Please wait a minute...
Chin. Phys. B, 2022, Vol. 31(7): 070503    DOI: 10.1088/1674-1056/ac4228
GENERAL Prev   Next  

Research and application of stochastic resonance in quad-stable potential system

Li-Fang He(贺利芳), Qiu-Ling Liu(刘秋玲), and Tian-Qi Zhang(张天骐)
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications(CQUPT), Chongqing 400065, China
Abstract  To solve the problem of low weak signal enhancement performance in the quad-stable system, a new quad-stable potential stochastic resonance (QSR) is proposed. Firstly, under the condition of adiabatic approximation theory, the stationary probability distribution (SPD), the mean first passage time (MFPT), the work (W), and the power spectrum amplification factor (SAF) are derived, and the impacts of system parameters on them are also extensively analyzed. Secondly, numerical simulations are performed to compare QSR with the classical Tri-stable stochastic resonance (CTSR) by using the genetic algorithm (GA) and the fourth-order Runge-Kutta algorithm. It shows that the signal-to-noise ratio (SNR) and mean signal-to-noise increase (MSNRI) of QSR are higher than CTSR, which indicates that QSR has superior noise immunity than CTSR. Finally, the two systems are applied in the detection of real bearing faults. The experimental results show that QSR is superior to CTSR, which provides a better theoretical significance and reference value for practical engineering application.
Keywords:  bearing fault detection      QSR      weak signal detection      SAF      W  
Received:  19 October 2021      Revised:  16 November 2021      Accepted manuscript online:  11 December 2021
PACS:  05.40.-a (Fluctuation phenomena, random processes, noise, and Brownian motion)  
  05.45.-a (Nonlinear dynamics and chaos)  
  05.40.Fb (Random walks and Levy flights)  
  02.60.Cb (Numerical simulation; solution of equations)  
Fund: Project supported by the National Natural Science Foundation of China (Grant No. 61771085) and the Research Project of Chongqing Educational Commission (Grant Nos. KJ1600407 and KJQN201900601).
Corresponding Authors:  Qiu-Ling Liu     E-mail:

Cite this article: 

Li-Fang He(贺利芳), Qiu-Ling Liu(刘秋玲), and Tian-Qi Zhang(张天骐) Research and application of stochastic resonance in quad-stable potential system 2022 Chin. Phys. B 31 070503

