[J].机械工程学报,2000,36(12):95~100
[50] 刘刚,屈梁生.应用连续小波变换提取机械故障的特征[J].西安交通大学学报,2000,36(12):95~100
[51] 林京,屈梁生.基于连续小波变换的奇异性检测与故障诊断[J].振动工程学报,2000,13(4):523~530
[52] 陈涛,屈梁生.多分辨小波网络的理论及应用[J].中国机械工程,1997,8(2):57~59
[53] 陈涛,屈梁生.小波分析及其在机械诊断中的应用[J].机械工程学报,1997,33(3):76~79
[54] 耿中行,屈梁生.小波包的移频算法与振动信号处理[J].振动工程学报,1996,9(2):145~152
[55] 王建忠.小波理论及其在物理和工程中的应用[J]数学进展,1992,21(3):289~793
[56] 邓东皋.小波分析.数学进展[J],1991,20(3):294~310
[57] 焦李成.保铮.子波理论与应用:进展与展望[J].电子学报,1993,21(7):91~96
[58] Norden E. Huang,Zheng Shen,Steven R Long,etal. The empirical mode decomposition and the Hibert spectrum for nonlinear and non-stationary time series analysis[C].Proc.R.Soc.Lond.A.1998:903~995
[59] Better Algorithms for Analyzing Nonlinear,Nonstaitionary Data.http://tco.gsfc.nasa.gov
[60] 胡劲松,杨世锡.基于 HHT 的转子横向裂纹故障诊断[J].动力工程,2004.4,24(2):218~221
[61] Loh CH,etal.Application of the empirical mode decomposition Hibert spectrum method to identify near-fault ground-motion characteristics and structural responses[J].Bulletin of the Seismological Society of America,2001,(91):1339~1357
[62] Vasudevan K,etal.Empircal mode skeletonization of deep crustal seismic data:Theory and applications[J].Journal of Geophysical Research-solid Earth,2000,(105):7845~7856
[63] Echeverria JC,etal.Application of empirical mode decomposition to heart rate variability analysis[J]. Medical & Biological Engineering & Computing,2001,(39):471~479.
[64] 胡劲松,杨世锡.基于 HHT 的转子冲临界过程分析[J].汽轮机技术,2004.6,46(3):196~198
[65] 胡劲松,杨世锡.基于 HHT 的旋转机械故障诊断方法研究[J].动力工程,2004.12,24(6):845~851
[66] 于德介,程军圣,杨宇.Hilbert 能量谱及其在齿轮故障诊断中的应用[J].湖南大学学报,2003.8,30(4):47~50
[67] 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[J].计算机工程与应用,2004,10:6~8
[68] 杨宇,于德介,程军圣.基于 Hilbert-Huang 边际谱的滚动轴承故障诊断方法[J].振动与冲击,2005,24(1):70~72
[69] Gardner W A. Statistical spectral analysis:A nonprobabilistic theory.Englewood Cliffs,NJ:Prentice-Hall,1987
[70] Gardner W A. Exploitation of spectral redundancy in cyclostaionary signals.IEEE Signal Processing Mag,1991.8,8:14~36
[71] Gardner W A(Ed.). Cyclostationary in communication and signal processing.New York.IEEE,1994
[72] Gardner W A,Brown W A.Fraction-of time probability for time-series that exhitbit cyclostationarity.Signal Processing,1991,23:273~292
[73] Gardner W A,Spooner C M. The cumulnt theory of cyclostionary time-series,Part Ⅰ:Foundation.IEEE Trans on Signal Processing,1994,42(12):3387~3408
[74] Spooner C M,Gardner W A. The cumulnt theory of cyclostionary time-series,Part Ⅱ:Development and application.IEEE Trans on Signal Processing,1994,42(12):3409~3429
