Improvement and Application of a Real-timing Analog Circuit Fault Diagnosis Method

The paper first makes a thorough research on the method for analog circuit fault diagnosis based on kurtosis and negentropy, and then theoretically analyses it's advantage and disadvantage, which is followed by introducing the idea of centroid to overcome the method's shortcoming, making t...

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Bibliographic Details
Published in2011 Fourth International Conference on Intelligent Computation Technology and Automation Vol. 1; pp. 155 - 158
Main Authors Zheng Hongyan, Li Hongbo, Zeng Fanjing, Li Tiefeng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2011
Subjects
Analog circuits
Artificial neural networks
centroid
Circuit faults
Data mining
Fault diagnosis
Feature extraction
kurtosis
negentropy
neural network
real-timing
Training
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Summary:The paper first makes a thorough research on the method for analog circuit fault diagnosis based on kurtosis and negentropy, and then theoretically analyses it's advantage and disadvantage, which is followed by introducing the idea of centroid to overcome the method's shortcoming, making the improved method can extract the signal's feature more efficiency. Finally, it applies the improved method to an actual circuit. The simulation result shows that the improved method not only improves the fault diagnosis ratio of neural network but also can be used in the real-timing condition such as online fault diagnosis.
ISBN:1612842895
9781612842899
DOI:10.1109/ICICTA.2011.47