Detecting of Multi Phase Inter Turn Short Circuit in the Five Permanent Magnet Synchronous Motor

2016 ◽  
Vol 17 (5) ◽  
pp. 583-595 ◽  
Author(s):  
N. Yassa ◽  
M. Rachek ◽  
A. Djerdir ◽  
M. Becherif

Abstract This paper proposes a general model of five phase permanent magnet synchronous machine (PMSM) which is capable of representing the multiphase Inter Turn Short Circuit (ITSC) occurring in several phase simultaneously this model is based on a coupled magnetic circuit approach leading to a differential equations system goveming the induction machine behavior. The obtained time-differential state equations system is implemented under Matlab environment and numerically solved using the fourth order Rung-Kutta method with variable step time corrected at each rotor displacement through the electromagnetic torque. Also, Fast Fourier Transform and (FFT) analysis is performed to the phase current signal to detect the frequency spectrum, Power Spectral Density (PSD) is chosen as a classification method. Its efficiency depends on its ability to discriminate between various faults generating the same range of harmonics in the stator current spectrum and on its ability to evaluate the fault severity. So, in order to improve the efficiency of these diagnosis methods, one needs a relatively accurate model to simulate the five-phase PMSM in the case of inter-tum short circuit fault helping to predict performances andor to extract fault signature in the machine main quantities. Simulation work has been carried out using MATLAB to verify the performance of the proposed detection/diagnosis method.

2019 ◽  
Vol 9 (2) ◽  
pp. 224 ◽  
Author(s):  
Siyuan Liang ◽  
Yong Chen ◽  
Hong Liang ◽  
Xu Li

Permanent magnet synchronous motors (PMSM) has the advantages of simple structure, small size, high efficiency, and high power factor, and a key dynamic source and is widely used in industry, equipment and electric vehicle. Aiming at its inter-turn short-circuit fault, this paper proposes a fault diagnosis method based on sparse representation and support vector machine (SVM). Firstly, the sparse representation is used to extract the first and second largest sparse coefficients of both current signal and vibration signals, and then they are composed into four-dimensional feature vectors. Secondly, the feature vectors are input into the support vector machine for fault diagnosis, which is suitable for small sample. Experiments on a permanent magnet synchronous motor with artificially set inter-turn short-circuit fault and a normal one showed that the method is feasible and accurate.


Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 510 ◽  
Author(s):  
Yiguang Chen ◽  
Xiaobin Zhao ◽  
Yukai Yang ◽  
Yichen Shi

The Dual-Redundancy Permanent Magnet Synchronous Motor (DRPMSM) with weak thermal coupling and no electromagnetic coupling among phase windings has two sets of three-phase symmetrical windings. Under normal conditions, two sets of windings can operate simultaneously, and once one set has an inter-turn short circuit fault (ISCF), the other set will operate alone, so a DRPMSM can be applied in fields with high reliability requirements. According to the equivalent circuit principle, a simplified model of a DRPMSM when ISCF occurs is established in this paper, and mathematical equations for the equivalent resistance, inductance and induction electromotive force (EMF) are derived. Based on the simplified circuit principle and instantaneous power theory, combined with the analysis of the fundamental wave in the two sets, an online diagnosis method of the ISCF for DRPMSM is proposed based on the reactive power difference and the feasibility of the method is verified by experiments.


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