[75] 毛用才,保铮.复循环平稳的非平稳信号的非参数谱估计[J].电子科学学刊,1996.11,18(6):574~581
[76] 毛用才,保铮.应用循环平稳方法对实测雷达数据的分析[J].西安电子科技大学学报,1997.9,24(3):319~323
[77] 于宏毅,保铮.一类循环加权子空间拟合法的性能分析[J].中国科学(E 辑),1998.12,28(6):513~519
[78] 毛用才,保铮.估计时变幅值复线性调频信号的循环平稳方法及其统计性能分析[J].电子学报,1999.4,27(4):135~136
[79] 于宏毅,保铮.平稳过程循环相关处理的有限数据消失特性[J].西安电子科技大学学报,1999.4,26(2):133~136
[80] 毛用才,保铮.多个具有非零均值复乘性噪声的复谐波信号循环估计量的性能分析[J].电子科学学刊,1999.5,21(3):289~295
[81] 毛用才,保铮.多个具有零均值复乘性噪声的复谐波信号循环估计量的性能分析[J].电子科学学刊,1999.7,21(4):482~487
[82] 姜鸣,陈进,秦恺.时变调幅信号的循环平稳特征[J].上海交通大学学报,2001.12,35(12):1798~1801
[83] 秦恺,陈进,姜鸣,陈春梅.一种滚动轴承故障特征提取的新方法——谱相关密度[J].振动与冲击,2001,20(1):34~37
[84] 姜鸣,陈进,秦恺,汪慰军.一阶循环矩分析在旋转机械振动信号分析中的应用[J].振动工程学报,2001,14(4):424~428
[85] 姜鸣,陈进,秦恺.循环周期图在滚动轴承故障诊断中的应用[J].机械科学与技术,2002.1,21(1):108~110
[86] 姜鸣,陈进.循环自相关函数的解调性能分析[J].上海交通大学学报,2002.6,36(6):799~803
[87] 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,2002.9,36(9):943~946
[88] 王锋,屈梁生.小波——循环密度法在旋转机械故障诊断中的应用[J].中国设备工程,2002.6:38~39
[89] 李力,屈梁生.循环域解调方法在滚动轴承故障诊断中的应用[J].轴承,2003,10:33~36
[90] 黄长艺,严普强.机械工程测试技术基础[M].机械工业出版社,2002.1,第 2 版
[91] 国家质量监督局.潜油电泵振动试验方法[M].中华人民共和国国家标准,2000.10
[92] 刘颖峰.旋转机械状态监测系统的研究与开发[M].浙江大学硕士学位论文,2003.1:21~22
[93] 赵叔清,郑薇.随机信号分析[M].哈尔滨工业大学出版社,1999.6
[94] 郭向前.设备振动诊断技术初步(七)——第五讲 振动测试技术[J].设备管理与维修,1994,4:80~82
[95] 袁宏义.设备振动诊断技术初步(八)——设备振动诊断标准及其建立方法[J].设备 管理与维修,1994,5:32~34
[96] 贡文伟,徐桂芳.旋转机械振动诊断标准研究[J].机械研究与应用,2001.9,14(3): 2~5
[97] 曹梅.浅谈旋转机械的故障诊断[J].安徽烟草,2005,5
[2] 李洪周,朱法银,邹积举.潜油电泵振动故障分析及振动模型[J].石油机械,1999,25(12):24~26
[3] 席文厚,朱善正,李勇梅.斜井用潜油电泵机组的研制及应用[J].石油机械,2000,28(4):35~37
[4] Graham Anderson,梁保伟,梁保升.海上潜油电泵采油新技术的成功应用[J].国外油田工程,2001,17(9):28~30
[5] 杨玉民,贺明华.在射孔层下使用电潜泵[J].国外石油机械,1998.8,9(4):42~43
[6] 杨元建,张艳秋,路江安.潜油电泵在油田注水中的应用[J].油气田地面工程,1997.3,16(2):7~8
[7] 春刚.双流电潜泵和井下油水分离器[J].石油机械,2000,28(3):57
[8] 梁明熙,杜滔.定向井双油管及潜油电泵完井技术[J].西部探矿工程,1994.1,6(1):28~31
[9] 李维兰.潜油电泵机组关键件——“电缆头”可靠性与环境应力[J].环境技术,1994,2:28~30
[10] 冯耀忠,袁英,李继康.电潜泵用的调频电机[J].国外石油机械,1998.6,9(3):46~48
[11] 夏华.改进型电潜泵 AC 变频电驱动装置[J].石油机械,1999,5:56
[12] 李振智,唐周怀,龚兴云,汪金周,张素敏.变频器在潜油电泵井上的应用[J].钻采工艺,2001,24(3):45~47
[13] 李武生.变频装置在潜油电泵井的应用[J].油气田地面工程,1999.7,18(4):21~22
[14] 张玉斌,于海春,周平.电潜泵机组可靠性评定[J].石油机械,2003,31(5):6~9
[15] 邹积举,胡再杰,李洪周.潜油电泵联接螺栓的可靠性设计[J].油田设备,1998,27(5):24~27
[16] 朱宗元,李邦俊,李玉青.潜油电泵轴断裂失效分析[J].理化检验-物理分册,2000.1,36(1):34~36
[17] 梁宗红,黄三弥.振动测试技术在旋转机械故障诊断中的应用[J].工业科技,2004,33(1):45~46
[18] 郭向前. 设备振动诊断技术初步(七)——第五讲 振动测试技术[J].设备管理与维修,1994,4:80~82
[19] 黄长艺,严普强.机械工程测试技术基础[M].机械工业出版社,2001.1:2~3
[20] 武和雷.集成智能故障诊断策略及其应用研究[M].浙江大学博士学位论文,2003.12:3
[21] 张贤达.现代信号处理[M].北京:清华大学出版社,1995
