An improved bistable stochastic resonance method and its application in early bearing fault diagnosis
Abstract In the field of bearing fault diagnosis, the phenomenon of stochastic resonance (SR) has been proven to effectively utilize noise to enhance weak features of early faults. The classical bistable stochastic resonance (CBSR) model, as one of the most widely applied SR methods, faces limitatio...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-01889-0 |
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| author | Yonghui Zhao Anqi Jiang Wanlu Jiang Enyu Tang Xu Jiang Xiaoyang Gu |
| author_facet | Yonghui Zhao Anqi Jiang Wanlu Jiang Enyu Tang Xu Jiang Xiaoyang Gu |
| author_sort | Yonghui Zhao |
| collection | DOAJ |
| description | Abstract In the field of bearing fault diagnosis, the phenomenon of stochastic resonance (SR) has been proven to effectively utilize noise to enhance weak features of early faults. The classical bistable stochastic resonance (CBSR) model, as one of the most widely applied SR methods, faces limitations in feature enhancement due to the complexity of parameter tuning and the issue of output saturation. To address these issues, this paper proposes an improved piecewise unsaturated bistable stochastic resonance (PUBSR) method, which employs an asymmetric potential function to effectively mitigate the output saturation problem of CBSR. Additionally, the cuckoo search (CS) algorithm is used to optimize the potential function parameters, enhancing fault diagnosis performance. Finally, the proposed method is applied to both simulated signals and early bearing fault engineering data. The results demonstrate that compared to the CBSR method, the proposed approach more than doubles the spectral peak value when extracting characteristic frequencies, significantly improving the identifiability of fault features and diagnostic accuracy. |
| format | Article |
| id | doaj-art-0adea0a7f5094d56b3e791b4ac87b24b |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-0adea0a7f5094d56b3e791b4ac87b24b2025-08-20T03:45:28ZengNature PortfolioScientific Reports2045-23222025-07-0115111710.1038/s41598-025-01889-0An improved bistable stochastic resonance method and its application in early bearing fault diagnosisYonghui Zhao0Anqi Jiang1Wanlu Jiang2Enyu Tang3Xu Jiang4Xiaoyang Gu5Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control, Yanshan UniversitySchool of Electrical Engineering, Yanshan UniversityHebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control, Yanshan UniversityHebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control, Yanshan UniversityHebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control, Yanshan UniversityHebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control, Yanshan UniversityAbstract In the field of bearing fault diagnosis, the phenomenon of stochastic resonance (SR) has been proven to effectively utilize noise to enhance weak features of early faults. The classical bistable stochastic resonance (CBSR) model, as one of the most widely applied SR methods, faces limitations in feature enhancement due to the complexity of parameter tuning and the issue of output saturation. To address these issues, this paper proposes an improved piecewise unsaturated bistable stochastic resonance (PUBSR) method, which employs an asymmetric potential function to effectively mitigate the output saturation problem of CBSR. Additionally, the cuckoo search (CS) algorithm is used to optimize the potential function parameters, enhancing fault diagnosis performance. Finally, the proposed method is applied to both simulated signals and early bearing fault engineering data. The results demonstrate that compared to the CBSR method, the proposed approach more than doubles the spectral peak value when extracting characteristic frequencies, significantly improving the identifiability of fault features and diagnostic accuracy.https://doi.org/10.1038/s41598-025-01889-0Stochastic resonanceCuckoo searchRolling bearingEarly fault diagnosis |
| spellingShingle | Yonghui Zhao Anqi Jiang Wanlu Jiang Enyu Tang Xu Jiang Xiaoyang Gu An improved bistable stochastic resonance method and its application in early bearing fault diagnosis Scientific Reports Stochastic resonance Cuckoo search Rolling bearing Early fault diagnosis |
| title | An improved bistable stochastic resonance method and its application in early bearing fault diagnosis |
| title_full | An improved bistable stochastic resonance method and its application in early bearing fault diagnosis |
| title_fullStr | An improved bistable stochastic resonance method and its application in early bearing fault diagnosis |
| title_full_unstemmed | An improved bistable stochastic resonance method and its application in early bearing fault diagnosis |
| title_short | An improved bistable stochastic resonance method and its application in early bearing fault diagnosis |
| title_sort | improved bistable stochastic resonance method and its application in early bearing fault diagnosis |
| topic | Stochastic resonance Cuckoo search Rolling bearing Early fault diagnosis |
| url | https://doi.org/10.1038/s41598-025-01889-0 |
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