Failure Probability Modeling of Miniature DC Motors and Its Application in Fault Diagnosis
This paper proposes a fault diagnosis method for miniature DC motors (MDCMs) in the presence of the uncertainties caused by material and random factors of the production process. In this method, the probability models of fault multiple features are established based on the advantage criterion of the...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2021/9958412 |
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| _version_ | 1832549180571123712 |
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| author | Zhiping Xie Rongchen Zhao Jiming Zheng Yancheng Lang |
| author_facet | Zhiping Xie Rongchen Zhao Jiming Zheng Yancheng Lang |
| author_sort | Zhiping Xie |
| collection | DOAJ |
| description | This paper proposes a fault diagnosis method for miniature DC motors (MDCMs) in the presence of the uncertainties caused by material and random factors of the production process. In this method, the probability models of fault multiple features are established based on the advantage criterion of the maximum overall average membership to determine the distribution of fault multiple features. The fault diagnosis algorithm is synthesized to obtain the threshold ranges of fault multiple features according to different confidence levels. Experimental test results are presented and analyzed to validate the efficiency and performance of the proposed fault diagnosis method. |
| format | Article |
| id | doaj-art-93d7be484d554be0ae3d997a7cfb7edd |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-93d7be484d554be0ae3d997a7cfb7edd2025-02-03T06:12:00ZengWileyShock and Vibration1070-96221875-92032021-01-01202110.1155/2021/99584129958412Failure Probability Modeling of Miniature DC Motors and Its Application in Fault DiagnosisZhiping Xie0Rongchen Zhao1Jiming Zheng2Yancheng Lang3School of Mechanical & Electrical Engineering, Guizhou Normal University, Guiyang 550001, ChinaSchool of Mechanical & Electrical Engineering, Guizhou Normal University, Guiyang 550001, ChinaSchool of Mechanical & Electrical Engineering, Guizhou Normal University, Guiyang 550001, ChinaSchool of Mechanical & Electrical Engineering, Guizhou Normal University, Guiyang 550001, ChinaThis paper proposes a fault diagnosis method for miniature DC motors (MDCMs) in the presence of the uncertainties caused by material and random factors of the production process. In this method, the probability models of fault multiple features are established based on the advantage criterion of the maximum overall average membership to determine the distribution of fault multiple features. The fault diagnosis algorithm is synthesized to obtain the threshold ranges of fault multiple features according to different confidence levels. Experimental test results are presented and analyzed to validate the efficiency and performance of the proposed fault diagnosis method.http://dx.doi.org/10.1155/2021/9958412 |
| spellingShingle | Zhiping Xie Rongchen Zhao Jiming Zheng Yancheng Lang Failure Probability Modeling of Miniature DC Motors and Its Application in Fault Diagnosis Shock and Vibration |
| title | Failure Probability Modeling of Miniature DC Motors and Its Application in Fault Diagnosis |
| title_full | Failure Probability Modeling of Miniature DC Motors and Its Application in Fault Diagnosis |
| title_fullStr | Failure Probability Modeling of Miniature DC Motors and Its Application in Fault Diagnosis |
| title_full_unstemmed | Failure Probability Modeling of Miniature DC Motors and Its Application in Fault Diagnosis |
| title_short | Failure Probability Modeling of Miniature DC Motors and Its Application in Fault Diagnosis |
| title_sort | failure probability modeling of miniature dc motors and its application in fault diagnosis |
| url | http://dx.doi.org/10.1155/2021/9958412 |
| work_keys_str_mv | AT zhipingxie failureprobabilitymodelingofminiaturedcmotorsanditsapplicationinfaultdiagnosis AT rongchenzhao failureprobabilitymodelingofminiaturedcmotorsanditsapplicationinfaultdiagnosis AT jimingzheng failureprobabilitymodelingofminiaturedcmotorsanditsapplicationinfaultdiagnosis AT yanchenglang failureprobabilitymodelingofminiaturedcmotorsanditsapplicationinfaultdiagnosis |