DocumentCode
2287654
Title
Induction Machine Fault Identification using Particle Swarm Algorithms
Author
Etny, S.A. ; Acarlney, P.P. ; Zahawi, B. ; Giaouris, D.
Author_Institution
Sch. of Electr. & Comput. Eng., Newcastle Univ.
fYear
2006
fDate
12-15 Dec. 2006
Firstpage
1
Lastpage
4
Abstract
The principles of a new technique using particle swarm algorithms for condition monitoring of the stator and rotor circuits of an induction machine is described in this paper. Using terminal voltage and current data, the stochastic optimization technique is able to indicate the presence of a fault and provide information about the location and nature of the fault. The technique is demonstrated using experimental data from a laboratory machine with both stator and rotor winding faults.
Keywords
asynchronous machines; condition monitoring; fault location; particle swarm optimisation; stochastic programming; condition monitoring; fault identification; fault location; induction machine; particle swarm algorithm; stochastic optimization; Circuit faults; Condition monitoring; Fault diagnosis; Induction machines; Laboratories; Machine windings; Particle swarm optimization; Stator windings; Stochastic processes; Voltage; Condition monitoring; induction machine; stochastic optimization; swarm algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Electronics, Drives and Energy Systems, 2006. PEDES '06. International Conference on
Conference_Location
New Delhi
Print_ISBN
0-7803-9772-X
Electronic_ISBN
0-7803-9772-X
Type
conf
DOI
10.1109/PEDES.2006.344310
Filename
4148017
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