Title :
Fault Diagnosis of Induction Motor Based on Artificial Immune System
Author :
Yuan, Gui-li ; Qin, Shi-wei ; Zhang, Jian
Author_Institution :
Control & Comput. Eng., North China Electr. Power Univ., Beijing, China
Abstract :
Based on principles of artificial immune systems, this paper put forward a fault diagnosis method for induction motor. Compared to the traditional negative selection algorithm, this method is added dynamic detector radius variation and immune memory cells, and improved the fault diagnosis detection rate for induction motor. Through simulation and testing, the validity of this method is proved.
Keywords :
artificial immune systems; fault diagnosis; induction motors; artificial immune system; dynamic detector radius variation; fault diagnosis detection rate; immune memory cells; induction motor fault diagnosis; negative selection algorithm; Detectors; Fault detection; Fault diagnosis; Heuristic algorithms; Immune system; Induction motors; Vectors; Artificial immune system; fault diagnosis; induction motor; negative selection;
Conference_Titel :
Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4673-1450-3
DOI :
10.1109/ICICEE.2012.51
