A velocity synchrosqueezing transform for fault diagnosis of planetary gearboxes under nonstationary conditions

Time–frequency analysis is widely used in the field of machinery condition monitoring and fault diagnosis under nonstationary conditions. Among the time–frequency methods synchrosqueezing transform outperforms others in providing fine-resolution time–frequency representation. However, it suffers from time–frequency smear when analysing nonstationary signals. To address this issue, this paper proposes a new synchrosqueezing-transform-based method which works by (1) mapping the raw nonstationary vibration signal into a corresponding stationary angle domain signal to meet the stationarity requirement of the synchrosqueezing transform, (2) performing the synchrosqueezing transform of the corresponding signal and (3) restoring the time–frequency representation of the raw signal from the synchrosqueezing transform result of the corresponding signal. As the synchrosqueezing transform is applied to the stationary corresponding signal, the time–frequency smear is eliminated in the synchrosqueezing transform result of the corresponding signal and the final signal time–frequency representation. As such the proposed method can generate a smear-free time–frequency representation with fine time–frequency resolution and thus provide more reliable diagnosis decisions. A fast implementation algorithm is also developed to simplify the implementation of the proposed method. The effectiveness of the proposed method is validated using both simulated and experimental vibration signals of planetary gearboxes.

[1]  F. Hlawatsch,et al.  Linear and quadratic time-frequency signal representations , 1992, IEEE Signal Processing Magazine.

[2]  Liu Hong,et al.  An explanation of frequency features enabling detection of faults in equally spaced planetary gearbox , 2014 .

[3]  William J. Williams,et al.  Improved time-frequency representation of multicomponent signals using exponential kernels , 1989, IEEE Trans. Acoust. Speech Signal Process..

[4]  Tomasz Barszcz,et al.  A two-step procedure for estimation of instantaneous rotational speed with large fluctuations , 2013 .

[5]  Jérôme Antoni,et al.  Vibration based condition monitoring of a multistage epicyclic gearbox in lifting cranes , 2014 .

[6]  Zhipeng Feng,et al.  Iterative generalized synchrosqueezing transform for fault diagnosis of wind turbine planetary gearbox under nonstationary conditions , 2015 .

[7]  Simon Haykin,et al.  The chirplet transform: physical considerations , 1995, IEEE Trans. Signal Process..

[8]  Ahmet Kahraman,et al.  A theoretical and experimental investigation of modulation sidebands of planetary gear sets , 2009 .

[9]  William D. Mark Stationary transducer response to planetary-gear vibration excitation II: Effects of torque modulations , 2009 .

[10]  Yang Yang,et al.  Multicomponent Signal Analysis Based on Polynomial Chirplet Transform , 2013, IEEE Transactions on Industrial Electronics.

[11]  Douglas L. Jones,et al.  A signal-dependent time-frequency representation: optimal kernel design , 1993, IEEE Trans. Signal Process..

[12]  Radoslaw Zimroz,et al.  Vibration condition monitoring of planetary gearbox under varying external load , 2009 .

[13]  K. R. Fyfe,et al.  ANALYSIS OF COMPUTED ORDER TRACKING , 1997 .

[14]  Chuan Li,et al.  Time-frequency signal analysis for gearbox fault diagnosis using a generalized synchrosqueezing transform , 2012 .

[15]  Tomasz Barszcz,et al.  Measurement of instantaneous shaft speed by advanced vibration signal processing - Application to wind turbine gearbox , 2010 .

[16]  James McNames,et al.  Fourier Series Analysis of Epicyclic Gearbox Vibration , 2002 .

[17]  P D McFadden,et al.  An Explanation for the Asymmetry of the Modulation Sidebands about the Tooth Meshing Frequency in Epicyclic Gear Vibration , 1985 .

[18]  W. M. Zhang,et al.  Polynomial Chirplet Transform With Application to Instantaneous Frequency Estimation , 2011, IEEE Transactions on Instrumentation and Measurement.

[19]  Robert B. Randall,et al.  A New Method of Modeling Gear Faults , 1982 .

[20]  Fakher Chaari,et al.  Modelling of gearbox dynamics under time-varying nonstationary load for distributed fault detection and diagnosis , 2010 .

[21]  Ming Liang,et al.  Time–frequency analysis based on Vold-Kalman filter and higher order energy separation for fault diagnosis of wind turbine planetary gearbox under nonstationary conditions , 2016 .

[22]  M. Plancherel,et al.  Contribution À ĽÉtude de la reprÉsentation D’une fonction arbitraire par des intÉgrales dÉfinies , 1910 .

[23]  Douglas L. Jones,et al.  An adaptive optimal-kernel time-frequency representation , 1995, IEEE Trans. Signal Process..

[24]  William D. Mark,et al.  Stationary transducer response to planetary-gear vibration excitation with non-uniform planet loading , 2009 .

[25]  Chuan Li,et al.  A generalized synchrosqueezing transform for enhancing signal time-frequency representation , 2012, Signal Process..

[26]  I. Daubechies,et al.  Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool , 2011 .

[27]  Radoslaw Zimroz,et al.  Two simple multivariate procedures for monitoring planetary gearboxes in non-stationary operating conditions , 2013 .

[28]  Paolo Pennacchi,et al.  The velocity synchronous discrete Fourier transform for order tracking in the field of rotating machinery , 2014 .

[29]  Jont B. Allen,et al.  Short term spectral analysis, synthesis, and modification by discrete Fourier transform , 1977 .

[30]  G. Meng,et al.  Spline-Kernelled Chirplet Transform for the Analysis of Signals With Time-Varying Frequency and Its Application , 2012, IEEE Transactions on Industrial Electronics.

[31]  Zhipeng Feng,et al.  Fault diagnosis of wind turbine planetary gearbox under nonstationary conditions via adaptive optimal kernel time–frequency analysis , 2014 .

[32]  Ming J. Zuo,et al.  Vibration signal models for fault diagnosis of planetary gearboxes , 2012 .

[33]  Darryll J. Pines,et al.  A review of vibration-based techniques for helicopter transmission diagnostics , 2005 .

[34]  Zhipeng Feng,et al.  Complex signal analysis for wind turbine planetary gearbox fault diagnosis via iterative atomic decomposition thresholding , 2014 .

[35]  Ahmet Kahraman,et al.  A dynamic model to predict modulation sidebands of a planetary gear set having manufacturing errors , 2010 .

[36]  H. Zheng,et al.  GEAR FAULT DIAGNOSIS BASED ON CONTINUOUS WAVELET TRANSFORM , 2002 .