Abstract
The nonlinear stochastic resonance system possesses the ability of taking advantage of background noise to enhance the weak signal. It provides a new approach to detect the weak signal embedded with heavy noise. This study proposes a new varying parameter stochastic resonance employing the fourth-order Runge–Kutta numerical method as well as the normalized transformation of a bistable stochastic resonance system. The model performs well in the detection of a time-varying signal with background noise for denoising and signal recovery. We take the fitness coefficient and cross-correlation coefficient as the criteria and analyze the influence of different parameters. The simulating results indicate its availability, validity and that it generates a better performance than the traditional stochastic resonance. The method develops the area of time-varying signal detection with stochastic resonance and presents new strategy for detection and denoising of a time-varying signal. It can be expected to be widely used in the areas of aperiodic signal processing, radar communication, etc.
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Reference
Benzi R, Sutera A and Vulpiani A 1981 The mechanism of stochastic resonance. J. Phys. A-Math. General 14: L453–L457
Gammaitoni L, Hanggi P, Jung P and Marchesoni F 1998 Stochastic resonance. Rev. Modern Phys. 70: 223–287
Dykman M I and McClintock P V E 1998 What can stochastic resonance do? Nature 391: 344–344
Gammaitoni L, Marchesoni F, Menichellasaetta E and Santucci S 1989 Stochastic resonance in bistable systems. Phys. Rev. Lett. 62: 349–352
Chen H and Varshney P K 2008 Theory of the stochastic resonance effect in signal detection—Part II: Variable detectors. IEEE Trans. Signal Process. 56: 5031–5041
Jung P and Hanggi P 1991 Amplification of small signals via stochastic resonance. Phys. Rev. A 44: 8032–8042
Leng Y G, Wang T Y, Guo Y, Xu Y G and Fan S B 2007 Engineering signal processing based on bistable stochastic resonance. Mech. Syst. Signal Process. 21: 138–150
Lu S, He Q and Kong F 2015 Effects of underdamped step-varying second-order stochastic resonance for weak signal detection. Digital Signal Process. 36: 93–103
Zozor S and Amblard P O 2002 On the use of stochastic resonance in sine detection. Signal Process. 82: 353–367
He Q B, Wang J, Liu Y B, Dai D Y and Kong F R 2012 Multiscale noise tuning of stochastic resonance for enhanced fault diagnosis in rotating machines. Mech. Syst. Signal Process. 28: 443–457
Lei Y G, Lin J, Han D and He Z J 2014 An enhanced stochastic resonance method for weak feature extraction from vibration signals in bearing fault detection. Proceedings of the Institution of Mechanical Engineers Part C-J. Mech. Eng. Sci. 228: 815–827
Li J M, Chen X F and He Z J 2013 Multi-stable stochastic resonance and its application research on mechanical fault diagnosis. J. Sound Vib. 332: 5999–6015
Tan J Y, Chen X F, Wang J X, Chen H X, Cao H R and Zi Y Y 2009 Study of frequency-shifted and re-scaling stochastic resonance and its application to fault diagnosis. Mech. Syst. Signal Process. 23: 811–822
Gammaitoni L, Neri I and Vocca H 2009 Nonlinear oscillators for vibration energy harvesting. Appl. Phys. Lett. 94: 164102(1)–164102(3)
Harne R L and Wang K W 2013 A review of the recent research on vibration energy harvesting via bistable systems. Smart Mater. Struct. 22: 023001(1)–023001(12)
McInnes C R, Gorman D G and Cartmell M P 2008 Enhanced vibrational energy harvesting using nonlinear stochastic resonance. J. Sound Vib. 318: 655–662
Singh A K and Saxena R 2013 Doppler estimation from echo signal using FRFT. Wirel. Pers. Commun. 72: 405–413
Wang M S, Chan A K and Chui C K 1998 Linear frequency-modulated signal detection using radon-ambiguity transform. IEEE Trans. Signal Process. 46: 571–586
Wang P, Li H B and Himed B 2008 Parameter estimation of linear frequency-modulated signals using integrated cubic phase function, 2008 42nd Asilomar Conference on Signals, Systems and Computers, vol 1–4, pp. 487–491
Collins J J, Chow C C and Imhoff T T 1995 Aperiodic stochastic resonance in excitable systems. Phys. Rev. E 52: R3321–R3324
Collins J J, Chow C C, Capela A C and Imhoff T T 1996 Aperiodic stochastic resonance. Phys. Rev. E 54: 5575–5584
Hu G, Gong D C, Wen X D, Yang C Y, Qing G R and Li R 1992 Stochastic resonance in a nonlinear-system driven by an aperiodic force. Phys. Rev. A 46: 3250–3254
Eichwald C and Walleczek J 1997 Aperiodic stochastic resonance with chaotic input signals in excitable systems. Phys. Rev. E 55: R6315–R6318
Yang D X and Hu N Q 2004 Detection of weak aperiodic shock, signal based on stochastic resonance. In: Proceedings of the Third International Symposium on Instrumentation Science and Technology, vol 1, pp. 209–21325
Peng H, Zhong S C, Tu Z and Ma H 2013 Stochastic resonance of over-damped bistable system driven by chirp signal and Gaussian white noise. Acta Physica Sinica 62: 080501(1)–080501(6)
Hu N Q, Chen M and Wen X S 2003 The application of stochastic resonance theory for early detecting rub-impact fault of rotor system. Mech. Syst. Signal Process. 17: 883–895
Øksendal B 2003 Stochastic differential equations. In: Stochastic differential equations, ed: Springer Berlin Heidelberg, pp. 65–84
Leng Y G, Yong S L, Wang T Y and Yan G 2006 Numerical analysis and engineering application of large parameter stochastic resonance. J. Sound Vib. 292: 788–801
Park K, Lai Y C, Liu Z H and Nachman A 2004 Aperiodic stochastic resonance and phase synchronization. Phys. Lett. A 326: 391–396
Morse P K and Ingard K U 1968 Theoretical acoustics (section 2). New York: Princeton University Press
Acknowledgements
This work was supported in part by the National Natural Science Foundation of China with the Grant Nos. 51475441 and 11274300. Besides, the authors also would like to thank the anonymous reviewers for their valuable comments and suggestions.
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Zhang, H., Xiong, W., Zhang, S. et al. Nonstationary weak signal detection based on normalization stochastic resonance with varying parameters. Sādhanā 41, 621–632 (2016). https://doi.org/10.1007/s12046-016-0503-x
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DOI: https://doi.org/10.1007/s12046-016-0503-x