Name
Abstract | ||
|---|---|---|
Permanent Magnet Synchronous Motors (PMSM) are frequently used to high performance applications. Accurate diagnosis of incipient faults can significantly improve system availability and reliability. This paper proposes a new scheme for the automatic diagnosis of turn-to-turn short circuit faults in PMSM stator windings. Both the fault location and fault severity are diagnosed using a particle swarm optimization (PSO) algorithm. The performance of the motor under the fault conditions is simulated through lumped-parameter models. Waveforms of the machine phase currents are monitored, based on which a fitness function is formulated and PSO is used to identify the fault location and fault size. Simulation results in MATLAB provide preliminary verification of the diagnosis scheme. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/IJCNN.2006.246942 | 2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10 |
Keywords | Field | DocType |
fitness function,reliability,synchronous motors | Particle swarm optimization,MATLAB,Synchronous motor,Computer science,Control theory,Waveform,Fitness function,Electromagnetic coil,Stator,Permanent magnet synchronous motor | Conference |
ISSN | Citations | PageRank |
2161-4393 | 2 | 0.58 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li Liu | 1 | 46 | 8.81 |
| David A. Cartes | 2 | 64 | 11.09 |
| Wenxin Liu | 3 | 87 | 15.40 |