DocumentCode :
2313803
Title :
Research on Electronic Equipment Fault Diagnosis Based on Improved BP Algorithm
Author :
Xu, Dong-Sheng
Author_Institution :
Coll. of Inf. Eng., Yulin Univ., Yulin, China
fYear :
2010
fDate :
9-11 Feb. 2010
Firstpage :
130
Lastpage :
134
Abstract :
It is increasingly difficult for the traditional fault diagnosis technologies to meet the complex and automation requirements of electronic equipments, so the combination of artificial intelligence technology has become a development direction of fault diagnosis. In the fault diagnosis, BP neural network has also been widely used. As for the deficiency of BP network, the paper presented an improved BP network dynamic parameter adjust algorithm and applied it in the research of electronic equipment fault diagnosis. Proved theoretically and practically, the method can effectively overcome the deficiency of standard BP algorithm, and provides efficient way for the fault diagnosis of electronic equipments.
Keywords :
artificial intelligence; backpropagation; electronic engineering computing; electronic equipment testing; fault diagnosis; neural nets; BP network dynamic parameter adjust algorithm; BP neural network; artificial intelligence technology; electronic equipment fault diagnosis; Algorithm design and analysis; Artificial intelligence; Artificial neural networks; Automation; Electronic equipment; Fault diagnosis; Heuristic algorithms; History; Neural networks; Working environment noise; BP algorithm; dynamic parameter; electronic equipment; fault diagnosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Computing (ICMLC), 2010 Second International Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-1-4244-6006-9
Electronic_ISBN :
978-1-4244-6007-6
Type :
conf
DOI :
10.1109/ICMLC.2010.14
Filename :
5460755
Link To Document :
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