多维固有时间尺度分解算法
|
摘要
针对控制回路、机械系统实际运行数据复杂多变、非稳定、非线性、信号耦合性强等问题,提出了一种新的多维信号分解方法,多维固有时间尺度分解(MITD)。给出了算法步骤;对所提出的MITD进行一定程度优化,以达到更好的分解效果;对所提出算法进行仿真分析和工业实例分析,表明了MITD对多维数据分解的优越性。
Aiming at the problem of actual operation data of control loop and the mechanical system is complex,variable,unstable,non-linear,strong signal coupling and other issues,a new multi-dimensional signal decomposition method is proposed,called multi-dimensional intrinsic time scale decomposition( MITD). Algorithm steps are given,MITD is optimized to achieve better decomposition effect. Simulation analysis and actual industrial analysis show the superiority of MITD to multi-dimensional data decomposition.
Aiming at the problem of actual operation data of control loop and the mechanical system is complex,variable,unstable,non-linear,strong signal coupling and other issues,a new multi-dimensional signal decomposition method is proposed,called multi-dimensional intrinsic time scale decomposition( MITD). Algorithm steps are given,MITD is optimized to achieve better decomposition effect. Simulation analysis and actual industrial analysis show the superiority of MITD to multi-dimensional data decomposition.
引文
[1]林萍,陈华杰,林封笑.基于EEMD的车辆微动信号提取及分类[J].传感器与微系统,2017,36(10):38-40,44.
[2]王之宏,范玉刚,冯早.旋转机械设备运行状态远程监测系统研究与开发[J].传感器与微系统,2017,36(9):88-90,93.
[3]印嘉,吴建德,王晓东,等.基于HHT的往复式隔膜泵主轴故障诊断研究[J].传感器与微系统,2013,32(4):5-8.
[4]曲志刚,封皓,靳世久,等.基于提升小波的管道安全系统信号特征提取方法[J].传感器与微系统,2010,29(5):59-62.
[5]贾可,张雪锋.二维EMD的指纹边缘检测算法[J].传感器与微系统,2016,35(10):127-130,134.
[6] REHMAN N,MANDIC D P. Multivariate mode decomposition[C]∥Proceedings of The Royal Society of London A:Mathematical,Physical and Engineering Sciences,2010:1291-1302.
[7] FREI M G,OSORIO I. Intrinsic time-scale decomposition:timefrequency-energy analysis and real-time filtering of non-stationary signals[C]∥Proceedings of the Royal Society of London A:Mathematical,Physical and Engineering Sciences,2007:321-342.
[8]毛敏,王晓东,吴建德,等.基于EMD与VPMCD的矿浆管道泄漏检测方法[J].传感器与微系统,2018,37(1):149-153.
[9]张立国,李盼,李梅梅,等.基于ITD模糊熵和GG聚类的滚动轴承故障诊断[J].仪器仪表学报,2014,35(11):2624-2632.
[10]陈勇旗,赵一鸣,陈杨.基于固有时间尺度分解的滚动轴承故障诊断[J].电子测量与仪器学报,2015,29(11):1677-1682.
[11] ALABIED S,HAMOMD O,DARAZ A,et al. Fault diagnosis of centrifugal pumps based on the intrinsic time-scale decomposition of motor current signals[C]∥2017 the 23rd International Conference on Automation and Computing(ICAC),Huddersfield:IEEE,2017:1-6.
[12] REN D,ZHANG T. Specific emitter identification based on intrinsic time-scale-decomposition and image texture feature[C]∥2017 IEEE the 9th International Conference on Communication Software and Networks(ICCSN),Guangzhou:IEEE,2017:1302-1307.
[13] XIONG W H,ZHAO G Z. A new method to identify inrush current based on HHT[C]∥2006 the 6th World Congress on Intelligent Control and Automation,Dalian:IEEE,2006:7480-7483.
[14] KOMATY A,BOUDRAA A O,NOLAN J P,et al. On the behavior of EMD and MEMD in presence of symmetric alpha-stable noise[J]. IEEE Signal Processing,2015,22(7):818-822.
[15] REHMAN N,XIA Y,MANDIC D P. Application of multivariate empirical mode decomposition for seizure detection in EEG signals[C]∥2010 Annual International Conference of the IEEE Engineering in Medicine and Biology,Buenos Aires:IEEE,2010:1650-1653.
[2]王之宏,范玉刚,冯早.旋转机械设备运行状态远程监测系统研究与开发[J].传感器与微系统,2017,36(9):88-90,93.
[3]印嘉,吴建德,王晓东,等.基于HHT的往复式隔膜泵主轴故障诊断研究[J].传感器与微系统,2013,32(4):5-8.
[4]曲志刚,封皓,靳世久,等.基于提升小波的管道安全系统信号特征提取方法[J].传感器与微系统,2010,29(5):59-62.
[5]贾可,张雪锋.二维EMD的指纹边缘检测算法[J].传感器与微系统,2016,35(10):127-130,134.
[6] REHMAN N,MANDIC D P. Multivariate mode decomposition[C]∥Proceedings of The Royal Society of London A:Mathematical,Physical and Engineering Sciences,2010:1291-1302.
[7] FREI M G,OSORIO I. Intrinsic time-scale decomposition:timefrequency-energy analysis and real-time filtering of non-stationary signals[C]∥Proceedings of the Royal Society of London A:Mathematical,Physical and Engineering Sciences,2007:321-342.
[8]毛敏,王晓东,吴建德,等.基于EMD与VPMCD的矿浆管道泄漏检测方法[J].传感器与微系统,2018,37(1):149-153.
[9]张立国,李盼,李梅梅,等.基于ITD模糊熵和GG聚类的滚动轴承故障诊断[J].仪器仪表学报,2014,35(11):2624-2632.
[10]陈勇旗,赵一鸣,陈杨.基于固有时间尺度分解的滚动轴承故障诊断[J].电子测量与仪器学报,2015,29(11):1677-1682.
[11] ALABIED S,HAMOMD O,DARAZ A,et al. Fault diagnosis of centrifugal pumps based on the intrinsic time-scale decomposition of motor current signals[C]∥2017 the 23rd International Conference on Automation and Computing(ICAC),Huddersfield:IEEE,2017:1-6.
[12] REN D,ZHANG T. Specific emitter identification based on intrinsic time-scale-decomposition and image texture feature[C]∥2017 IEEE the 9th International Conference on Communication Software and Networks(ICCSN),Guangzhou:IEEE,2017:1302-1307.
[13] XIONG W H,ZHAO G Z. A new method to identify inrush current based on HHT[C]∥2006 the 6th World Congress on Intelligent Control and Automation,Dalian:IEEE,2006:7480-7483.
[14] KOMATY A,BOUDRAA A O,NOLAN J P,et al. On the behavior of EMD and MEMD in presence of symmetric alpha-stable noise[J]. IEEE Signal Processing,2015,22(7):818-822.
[15] REHMAN N,XIA Y,MANDIC D P. Application of multivariate empirical mode decomposition for seizure detection in EEG signals[C]∥2010 Annual International Conference of the IEEE Engineering in Medicine and Biology,Buenos Aires:IEEE,2010:1650-1653.