Fault Detection of Stator Winding Interturn Short Circuit in PMSM Based on Wavelet Packet Analysis

Author(s):  
Zheng An Ping ◽  
Yang Juan ◽  
Wang Ling
2012 ◽  
Vol 529 ◽  
pp. 37-42 ◽  
Author(s):  
Jun Yong Sang ◽  
Chen Hao ◽  
Peng Chao Wang

Aiming at the problem of the traditional stator current frequency spectrum analysis method cannot completely guarantee the accurate identification of stator winding inter-turn faults,the diagnosis method of stator winding inter-turn based on wavelet packet analysis (WPA) and Back Propagation (BP) neural network is put forward. The finite element model of the three-phase asynchronous motor which is based on Magnet is established, and analysis the magnetic flux density and current of the motor through simulation in normal and in the situation of short-circuit fault of stator winding inter-turn, the current signal of stator is analysised by wavelet packet , and the feature vector of frequency band energy is extracted as the basis to judge the state of induction motor running, and the motor state is identified by BP neural network, and the mapping from feature vector to the motor state is established. Simulation results show that: The diagnosis system of inter-turn fault based on WPA and BP neural network can effectively identify short-circuit fault between ratios. This is to say that the method has a high fault diagnosis rate.


2004 ◽  
Vol 14 (3) ◽  
pp. 161-174 ◽  
Author(s):  
Andoni Lazkano ◽  
Jesus Ruiz ◽  
Elisabete Aramendi ◽  
Luis A. Leturiondo

2018 ◽  
Vol 8 (9) ◽  
pp. 1677 ◽  
Author(s):  
Hong Liang ◽  
Yong Chen ◽  
Siyuan Liang ◽  
Chengdong Wang

The stator inter-turn short circuit fault is one of the most common and key faults in permanent magnet synchronous motor (PMSM). This paper introduces a time–frequency method for inter-turn fault detection in stator winding of PMSM using improved wavelet packet transform. Both stator current signal and vibration signal are used for the detection of short circuit faults. Two different experimental data from a three-phase PMSM were processed and analyzed by this time–frequency method in LabVIEW. The feasibility of this approach is shown by the experimental test.


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