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Research on Electronic Equipment Fault Diagnosis Based on Improved BP Algorithm

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1 Author(s)
Dong-sheng Xu ; Coll. of Inf. Eng., Yulin Univ., Yulin, China

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.

Published in:

Machine Learning and Computing (ICMLC), 2010 Second International Conference on

Date of Conference:

9-11 Feb. 2010