Generalized stepwise demodulation transform and synchrosqueezing for time-frequency analysis and bearing fault diagnosis

被引:126
|
作者
Shi, Juanjuan [1 ]
Liang, Ming [1 ]
Necsulescu, Dan-Sorin [1 ]
Guan, Yunpeng [1 ]
机构
[1] Univ Ottawa, Dept Mech Engn, Ottawa, ON K1N 6N5, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Time-frequency analysis; Energy concentration level; Generalized demodulation; Time-varying speed condition; Bearing fault diagnosis; WIND TURBINES; SPEED-UP; SIGNALS; TRACKING; GEARBOX;
D O I
10.1016/j.jsv.2016.01.015
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
The energy concentration level is an important indicator for time-frequency analysis (TFA). Weak energy concentration would result in time-frequency representation (TFR) diffusion and thus leading to ambiguous results or even misleading signal analysis results, particularly for nonstationary multicomponent signals. To improve the energy concentration level, this paper proposes a generalized stepwise demodulation transform (GSDT). The rationale of the proposed method is that (1) the generalized demodulation (GD) can map the original signal into an analytic signal with constant instantaneous frequency (IF) and improve the energy concentration level on time-frequency plane, and (2) focusing on a short window around the time instant of interest, a backward demodulation operation can recover the original frequency at the time instant without affecting the improved energy concentration level. By repeating the backward demodulation at every time instant of interest, the TFR of the entire signal can be attained with enhanced energy concentration level. With the GSDT, an iterative GSDT (IGSDT) is developed to analyze multicomponent signal that is subjected to different modulating sources for their constituent components. The IGSDT iteratively demodulates each constituent component to attain its TFR and the TFR of the whole signal is derived from superposing all the resulting TFRs of constituent components. The cross-term free and more energy concentrated TFR of the signal is, therefore, obtained, and the diffusion in the TFR can be reduced. The GSDT-based synchrosqueezing transform is also elaborated to further enhance the GSDT(IGSDT) yielded TFR. The effectiveness of the proposed method in TFA is tested using both simulated monocomponent and multicomponent signals. The application of the proposed method to bearing fault detection is explored. Bearing condition and fault pattern can be revealed by the proposed method resulting TFR. The main advantages of the proposed method for bearing condition monitoring under variable speed conditions include: (a) it can simultaneously improve energy concentration level of signals of interest and remove interferences in the TFR, (b) it is resampling-free and hence can avoid the resampling related errors, and (c) it yields instantaneous frequencies for fault and shaft rotation and thus can carry out both fault detection and diagnosis tasks. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:202 / 222
页数:21
相关论文
共 50 条
  • [1] Bearing Fault Diagnosis Using Time-Frequency Synchrosqueezing Transform
    Yu, Lan
    [J]. 2020 CHINESE AUTOMATION CONGRESS (CAC 2020), 2020, : 4260 - 4264
  • [2] Instantaneous Frequency Synchronized Generalized Stepwise Demodulation Transform for Bearing Fault Diagnosis
    Shi, Juanjuan
    Hua, Zehui
    Huang, Weiguo
    Dumond, Patrick
    Shen, Changqing
    Zhu, Zhongkui
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
  • [3] Time-frequency signal analysis for gearbox fault diagnosis using a generalized synchrosqueezing transform
    Li, Chuan
    Liang, Ming
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2012, 26 : 205 - 217
  • [4] Matching Demodulation Transform and SynchroSqueezing in Time-Frequency Analysis
    Wang, Shibin
    Chen, Xuefeng
    Cai, Gaigai
    Chen, Binqiang
    Li, Xiang
    He, Zhengjia
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2014, 62 (01) : 69 - 84
  • [5] Time-Frequency Squeezing and Generalized Demodulation Combined for Variable Speed Bearing Fault Diagnosis
    Huang, Weiguo
    Gao, Guanqi
    Li, Ning
    Jiang, Xingxing
    Zhu, Zhongkui
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2019, 68 (08) : 2819 - 2829
  • [6] Matching Demodulation Synchrosqueezing S Transform and Its Application in Seismic Time-Frequency Analysis
    Wang, Qian
    Li, Yexue
    Chen, Shijun
    Tang, Bo
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
  • [7] A generalized synchrosqueezing transform for enhancing signal time-frequency representation
    Li, Chuan
    Liang, Ming
    [J]. SIGNAL PROCESSING, 2012, 92 (09) : 2264 - 2274
  • [8] Applications of the synchrosqueezing transform in seismic time-frequency analysis
    Herrera, Roberto H.
    Han, Jiajun
    van der Baan, Mirko
    [J]. GEOPHYSICS, 2014, 79 (03) : V55 - V64
  • [9] Time-frequency demodulation analysis based on iterative generalized demodulation for fault diagnosis of planetary gearbox under nonstationary conditions
    Feng, Zhipeng
    Chen, Xiaowang
    Liang, Ming
    Ma, Fei
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2015, 62-63 : 54 - 74
  • [10] Multichannel synchrosqueezing generalized S-transform for time-frequency analysis of seismic traces
    Wu, Nanke
    Zhou, Huailai
    Wang, Yuanjun
    Zhang, Bo
    Yan, Haitao
    Niu, Cong
    [J]. INTERPRETATION-A JOURNAL OF SUBSURFACE CHARACTERIZATION, 2020, 8 (04): : T793 - T801