A Novel Second Order Bistable Adaptive Random Resonance Noise Reduction Method
American Journal of Physics and Applications
Volume 6, Issue 1, January 2018, Pages: 6-10
Received: Sep. 21, 2017; Accepted: Oct. 11, 2017; Published: Nov. 21, 2017
Views 2479      Downloads 140
Authors
Rui Tang, School of Mechanical Engineering, Panzhihua University, Panzhihua, China
Zheng Zhang, School of Mechanical Engineering, Xihua University, Chengdu, China
Article Tools
Follow on us
Abstract
This paper aimed at the key problems which the monitoring and fault diagnosis of process system generated in the high performance composite components manufacturing, established a new type of second-order bistable model, proposed a kind of adaptive stochastic resonance noise reduction method based on the model, and experimented to verifiy, it has very good detection effect and higher operation effect.
Keywords
High Performance Composite Components, Bistable Adaptation, Noise Reduction
To cite this article
Rui Tang, Zheng Zhang, A Novel Second Order Bistable Adaptive Random Resonance Noise Reduction Method, American Journal of Physics and Applications. Vol. 6, No. 1, 2018, pp. 6-10. doi: 10.11648/j.ajpa.20180601.12
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Qin Yi, Wang Teng, He Qiyuan, Ren Bing. Application of Higher Density Wavelet Transform to Composite Fault Diagnosis of Rolling Bearing [J]. Journal of Chongqing University, 2013, 36(3): 13-19.
[2]
R. Benzi, A. Sutera, A. Vulpiana. The mechanism of stochastic resonance [J]. Journal of Physics A: Mathematical and General, 1981, 14(11): 453–457.
[3]
H. Gang, G. Nicolis, C. Nicolis. Periodically forced Fokker–Planck equation and stochastic resonance [J], Physical ReviewA, 1990, 42 (4): 2030–2041.
[4]
L. Gammaitoni, P. Hanggi, P. Jung, F. Marchesoni. Stochastic Resonance [J]. Reviews of Modern Physics, 1998, 70(1): 223–287.
[5]
Len Yonggang, Wang Taiyong. Numerical Research of Twice Sampling Stochastic for The detection of A Weak Signal Submerged in A Heavy Noise [J]. Acta Phisica Sinica, 2003, 52, 10, 2432-2437.
[6]
F. Mao, M. Lin, Y. Zheng. Study of weak multi-frequencies signal detection based on stochastic resonance [J]. Journal of Basic Science and Engineering, 2008, 16(1): 86–91. [74].
[7]
J. Y. Tan, X. F. Chen, J. Y. Wang, H. X. Chen. H. R. Cao, Y. Y. Zi, Z. J. He. Study of frequency-shifted and re-scaling stochastic resonance and its application to fault diagnosis [J]. Mechanical Systems and Signal Processing, 2009, 23(3): 811–822.
[8]
V. Kohar, K. Murali, S. Sinh. Enhanced logical stochastic resonance under periodic forcing [J], Communications in Nonlinear Science and Numerical Simulation, 2014, 19 (8): 2866–2873.
[9]
Len Yonggang, Wang Taiyong. Numerical Research of Twice Sampling Stochastic for The detection of A Weak Signal Submerged in A Heavy Noise [J]. Acta Phisica Sinica, 2003, 52, 10, 2432-2437.
[10]
V. Kohar, K. Murali, S. Sinh. Enhanced logical stochastic resonance under periodic forcing [J], Communications in Nonlinear Science and Numerical Simulation, 2014, 19 (8): 2866–2873.
ADDRESS
Science Publishing Group
1 Rockefeller Plaza,
10th and 11th Floors,
New York, NY 10020
U.S.A.
Tel: (001)347-983-5186