Stochastic Resonance of Asymmetric Joint Potential System and Its Application in Weak Signal Detection
Stochastic resonance (SR) as an important nonlinear detection technique has been widely applied in weak signal diagnosis. In order to improve the weak signal processing capability of SR, a new asymmetric SR system with nonlinear jointed potential function is proposed in this paper. Firstly, the new...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9982448/ |
| _version_ | 1811197664102973440 |
|---|---|
| author | Yuan Liu Shao Juan Ma Xiao Yan Ma |
| author_facet | Yuan Liu Shao Juan Ma Xiao Yan Ma |
| author_sort | Yuan Liu |
| collection | DOAJ |
| description | Stochastic resonance (SR) as an important nonlinear detection technique has been widely applied in weak signal diagnosis. In order to improve the weak signal processing capability of SR, a new asymmetric SR system with nonlinear jointed potential function is proposed in this paper. Firstly, the new joint potential stochastic resonance (JPSR) system is built by combined gaussian potential function and asymmetric bistable potential function. Secondly, the analytical expression of signal-to-noise ratio (SNR) is derived based on two-state theory and adiabatic approximation theory. Meanwhile, the influence of system parameters on SNR is discussed theoretically. Thirdly, based on proposed system, various types weak signals with noise are detected more accurately in simulation experiments. Then, by particle swarm optimization algorithm, the JPSR system is applied to detect actual bearing fault signals and the better effects are obtained. Finally, the simulation results show that the proposed system can detect weak signal characteristics more effectively. |
| first_indexed | 2024-04-12T01:17:55Z |
| format | Article |
| id | doaj.art-8e42044a1687444c911601d2079a42c3 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T01:17:55Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8e42044a1687444c911601d2079a42c32022-12-22T03:53:53ZengIEEEIEEE Access2169-35362022-01-011013015513016510.1109/ACCESS.2022.32285499982448Stochastic Resonance of Asymmetric Joint Potential System and Its Application in Weak Signal DetectionYuan Liu0https://orcid.org/0000-0003-2174-5055Shao Juan Ma1https://orcid.org/0000-0003-2810-586XXiao Yan Ma2School of Mathematics and Information Science, North Minzu University, YinChuan, NingXia, ChinaSchool of Mathematics and Information Science, North Minzu University, YinChuan, NingXia, ChinaSchool of Mathematics and Information Science, North Minzu University, YinChuan, NingXia, ChinaStochastic resonance (SR) as an important nonlinear detection technique has been widely applied in weak signal diagnosis. In order to improve the weak signal processing capability of SR, a new asymmetric SR system with nonlinear jointed potential function is proposed in this paper. Firstly, the new joint potential stochastic resonance (JPSR) system is built by combined gaussian potential function and asymmetric bistable potential function. Secondly, the analytical expression of signal-to-noise ratio (SNR) is derived based on two-state theory and adiabatic approximation theory. Meanwhile, the influence of system parameters on SNR is discussed theoretically. Thirdly, based on proposed system, various types weak signals with noise are detected more accurately in simulation experiments. Then, by particle swarm optimization algorithm, the JPSR system is applied to detect actual bearing fault signals and the better effects are obtained. Finally, the simulation results show that the proposed system can detect weak signal characteristics more effectively.https://ieeexplore.ieee.org/document/9982448/Asymmetric joint potential systemstochastic resonancesignal-to-noise ratioparticle swarm optimizationbearing fault diagnosis |
| spellingShingle | Yuan Liu Shao Juan Ma Xiao Yan Ma Stochastic Resonance of Asymmetric Joint Potential System and Its Application in Weak Signal Detection IEEE Access Asymmetric joint potential system stochastic resonance signal-to-noise ratio particle swarm optimization bearing fault diagnosis |
| title | Stochastic Resonance of Asymmetric Joint Potential System and Its Application in Weak Signal Detection |
| title_full | Stochastic Resonance of Asymmetric Joint Potential System and Its Application in Weak Signal Detection |
| title_fullStr | Stochastic Resonance of Asymmetric Joint Potential System and Its Application in Weak Signal Detection |
| title_full_unstemmed | Stochastic Resonance of Asymmetric Joint Potential System and Its Application in Weak Signal Detection |
| title_short | Stochastic Resonance of Asymmetric Joint Potential System and Its Application in Weak Signal Detection |
| title_sort | stochastic resonance of asymmetric joint potential system and its application in weak signal detection |
| topic | Asymmetric joint potential system stochastic resonance signal-to-noise ratio particle swarm optimization bearing fault diagnosis |
| url | https://ieeexplore.ieee.org/document/9982448/ |
| work_keys_str_mv | AT yuanliu stochasticresonanceofasymmetricjointpotentialsystemanditsapplicationinweaksignaldetection AT shaojuanma stochasticresonanceofasymmetricjointpotentialsystemanditsapplicationinweaksignaldetection AT xiaoyanma stochasticresonanceofasymmetricjointpotentialsystemanditsapplicationinweaksignaldetection |