Multi-stable stochastic resonance and its application research on mechanical fault diagnosis

Abstract It is difficult to extract the fault features of a rotating machine via vibration analysis due to interference from background noise. Stochastic resonance (SR), used as a method of utilising noise to amplify weak signals in nonlinear dynamical systems, can detect weak signals overwhelmed in the noise. However, the detection effect of current SR methods is still unsatisfactory. To further increase the output signal-to-noise ratio (SNR) and improve the detection effect of SR, the present study proposes an improved SR method with a multi-stable model for identifying the defect-induced rotating machine faults by analysing the influence relationship between the resonance model and the resonance effect. Due to the structural characteristics of three potential wells and two barriers, the proposed resonance model can not only further amplify weak signals, but also convert into a monostable model, a bistable model or a tristable model. This result is achieved by adjusting system parameters and thus obtaining a better matching of the input signals and resonance models. Therefore, the multi-stable SR method, combined with the characteristics of the multi-stable model, can both increase the output SNR and improve the detection effect and also detect the low SNR signals and enhance the processing capability of SR for weak signals. Finally, the proposed method is applied to a gearbox fault diagnosis in a rolling mill in which two local faults located in the big gear and the pinion, respectively, are found successfully. It can be concluded that multi-stable SR method has practical value in engineering.

[1]  Min Lin,et al.  The Control of Stochastic Resonance by Harmonic Signal , 2011 .

[2]  Zhongkui Zhu,et al.  Transient modeling and parameter identification based on wavelet and correlation filtering for rotating machine fault diagnosis , 2011 .

[3]  S. Fauve,et al.  Stochastic resonance in a bistable system , 1983 .

[4]  Gregoire Nicolis,et al.  Stochastic resonance , 2007, Scholarpedia.

[5]  Yanyang Zi,et al.  Study of frequency-shifted and re-scaling stochastic resonance and its application to fault diagnosis , 2009 .

[6]  Jimeng Li.  Adaptive Monostable Stochastic Resonance Based on PSO with Application in Impact Signal Detection , 2011 .

[7]  Toshiya Iwai,et al.  Study of stochastic resonance by method of stochastic energetics , 2001 .

[8]  Lin Min,et al.  The stochastic energetics resonance of bistable systems and efficiency of doing work , 2011 .

[9]  B. Kosko,et al.  Adaptive stochastic resonance , 1998, Proc. IEEE.

[10]  A. Kenfack,et al.  Stochastic resonance in coupled underdamped bistable systems. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[11]  A. Sutera,et al.  The mechanism of stochastic resonance , 1981 .

[12]  Fanrang Kong,et al.  Multiscale noise tuning of stochastic resonance for enhanced fault diagnosis in rotating machines , 2012 .

[13]  Taiyong Wang,et al.  Study on non-linear filter characteristic and engineering application of cascaded bistable stochastic resonance system , 2007 .

[14]  Chen Min,et al.  The Application of Stochastic Resonance Theory for Early Detecting Rub-Impact Fault of Rotor System , 2003 .

[15]  Haining Huang,et al.  Improved bearing estimates of weak signals using stochastic resonance and frequency shift techniques , 2003, Oceans 2003. Celebrating the Past ... Teaming Toward the Future (IEEE Cat. No.03CH37492).

[16]  Gang,et al.  Stochastic resonance in a nonlinear system driven by an aperiodic force. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[17]  F. McNeill,et al.  Grid search: an innovative method for the estimation of the rates of lead exchange between body compartments. , 2005, Journal of environmental monitoring : JEM.

[18]  Pulak Kumar Ghosh,et al.  Interference of stochastic resonances: splitting of Kramers' rate. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Eli Pollak,et al.  Kramers Turnover Theory for a Triple Well Potential , 2001 .

[20]  S Rajasekar,et al.  Analysis of vibrational resonance in a quintic oscillator. , 2009, Chaos.

[21]  Ming Liang,et al.  Identification of multiple transient faults based on the adaptive spectral kurtosis method , 2012 .

[22]  Bohou Xu,et al.  Intrawell stochastic resonance of bistable system , 2004 .

[23]  Ruqiang Yan,et al.  Harmonic wavelet-based data filtering for enhanced machine defect identification , 2010 .

[24]  Wiesenfeld,et al.  Theory of stochastic resonance. , 1989, Physical review. A, General physics.

[25]  A.H. Tewfik,et al.  Detection of weak signals using adaptive stochastic resonance , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[26]  Klaus Obermayer,et al.  Activity Driven Adaptive Stochastic Resonance , 2001, NIPS.

[27]  Ming Yang,et al.  A wavelet approach to fault diagnosis of a gearbox under varying load conditions , 2010 .

[28]  Yong Chen,et al.  Stochastic resonance in time-delayed bistable systems driven by weak periodic signal , 2008, 0806.0427.

[29]  Guo Yan,et al.  Engineering signal processing based on bistable stochastic resonance , 2007 .

[30]  Tai Yong Wang,et al.  Numerical analysis and engineering application of large parameter stochastic resonance , 2006 .

[31]  Robert X. Gao,et al.  Performance enhancement of ensemble empirical mode decomposition , 2010 .

[32]  Leon O. Chua,et al.  STOCHASTIC RESONANCE IN CHUA’S CIRCUIT , 1992 .