Interturn Fault Diagnosis in Sensorless PMSM Drive Based on Negative-Sequence Reactive Power Distortions
Stator interturn fault (ITF) is the most common failure in electrical machines; if no prompt detection is implemented, it can cause catastrophic results. This work proposes a novel method in permanent magnet synchronous machine (PMSM) drives to detect the ITF, which is insular to speed and load variations. The proposed ITF technique is based on negative-sequence instantaneous reactive power (IRP) distortions. The sensorless control of the PMSM drive, while using field-oriented technique, uses the voltage and current information for rotor position estimation. This serves the dual purpose of controlling the drive and also in developing the diagnostic technique. The IRP distortion is calculated from dq-reference frame voltage distortions, which are estimated using Luenberger observer and dq-reference frame current distortions. The novel fault indicator is calculated based on the vector magnitude of dc components obtained from negative-sequence IRP distortions, which is insular to various speed and load conditions of the drive. The proposed ITF detection technique is experimentally validated under varying load and speed conditions of the sensorless field-oriented controlled (FOC) PMSM drive. Further, a comparison of the proposed ITF detection scheme with the dq-reference frame current residuals technique shows the superiority of the proposed ITF detection scheme under various speed and load conditions of the PMSM drive scheme; furthermore, the reliability of the proposed ITF detection technique under various noise conditions is also verified.
Authors
- Jeevanand Seshadrinath (ORCID: https://orcid.org/0000-0002-2072-7317)
- Shivateja Manala (ORCID: https://orcid.org/0000-0001-7873-0298)
Institutions
- Indian Institute of Technology Roorkee (IN)
Publication Details
- Journal
- Canadian Journal of Electrical and Computer Engineering
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/icjece.2025.3573736
- Citations
- 1
- Primary Topic
- Machine Fault Diagnosis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- Department of Science and Technology, Government of Kerala