A Model-Based Strategy for Interturn Short-Circuit Fault Diagnosis in PMSM
A model-based method for interturn short-circuit fault detection and isolation in permanent magnet synchronous machines (PMSMs) is proposed in this paper. The fault detection is realized based on a residual current vector (RCV) generated by the difference between the measured stator currents and the...
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Published in | IEEE transactions on industrial electronics (1982) Vol. 64; no. 9; pp. 7218 - 7228 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.09.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | A model-based method for interturn short-circuit fault detection and isolation in permanent magnet synchronous machines (PMSMs) is proposed in this paper. The fault detection is realized based on a residual current vector (RCV) generated by the difference between the measured stator currents and the stator currents estimated by a state observer. In order to avoid false alarms due to possible undesired perturbations, the sequence decomposition of the RCV is performed by employing different reference-frames. Thus, the proposed RCV allows the correct detection of interturn short-circuit faults and quantification of the fault severity in any faulty stator-phase winding. Moreover, since the back-EMF generated by the magnets is proportional to the rotor shaft speed, the electrical angular speed is estimated through the stator voltages measurement, without using a speed sensor. Simulation results from the three-phase PMSM dynamic model that allows considering the interturn short-circuit fault in any stator phase-windings are presented. The proposed method is validated using a three-phase PMSM prototype with modified stator windings. The robustness and the reliability of the proposal was tested for several interturn fault conditions under transient conditions including different disturbances. |
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ISSN: | 0278-0046 1557-9948 |
DOI: | 10.1109/TIE.2017.2688973 |