Abstract
In the aerospace and military fields, with high reliability requirements, the dual-redundancy permanent magnet synchronous motor (DRPMSM) with weak thermal coupling and no electromagnetic coupling is needed. A common fault in the DRPMSM is the inter-turn short circuit fault (ISCF). However, research on how to diagnose ISCF and the set of faulty windings in the DRPMSM is lacking. In this paper, the structure of the DRPMSM is analyzed and mathematical models of the motor under normal and faulty conditions are established. Then an on-line ISCF detection scheme, which depends on the running modes of the DRPMSM and the average values for the difference of the d-axis voltages between two sets of windings in the latest 20 sampling periods, is proposed. The main contributions of this paper are to analyze the calculation for the inductance of each part of the stator windings and propose the on-line diagnosis method of the ISCF under various operating conditions. The simulation and experimental results show that the proposed method can quickly and effectively diagnose ISCF and determine the set of faulty windings of the DRPMSM.
Highlights
Permanent magnet synchronous motors have a lot of advantages, such as high power density, high efficiency and simple structure, and they have been widely applied in various fields [1,2,3,4].In some important control applications with high reliability requirements, multiphase permanent magnet synchronous motors (PMSMs), such as five-phase PMSMs and six-phase PMSMs, are widely used
The dual-redundancy permanent magnet synchronous motor (DRPMSM) with weak thermal coupling and no electromagnetic coupling is analyzed in this paper, which is equivalent to a six-phase
ISCFsmethods of motors non-stationary conditions, but these methods set of faulty windings in DRPMSMs online under various operation conditions, a novel diagnosis are all based on stator currents
Summary
Permanent magnet synchronous motors have a lot of advantages, such as high power density, high efficiency and simple structure, and they have been widely applied in various fields [1,2,3,4]. In [19], a wavelet approach was proposed to diagnose the occurrence and severity of ISCFs in three-phase induction motors through characteristic patterns These patterns were caused by fault components which were acquired through discrete wavelet transform (DWT) for stator currents. Referencesoperation [27,28,29] presented methods for the diagnosing the ISCFs magnet of motors under under varying speed and load conditions, an adaptive algorithm based on extracting non-stationary non-stationary operation conditions. The locate discrete wavelet energy related the fault was generated by the DWT of was adopted to detect and ISCFs in induction motors to under non-stationary operation conditions. ISCFsmethods of motors non-stationary conditions, but these methods set of faulty windings in DRPMSMs online under various operation conditions, a novel diagnosis are all based on stator currents.
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