Permanent Magnet Synchronous Motor Driving Mechanical Transmission Fault Detection and Identification: A Model-Based Diagnosis Approach
This paper presents a model-based scheme for permanent magnet synchronous motor (PMSM) driving transmission fault detection and identification (FDI) in a steady-state condition. The proposed framework utilizes a PMSM state-space model and an approximated transmission model to construct the regressio...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-04-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/9/1356 |
| _version_ | 1797505177356337152 |
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| author | Widagdo Purbowaskito Po-Yan Wu Chen-Yang Lan |
| author_facet | Widagdo Purbowaskito Po-Yan Wu Chen-Yang Lan |
| author_sort | Widagdo Purbowaskito |
| collection | DOAJ |
| description | This paper presents a model-based scheme for permanent magnet synchronous motor (PMSM) driving transmission fault detection and identification (FDI) in a steady-state condition. The proposed framework utilizes a PMSM state-space model and an approximated transmission model to construct the regression models for parameter estimation using the Recursive Least-Square (RLS) algorithm. The FDI are accomplished by the residual current spectrum thresholding method to assess the fault characteristic frequency magnitude and also by parameter clustering. Two types of mechanical transmission with three different fault conditions are tested in the experiments. As a preliminary effort in the condition monitoring of PMSM driving transmission, the study results demonstrate a promising approach by considering both residual current spectrum and parameter cluster, which achieved a satisfactory decision making in detecting and identifying the faulty condition. |
| first_indexed | 2024-03-10T04:14:52Z |
| format | Article |
| id | doaj.art-409f9ceb2d0b4a559a585ead983ba587 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T04:14:52Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-409f9ceb2d0b4a559a585ead983ba5872023-11-23T08:02:24ZengMDPI AGElectronics2079-92922022-04-01119135610.3390/electronics11091356Permanent Magnet Synchronous Motor Driving Mechanical Transmission Fault Detection and Identification: A Model-Based Diagnosis ApproachWidagdo Purbowaskito0Po-Yan Wu1Chen-Yang Lan2Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10607, TaiwanDepartment of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10607, TaiwanDepartment of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 10607, TaiwanThis paper presents a model-based scheme for permanent magnet synchronous motor (PMSM) driving transmission fault detection and identification (FDI) in a steady-state condition. The proposed framework utilizes a PMSM state-space model and an approximated transmission model to construct the regression models for parameter estimation using the Recursive Least-Square (RLS) algorithm. The FDI are accomplished by the residual current spectrum thresholding method to assess the fault characteristic frequency magnitude and also by parameter clustering. Two types of mechanical transmission with three different fault conditions are tested in the experiments. As a preliminary effort in the condition monitoring of PMSM driving transmission, the study results demonstrate a promising approach by considering both residual current spectrum and parameter cluster, which achieved a satisfactory decision making in detecting and identifying the faulty condition.https://www.mdpi.com/2079-9292/11/9/1356condition monitoringfault diagnosismechanical transmissionmodel-based diagnosisparameter clusteringPMSM |
| spellingShingle | Widagdo Purbowaskito Po-Yan Wu Chen-Yang Lan Permanent Magnet Synchronous Motor Driving Mechanical Transmission Fault Detection and Identification: A Model-Based Diagnosis Approach Electronics condition monitoring fault diagnosis mechanical transmission model-based diagnosis parameter clustering PMSM |
| title | Permanent Magnet Synchronous Motor Driving Mechanical Transmission Fault Detection and Identification: A Model-Based Diagnosis Approach |
| title_full | Permanent Magnet Synchronous Motor Driving Mechanical Transmission Fault Detection and Identification: A Model-Based Diagnosis Approach |
| title_fullStr | Permanent Magnet Synchronous Motor Driving Mechanical Transmission Fault Detection and Identification: A Model-Based Diagnosis Approach |
| title_full_unstemmed | Permanent Magnet Synchronous Motor Driving Mechanical Transmission Fault Detection and Identification: A Model-Based Diagnosis Approach |
| title_short | Permanent Magnet Synchronous Motor Driving Mechanical Transmission Fault Detection and Identification: A Model-Based Diagnosis Approach |
| title_sort | permanent magnet synchronous motor driving mechanical transmission fault detection and identification a model based diagnosis approach |
| topic | condition monitoring fault diagnosis mechanical transmission model-based diagnosis parameter clustering PMSM |
| url | https://www.mdpi.com/2079-9292/11/9/1356 |
| work_keys_str_mv | AT widagdopurbowaskito permanentmagnetsynchronousmotordrivingmechanicaltransmissionfaultdetectionandidentificationamodelbaseddiagnosisapproach AT poyanwu permanentmagnetsynchronousmotordrivingmechanicaltransmissionfaultdetectionandidentificationamodelbaseddiagnosisapproach AT chenyanglan permanentmagnetsynchronousmotordrivingmechanicaltransmissionfaultdetectionandidentificationamodelbaseddiagnosisapproach |