[22] 孟庆丰等.数字滤波在机械故障诊断方法中的应用技术[J].动态分析与测试技术,1994,4:5~10
[23] 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,2001.6,14(2):125~134
[24] J.R. Fonolosa and C.L. Nikias,“Wigner Higher order Moment Spectra:Definition,Properities , Computation and Application to Transient Signal Analysis ”, IEEE Trans.Signal Processing.1993,41:245~266.
[25] C.L.Nikias and M.R.Raghuveer,“Bispectrum Estimation:A Digital Signal Processing framework”,Proc.IEEE,1987,75:869~891
[26] G.B.Gianaakis,“Cumulants:A Powerful tool in Signal Processing”,Proc.IEEE,1987,75:1333~1334
[27] R.W. Barker,G.A. Klute and M.J. Hinich,“Monitoring Rotaing Tool wear Using High Order Spetral Features”Transactions of the ASME:J.Engineering for Industry,1993,115:23~29
[28] J.W.A. Fcakrell,P.R. White,J.K. Hammond and R.J. Pinnington,“The Interpretation of the Bispectra of Vibration Signal-Ⅰ. Theory”,Mechanical System and Signal Processing,Mar.1995,257~266
[29] J.W.A. Fcakrell,P.R. White,J.K. Hammond and R.J. Pinnington,“The Interpretation of the Bispectra of Vibration Signal-Ⅱ. Experimental Result and Applications”,Mechanical System and Signal Processing,Mar.1995,257~266
[30] 张春梅,王尚锦,张太镒,朱长新.时频分析在旋转机械状态监测及故障诊断中的应用[J].工程热物理学报,2002.3,23(2):187~189
[31] 张贤达.非平稳信号分析与处理[M].北京:国防工业出版社,1998,1~2
[32] T.A.C.M. Classen and W.F.G. Mecklenbrauker,“The Wigner Distribution-A Tool for Time-Frequency Signal Analysis,part Ⅰ,Ⅱ,Ⅲ”,Philips Res.J,1980,35:217~250
[33] Y. Meyer,Wavelets algorithms and applications,Chapter 2:Wavelet from a historical perspective,Society for Industrial Applied Mathematics,1993
[34] Y. Meyer , Wavelets and applications. Proceedings of the Intermational Conference,Marseiile,France,1989
[35] A. Grossman,J. Morlet.Decomposition of hardy function into square integrable wavelets of constant shape. SLAM J. MATH. ANAL,1984,15(4):723~736
[36] A. Grossman , J. Morlet.Transforms associated to square integrable group representations,Ⅰ:general results. J. MATH. Phys,1985,26(10):2473~2479
[37] I. Daubechies,Orthonormal bases of compactly supported wavelet,Comm.On Pure and Appl.Math,1988,41:909~996
[38] I. Daubechies,The wavelet transform,time-frequency localization and signal analysis,IEEE Trans,1990,IT-36:961~1005
[39] I. Daubechies,Ten lectures on wavelets,SIAM.Philadelphia,Pennsyvania,1992
[40] I. Daubechies,Orthonormal bases of compactly supported wavelet,Ⅱ.Variation on a theme,SIAM J.Math.Anal,1993,24:499~519
[41] I. Daubechies,Orthonormal bases of compactly supported wavelet,Ⅲ.Better frequency resolution,SIAM J.Math.Anal,1993,24:520~527