[1] Li M D, Shi P M, Zhang W Y and Han D Y 2021 Chaos, Solitons and Fractals 151 111228
[2] Zhang L, Lai L, Peng H, Tu Z and Zhong S H 2018 Phys. Rev. E 97 012147
[3] Emanuel M, Miguel R G, Manuel C, Holger T G, Zhang Y H and Luis L B 2018 Phys. Rev. Lett. 121 086805
[4] Xie M, Fan B, He X and Chen Q Q 2018 Phys. Rev. E 98 052202
[5] Zamani A P, Novikov N and Gutkin B 2019 Commun. Nonlinear Sci. Num. Simul. 82 105024
[6] Singh M, Verma A and Sharma N 2018 Innovation and Research in Biomedical en 39 334
[7] Bai C Y 2018 Physica A 507 304
[8] Evstigneev M, Pankov V and Prince R H 2001 J. Phys. A:Gen. Phys. 34 2595
[9] Nurujjaman Md, Sekar Iyengar A N, Parmananda P 2008 Phys. Rev. E 78 026406
[10] He L, Wu X, Zhang G 2019 Physica A:Statistical Mechanics and its Applications 545
[11] Liu Z P, Zhang J, Özdemir Ş K, Peng B, Jing H, Lü X Y, Li C W, Yang L, Nori F and Liu Y X 2016 Phys. Rev. Lett. 117 110802
[12] Van der Groen Onno and Wenderoth Nicole 2016 The Journal of Neuroscience 36 5289
[13] R Benzi, A Sutera and A Vulpiani 1999 J. Phys. A 14 L453
[14] Gammaitoni, Marchesoni, Menichella-Saetta and Santucci 1989 Phys. Rev. Lett. 62 349
[15] Benzi R and Parisi G 2012 Sutera A
[16] McNamara and Wiesenfeld 1989 Phys. Rev. A 39 4854
[17] Cheng Z, Hu N and Zuo M 2012 J. Phys. Conference 364 012076
[18] Dykman M I, Luchinsky D G, Mannella R and Mcclintock PVE 1993 J. Statist. Phys. 70 463
[19] Hanggi, Mroczkowski, Moss, McClintock 1985 Phys. Rev. A 32 695
[20] Jung P and Hänggi P 1989 Europhys. Lett. 8 505
[21] Jung Hänggi 1991 Phys. Rev. A 44 8032
[22] Baomin Dai, Minxia Li and Yitai Ma 2014 Appl. Thermal Eng. 67 283
[23] Liu J, Hu B, Yang F and Zang C L 2020 Commun. Nonlinear Sci. Num. Simul. 85 105245
[24] Moreno Miguel V, Barci Daniel G and Arenas Zochil González 2020 Phys. Rev. E 101 062110
[25] Xu L, Yu T, Lai L et al. 2020 Commun. Nonlinear Sci. Num. Simul. 83 105133
[26] He L F, Cao L, Zhang G and Yi T 2018 Chin. J. Phys. 56 1588
[27] Wang H, Obenauer-Kutner L and Lin M 2008 J. Am. Chem. Soc. 130 8154
[28] Qiao Z J, Liu J, Ma X and Liu J L 2021 Journal of the Franklin Institute 358 2194
[29] Lei Y, Qiao Z and Xu X 2017 Mechanical Systems and Signal Processing 94 148
[30] He L F, Tan C L and Zhang G 2021 The European Physical Journal Plus 136 1
[31] Sacco R L, Freddo L and Bello J A 1993 W Archives of Neurology 50 609
[32] Ergin Y, Veli B, Matja P 2016 Sci. China- Technological Sciences 59 364
[33] Jiao S B, Lei S, Jiang W, Zhang Q and Huang W C 2019 IEEE Access 7 160191
[34] Morizono H, Ohishii Y and Yamamoto Y 2001 J. Jpn. Soc. Clin. Cytol 40 500
[35] Zhang G, Wang H and Zhang T Q 2021 Fluctuation and Noise Letters 20 2150045
[36] Qiao Z J, Elhattab A, Shu X D and He C B 2021 Nonlinear Dynamics 106 707
[37] Lei Y G, Qiao Z J, Xu X F and Lin J 2017 Mechanical Systems and Signal Processing 94 148
[38] Qiao Z J, Liu J, Xu X, Yin A M and Shu X D 2021 Rev. Sci. Instrum. 92 105102
[39] Liu J J, Leng Y G, Fan S B et al. 2017 American Society of Mechanical Engineers 58226 V008T12A045
[40] Cheng W, Xu X M, Ding Y P and Sun K H 2020 Rev. Sci. Instrum. 91 064701
[41] Zhang G, Tan C and He L 2021 Mod. Phys. Lett. B 35 2150280
[42] Li J, Zhang J and Li M 2019 Mechanical Systems & Signal Processing 114 128
[43] He L F, Hu D Y, Zhang G and Lu S L 2019 Mod. Phys. Lett. B 33 19
[1] Simulation of single bubble dynamic process in pool boiling process under microgravity based on phase field method
