Non-stationary vibration feature extraction method based on sparse decomposition and order tracking for gearbox fault diagnosis

Abstract Vibration signals of gearboxes working under time-varying conditions are non-stationary, which causes difficulties to the fault diagnosis. Based on the techniques of signal sparse decomposition and order tracking, a novel method is proposed to extract fault features from non-stationary vibration signals of gearboxes. The method contains two key procedures, the quasi-steady component separation in angle domain and the impact resonance component extraction in time domain. The sparse dictionary including quasi-steady sub-dictionary and impact sub-dictionary is specifically designed according to the time-frequency characteristics of steady-type fault and impact-type fault. The former sub-dictionary consists of cosine functions and is based on the order spectrum information of angle domain signal. The latter sub-dictionary consists of the unit impulse response of multiple-degree-of-freedom vibration system whose modal parameters are self-adaptively recognized by the method of correlation filtering. An improved matching pursuit algorithm on segmental signal is designed to solve sparse coefficients and reconstruct steady-type fault components and impact-type fault components. The simulation analyses show that the proposed method is capable to process the signal with 30% speed fluctuation and −1.5 dB signal-to-noise ratio (SNR), in which the SNR of impact-type fault components is as low as −14.6 dB. The effectiveness is further verified by experimental tests on a fixed-shaft gearbox and a planetary gearbox.

[1]  Ghalib R. Ibrahim,et al.  Adaptive filtering based system for extracting gearbox condition feature from the measured vibrations , 2013 .

[2]  Kang Zhang,et al.  An order tracking technique for the gear fault diagnosis using local mean decomposition method , 2012 .

[3]  Gaigai Cai,et al.  Sparse representation of transients in wavelet basis and its application in gearbox fault feature extraction , 2015 .

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

[5]  Robert B. Randall,et al.  Single and multi-stage phase demodulation based order-tracking , 2014 .

[6]  Guolin He,et al.  A novel order tracking method for wind turbine planetary gearbox vibration analysis based on discrete spectrum correction technique , 2016 .

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

[8]  Robert B. Randall,et al.  Vibration-based diagnostics of gearboxes under variable speed and load conditions , 2016 .

[9]  Jérôme Antoni,et al.  The spectral analysis of cyclo-non-stationary signals , 2016 .

[10]  Dingcheng Zhang,et al.  Multi-fault diagnosis of gearbox based on resonance-based signal sparse decomposition and comb filter , 2017 .

[11]  Huibin Lin,et al.  Vibration mechanisms of spur gear pair in healthy and fault states , 2016 .

[12]  Michael Elad,et al.  Dictionaries for Sparse Representation Modeling , 2010, Proceedings of the IEEE.

[13]  Shunming Li,et al.  A dual path optimization ridge estimation method for condition monitoring of planetary gearbox under varying-speed operation , 2016 .

[14]  Yaguo Lei,et al.  Condition monitoring and fault diagnosis of planetary gearboxes: A review , 2014 .

[15]  Gaigai Cai,et al.  Sparsity-enabled signal decomposition using tunable Q-factor wavelet transform for fault feature extraction of gearbox , 2013 .

[16]  Huibin Lin,et al.  Gearbox coupling modulation separation method based on match pursuit and correlation filtering , 2016 .

[17]  Yu Zhang,et al.  Application of pattern recognition in gear faults based on the matching pursuit of a characteristic waveform , 2017 .

[18]  I. R. Praveen Krishna,et al.  Local fault detection in helical gears via vibration and acoustic signals using EMD based statistical parameter analysis , 2014 .

[19]  Anand Parey,et al.  Gear crack detection using modified TSA and proposed fault indicators for fluctuating speed conditions , 2016 .