[42] S. Mallat,A theory of multiresolution signal decomposition:the wavelet transform,IEEE Trans.Pattern Anal.Machine Intell,1989,11(7):674~693
[43] S. Mallat,Multi-frequency channel decompositions of images and wavelet models,IEEE Trans.ASSP,1989,37(12):2091~2110
[44] S. Mallat,W.L.Huang.Singularity detection and processing with wavelets,IEEE Trans.Information Theory,1992,38(2):617~643
[45] S. Mallat,S.Zhong,Characterization of signals from multiscal edges,IEEE Trans.Pattern Anal.Machine Intell,1992,14(7):710~732
[46] W.J. Wang and P.D. McFadden,“Application of Orthogonal Wavelets to early gear damage dection”,Mechanical System and Signal Processing,1995.5,9:497-507
[47] W.J. Wang and P.D. McFadden,“Application of wavelets to gearbox vibration signals for fault detection”,Journal of Sound and vibration,1996.5:927-939
[48] Y. Wu and R. Du,“Feature extraction and assement using wavelet packets for monitoring of maching processes”,Mechanical System and Signal Processing,1996.10:29~53
[49] 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[J].机械工程学报,2000,36(12):95~100
[50] 刘刚,屈梁生.应用连续小波变换提取机械故障的特征[J].西安交通大学学报,2000,36(12):95~100
[51] 林京,屈梁生.基于连续小波变换的奇异性检测与故障诊断[J].振动工程学报,2000,13(4):523~530
[52] 陈涛,屈梁生.多分辨小波网络的理论及应用[J].中国机械工程,1997,8(2):57~59
[53] 陈涛,屈梁生.小波分析及其在机械诊断中的应用[J].机械工程学报,1997,33(3):76~79
[54] 耿中行,屈梁生.小波包的移频算法与振动信号处理[J].振动工程学报,1996,9(2):145~152
[55] 王建忠.小波理论及其在物理和工程中的应用[J]数学进展,1992,21(3):289~793
[56] 邓东皋.小波分析.数学进展[J],1991,20(3):294~310
[57] 焦李成.保铮.子波理论与应用:进展与展望[J].电子学报,1993,21(7):91~96
[58] Norden E. Huang,Zheng Shen,Steven R Long,etal. The empirical mode decomposition and the Hibert spectrum for nonlinear and non-stationary time series analysis[C].Proc.R.Soc.Lond.A.1998:903~995
[59] Better Algorithms for Analyzing Nonlinear,Nonstaitionary Data.http://tco.gsfc.nasa.gov
[60] 胡劲松,杨世锡.基于 HHT 的转子横向裂纹故障诊断[J].动力工程,2004.4,24(2):218~221
[61] Loh CH,etal.Application of the empirical mode decomposition Hibert spectrum method to identify near-fault ground-motion characteristics and structural responses[J].Bulletin of the Seismological Society of America,2001,(91):1339~1357
[62] Vasudevan K,etal.Empircal mode skeletonization of deep crustal seismic data:Theory and applications[J].Journal of Geophysical Research-solid Earth,2000,(105):7845~7856
[63] Echeverria JC,etal.Application of empirical mode decomposition to heart rate variability analysis[J]. Medical & Biological Engineering & Computing,2001,(39):471~479.