Chang-Sheng Zhu(朱昶胜), Bo-Rui Zhao(赵博睿), Yao Lei(雷瑶), and Xiu-Ting Guo(郭秀婷). Chin. Phys. B, 2023, 32(4): 044702.
[2] Mechanical enhancement and weakening in Mo6S6 nanowire by twisting
Ke Xu(徐克), Yanwen Lin(林演文), Qiao Shi(石桥), Yuequn Fu(付越群), Yi Yang(杨毅),Zhisen Zhang(张志森), and Jianyang Wu(吴建洋). Chin. Phys. B, 2023, 32(4): 046204.
[3] SiC gate-controlled bipolar field effect composite transistor with polysilicon region for improving on-state current
Baoxing Duan(段宝兴), Kaishun Luo(罗开顺), and Yintang Yang(杨银堂). Chin. Phys. B, 2023, 32(4): 047702.
[4] First-principles study of the bandgap renormalization and optical property of β-LiGaO2
Dangqi Fang(方党旗). Chin. Phys. B, 2023, 32(4): 047101.
[5] Conductive path and local oxygen-vacancy dynamics: Case study of crosshatched oxides
Z W Liang(梁正伟), P Wu(吴平), L C Wang(王利晨), B G Shen(沈保根), and Zhi-Hong Wang(王志宏). Chin. Phys. B, 2023, 32(4): 047303.
[6] Meshfree-based physics-informed neural networks for the unsteady Oseen equations
Keyi Peng(彭珂依), Jing Yue(岳靖), Wen Zhang(张文), and Jian Li(李剑). Chin. Phys. B, 2023, 32(4): 040208.
[7] Precision measurement and suppression of low-frequency noise in a current source with double-resonance alignment magnetometers
Jintao Zheng(郑锦韬), Yang Zhang(张洋), Zaiyang Yu(鱼在洋), Zhiqiang Xiong(熊志强), Hui Luo(罗晖), and Zhiguo Wang(汪之国). Chin. Phys. B, 2023, 32(4): 040601.
[8] Diffraction deep neural network based orbital angular momentum mode recognition scheme in oceanic turbulence
Hai-Chao Zhan(詹海潮), Bing Chen(陈兵), Yi-Xiang Peng(彭怡翔), Le Wang(王乐), Wen-Nai Wang(王文鼐), and Sheng-Mei Zhao(赵生妹). Chin. Phys. B, 2023, 32(4): 044208.
[9] Drift characteristics and the multi-field coupling stress mechanism of the pantograph-catenary arc under low air pressure
Zhilei Xu(许之磊), Guoqiang Gao(高国强), Pengyu Qian(钱鹏宇), Song Xiao(肖嵩), Wenfu Wei(魏文赋), Zefeng Yang(杨泽锋), Keliang Dong(董克亮), Yaguang Ma(马亚光), and Guangning Wu(吴广宁). Chin. Phys. B, 2023, 32(4): 045202.
[10] Prediction of lattice thermal conductivity with two-stage interpretable machine learning
Jinlong Hu(胡锦龙), Yuting Zuo(左钰婷), Yuzhou Hao(郝昱州), Guoyu Shu(舒国钰), Yang Wang(王洋), Minxuan Feng(冯敏轩), Xuejie Li(李雪洁), Xiaoying Wang(王晓莹), Jun Sun(孙军), Xiangdong Ding(丁向东), Zhibin Gao(高志斌), Guimei Zhu(朱桂妹), Baowen Li(李保文). Chin. Phys. B, 2023, 32(4): 046301.
[11] Abnormal magnetic behavior of prussian blue analogs modified with multi-walled carbon nanotubes
Jia-Jun Mo(莫家俊), Pu-Yue Xia(夏溥越), Ji-Yu Shen(沈纪宇), Hai-Wen Chen(陈海文), Ze-Yi Lu(陆泽一), Shi-Yu Xu(徐诗语), Qing-Hang Zhang(张庆航), Yan-Fang Xia(夏艳芳), Min Liu(刘敏). Chin. Phys. B, 2023, 32(4): 047503.
[12] Tunable phonon-atom interaction in a hybrid optomechanical system
Yao Li(李耀), Chuang Li(李闯), Jiandong Zhang(张建东),Ying Dong(董莹), and Huizhu Hu(胡慧珠). Chin. Phys. B, 2023, 32(4): 044213.
[13] Modeling of thermal conductivity for disordered carbon nanotube networks
Hao Yin(殷浩), Zhiguo Liu(刘治国), and Juekuan Yang(杨决宽). Chin. Phys. B, 2023, 32(4): 044401.
[14] Super-resolution reconstruction algorithm for terahertz imaging below diffraction limit
Ying Wang(王莹), Feng Qi(祁峰), Zi-Xu Zhang(张子旭), and Jin-Kuan Wang(汪晋宽). Chin. Phys. B, 2023, 32(3): 038702.
[15] Application of the body of revolution finite-element method in a re-entrant cavity for fast and accurate dielectric parameter measurements
Tianqi Feng(冯天琦), Chengyong Yu(余承勇), En Li(李恩), and Yu Shi(石玉). Chin. Phys. B, 2023, 32(3): 030101.
No Suggested Reading articles found!