DocumentCode :
2841419
Title :
Fault diagnosis algorithm based on artificial immune mechanism
Author :
Xinying, Xu ; Xiaoming, Han ; Jun, Xie ; Keming, Xie
Author_Institution :
Coll. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan, China
fYear :
2009
fDate :
17-19 June 2009
Firstpage :
5314
Lastpage :
5317
Abstract :
In recent years, there has been a growth of investigation into the use of artificial immune system as a source of inspiration and metaphor for computational tasks. In this paper, we present a fault diagnosis algorithm based on artificial immune mechanism that can execute multi-point parallel search from local to global searching field and increase the diversity of antigen population and the ability of searching maximum. At last, we apply this algorithm to the fault diagnosis system. Simulation studies show that the proposed method is feasible and recognize the fault correctly.
Keywords :
artificial immune systems; artificial intelligence; fault diagnosis; genetic algorithms; query formulation; antigen population; artificial immune mechanism; fault diagnosis algorithm; maximum searching; multi-point parallel search; Artificial immune systems; Artificial intelligence; Artificial neural networks; Automatic control; Biological system modeling; Computer networks; Fault diagnosis; Immune system; Mathematical model; Mathematics; Artificial Immune Mechanism; Artificial Intelligence; Fault Diagnosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
Type :
conf
DOI :
10.1109/CCDC.2009.5195058
Filename :
5195058
Link To Document :
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