[64] 胡劲松,杨世锡.基于 HHT 的转子冲临界过程分析[J].汽轮机技术,2004.6,46(3):196~198
[65] 胡劲松,杨世锡.基于 HHT 的旋转机械故障诊断方法研究[J].动力工程,2004.12,24(6):845~851
[66] 于德介,程军圣,杨宇.Hilbert 能量谱及其在齿轮故障诊断中的应用[J].湖南大学学报,2003.8,30(4):47~50
[67] 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[J].计算机工程与应用,2004,10:6~8
[68] 杨宇,于德介,程军圣.基于 Hilbert-Huang 边际谱的滚动轴承故障诊断方法[J].振动与冲击,2005,24(1):70~72
[69] Gardner W A. Statistical spectral analysis:A nonprobabilistic theory.Englewood Cliffs,NJ:Prentice-Hall,1987
[70] Gardner W A. Exploitation of spectral redundancy in cyclostaionary signals.IEEE Signal Processing Mag,1991.8,8:14~36
[71] Gardner W A(Ed.). Cyclostationary in communication and signal processing.New York.IEEE,1994
[72] Gardner W A,Brown W A.Fraction-of time probability for time-series that exhitbit cyclostationarity.Signal Processing,1991,23:273~292
[73] Gardner W A,Spooner C M. The cumulnt theory of cyclostionary time-series,Part Ⅰ:Foundation.IEEE Trans on Signal Processing,1994,42(12):3387~3408
[74] Spooner C M,Gardner W A. The cumulnt theory of cyclostionary time-series,Part Ⅱ:Development and application.IEEE Trans on Signal Processing,1994,42(12):3409~3429
[75] 毛用才,保铮.复循环平稳的非平稳信号的非参数谱估计[J].电子科学学刊,1996.11,18(6):574~581
[76] 毛用才,保铮.应用循环平稳方法对实测雷达数据的分析[J].西安电子科技大学学报,1997.9,24(3):319~323
[77] 于宏毅,保铮.一类循环加权子空间拟合法的性能分析[J].中国科学(E 辑),1998.12,28(6):513~519
[78] 毛用才,保铮.估计时变幅值复线性调频信号的循环平稳方法及其统计性能分析[J].电子学报,1999.4,27(4):135~136
[79] 于宏毅,保铮.平稳过程循环相关处理的有限数据消失特性[J].西安电子科技大学学报,1999.4,26(2):133~136
[80] 毛用才,保铮.多个具有非零均值复乘性噪声的复谐波信号循环估计量的性能分析[J].电子科学学刊,1999.5,21(3):289~295
[81] 毛用才,保铮.多个具有零均值复乘性噪声的复谐波信号循环估计量的性能分析[J].电子科学学刊,1999.7,21(4):482~487
[82] 姜鸣,陈进,秦恺.时变调幅信号的循环平稳特征[J].上海交通大学学报,2001.12,35(12):1798~1801
[83] 秦恺,陈进,姜鸣,陈春梅.一种滚动轴承故障特征提取的新方法——谱相关密度[J].振动与冲击,2001,20(1):34~37
[84] 姜鸣,陈进,秦恺,汪慰军.一阶循环矩分析在旋转机械振动信号分析中的应用[J].振动工程学报,2001,14(4):424~428
[85] 姜鸣,陈进,秦恺.循环周期图在滚动轴承故障诊断中的应用[J].机械科学与技术,2002.1,21(1):108~110
[86] 姜鸣,陈进.循环自相关函数的解调性能分析[J].上海交通大学学报,2002.6,36(6):799~803
[87] 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,2002.9,36(9):943~946
[88] 王锋,屈梁生.小波——循环密度法在旋转机械故障诊断中的应用[J].中国设备工程,2002.6:38~39
[89] 李力,屈梁生.循环域解调方法在滚动轴承故障诊断中的应用[J].轴承,2003,10:33~36
[90] 黄长艺,严普强.机械工程测试技术基础[M].机械工业出版社,2002.1,第 2 版
[91] 国家质量监督局.潜油电泵振动试验方法[M].中华人民共和国国家标准,2000.10
[92] 刘颖峰.旋转机械状态监测系统的研究与开发[M].浙江大学硕士学位论文,2003.1:21~22
[93] 赵叔清,郑薇.随机信号分析[M].哈尔滨工业大学出版社,1999.6
[94] 郭向前.设备振动诊断技术初步(七)——第五讲 振动测试技术[J].设备管理与维修,1994,4:80~82
[95] 袁宏义.设备振动诊断技术初步(八)——设备振动诊断标准及其建立方法[J].设备 管理与维修,1994,5:32~34
[96] 贡文伟,徐桂芳.旋转机械振动诊断标准研究[J].机械研究与应用,2001.9,14(3): 2~5
[97] 曹梅.浅谈旋转机械的故障诊断[J].安徽烟草,2005,5