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Extended stochastic resonance (SR) and its applications
in weak mechanical signal processing |
| Niaoqing HU,Min CHEN,Guojun QIN,Lurui XIA,Zhongyin PAN,Zhanhui FENG, |
| School of Mechatronics
Engineering and Automation, National University of Defense Technology,
Changsha 410073, China; |
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Abstract To catch symptoms of machine failure as early as possible, one of the most important strategies is to apply more progressive techniques during signal processing. This paper presents a method based on stochastic resonance (SR) to detect weak fault signal. First, a discrete model of a bistable system that can demonstrate SR is researched, and the stability condition for controlling the selection of model parameters of the discrete model and guarantee the solving convergence are established. Then, the frequency range of the weak signals that the SR model can detect is extended through a type of normalized scale transformation. Finally, the method is applied to extract the weak characteristic component from heavy noise to indicate the little crack fault in a bearing outer circle.
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| Keywords
extended stochastic resonance (SR)
stability analysis of SR
scale transform
weak signal detection
incipient fault detection
envelope analysis
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Issue Date: 05 December 2009
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Qu L S, Lin J. A difference resonator fordetecting weak signals. Journal of Measurement, 1999, 26(1): 69–77
doi: 10.1016/S0263-2241(99)00023-8
|
|
Donald L B. Chaotic oscillators and CMFFNS for signal detection in noise environment. IEEE International Joint Conference on Neural Networks, 1992, 2: 881–888
|
|
Hu N Q, Wen X S. The application of duffingoscillator in characteristic signal detection of early fault. Journal of Sound and Vibration, 2003, 268(5): 917–931
doi: 10.1016/S0022-460X(03)00002-6
|
|
He Z J, Zhao J Y, Meng Q F. Wavelet transform in tandem with autoregressive techniquefor monitoring and diagnosis of machinery. Chinese Journal of Mechanical Engineering, 1996, 9(4): 311–317
|
|
Gong D C, Hu G, Wen X D, Yang C Y, Qin G R, Li R, Ding D F. Experimental study of signal-to-noiseratio of stochastic resonance systems. Physical Review A, 1992, 46(6): 3243–3249
doi: 10.1103/PhysRevA.46.3243
|
|
Benzi R, Sutera A, Vulpiani A. The Mechanism of stochastic resonance. Journal of Physics A: Mathematical and General, 1981, 14(11): 453–457
doi: 10.1088/0305-4470/14/11/006
|
|
Gammaitoni L, Hänggi P, Jung P, Marchesoni F. Stochastic resonance. Reviews of ModernPhysics, 1998, 70(1): 223–287
doi: 10.1103/RevModPhys.70.223
|
|
Hu N Q, Chen M, Wen X S. The application of stochastic resonance theory for earlydetecting rub-impact fault of rotor system. Mechanical System and Signal Processing, 2003, 17(4): 883–895
doi: 10.1006/mssp.2002.1470
|
|
Franaszek M, Simiu E. Stochastic resonance: a chaoticdynamics approach. Physical Review E, 1996, 54(2): 1298–1304
doi: 10.1103/PhysRevE.54.1298
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