Circuit Failure Diagnosis Analysis and Research Based On Neural Network

For the better analysis of failure diagnosis problems, firstly, using MATLAB software to simulate failure problems such as the emergence of regular power, short circuit and broken circuit. Combining the failure practical example, neural network analysis is introduced for diagnosis. Failure diagnosis...

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Bibliographic Details
Published in2008 International Symposium on Electronic Commerce and Security pp. 209 - 212
Main Authors Wenzhe Qi, Chenghui Yang, Jianjun Meng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2008
Subjects
Analytical models
Artificial neural networks
BP network
Circuit faults
Convergence
Elman network
failure diagnosis
Integrated circuit modeling
Testing
Training
training simulation
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Summary:For the better analysis of failure diagnosis problems, firstly, using MATLAB software to simulate failure problems such as the emergence of regular power, short circuit and broken circuit. Combining the failure practical example, neural network analysis is introduced for diagnosis. Failure diagnosis using two kinds of neural networks: the BP network and Elman network training. Trainings choose rational network design parameters, training functions and the simulation realizes practical results analysis. Then, through the comparative analysis of two network training simulation and testing results, the results conclude that Elman network training avoiding the slower pace shortcoming in BP network training. But there are still existing deficiencies. At last, the improved methods and measures provided better parameters set for the power failure diagnosis is presented.
ISBN:9780769532585
0769532586
DOI:10.1109/ISECS.2008.151