The directional Choi-Williams distribution for the analysis of rotor-vibration signals

被引:25
|
作者
Lee, SU [1 ]
Robb, D [1 ]
Besant, C [1 ]
机构
[1] Univ London Imperial Coll Sci Technol & Med, Dept Mech Engn, London SW7 2BX, England
关键词
D O I
10.1006/mssp.2000.1359
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The accurate analysis of time-varying signals is an essential pre-request for the fault diagnosis and hence safe operation of rotating machines. The Wigner distribution (WD) is probably most widely used among the Cohen's class in order to describe how the spectral content of a signal changes over time. However, the basic nature of such signals causes significant interfering cross-terms, which do not permit a straightforward interpretation of the energy distribution. A new signal processing technique, the directional Choi-Williams distribution (dCWD), is proposed to account for complex-valued time-varying signals, which represent the planar motion of rotating machinery at each instant of time. Using the dCWD, not only are the cross-terms minimised but also the interference terms between the forward and backward harmonic components are avoided by transforming complex signals into the forward and backward pass analytic signals. Therefore, the dCWD produces a much lower level of the interference terms than the WD and hence leads to a much clear understanding of the dynamic behaviour of rotors under rotating conditions. The effectiveness of the dCWD is demonstrated by comparing it with the WD and Choi-Williams distribution through some numerical examples and an application to experimental signals. (C) 2001 Academic Press.
引用
收藏
页码:789 / 811
页数:23
相关论文
共 50 条
  • [21] A correlative method of machine condition monitoring based on the Choi-Williams distribution
    Yang, G
    Wu, ZH
    Gao, JJ
    DAMAGE ASSESSMENT OF STRUCTURES VI, 2005, 293-294 : 777 - 783
  • [22] Tonic Cold Pain Detection Using Choi-Williams Time-Frequency Distribution Analysis of EEG Signals: A Feasibility Study
    Alazrai, Rami
    AL-Rawi, Saifaldeen
    Alwanni, Hisham
    Daoud, Mohammad I.
    APPLIED SCIENCES-BASEL, 2019, 9 (16):
  • [23] Gearbox vibration signal fault feature extraction based on ensemble empirical mode decomposition and Choi-Williams distribution
    Wang, Wei-Guo
    Sun, Lei
    Binggong Xuebao/Acta Armamentarii, 2014, 35 (08): : 1288 - 1294
  • [24] Time-frequency analysis of nonstationary complex magneto-hydro-dynamics in fusion plasma signals using the Choi-Williams distribution
    Xu, L. Q.
    Hu, L. Q.
    Chen, K. Y.
    Li, E. Z.
    FUSION ENGINEERING AND DESIGN, 2013, 88 (11) : 2767 - 2772
  • [25] Improved Time-Frequency Distribution using Singular Value Decomposition of Choi-Williams Distribution
    Lu, Juan
    Oruklu, Erdal
    Saniie, Jafar
    2013 IEEE INTERNATIONAL CONFERENCE ON ELECTRO-INFORMATION TECHNOLOGY (EIT 2013), 2013,
  • [26] Spectral Kurtosis of Choi-Williams Distribution and Hidden Markov Model for Gearbox Fault Diagnosis
    Li, Yufei
    Song, Wanqing
    Wu, Fei
    Zio, Enrico
    Zhang, Yujin
    SYMMETRY-BASEL, 2020, 12 (02):
  • [28] Detection of Transient Power Quality Disturbances Based EMD Combined With Choi-Williams Distribution
    Liu, Wei
    Guo, Xiaoting
    2012 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS (ICAL), 2012, : 588 - 591
  • [29] Joint estimation of range and velocity for multiple sources using modified Choi-Williams distribution
    Qin, H
    Huang, J
    Zhang, Q
    Qin, H
    2001 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-VI, PROCEEDINGS: VOL I: SPEECH PROCESSING 1; VOL II: SPEECH PROCESSING 2 IND TECHNOL TRACK DESIGN & IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS NEURALNETWORKS FOR SIGNAL PROCESSING; VOL III: IMAGE & MULTIDIMENSIONAL SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING - VOL IV: SIGNAL PROCESSING FOR COMMUNICATIONS; VOL V: SIGNAL PROCESSING EDUCATION SENSOR ARRAY & MULTICHANNEL SIGNAL PROCESSING AUDIO & ELECTROACOUSTICS; VOL VI: SIGNAL PROCESSING THEORY & METHODS STUDENT FORUM, 2001, : 4045 - 4045
  • [30] Measuring Heart Rate Variability by means of Information Entropies based on Choi-Williams Distribution
    Vallverdu, Montserrat
    Claria, Francesc
    Melia, Umberto
    Bayes de Luna, Antonio
    Caminal, Pere
    2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2015, : 1797 - 1800