DocumentCode :
2728219
Title :
Research on Fault Diagnosis in Analog Circuit Based on Wavelet-Neural Network
Author :
Yuan, Haiying ; Chen, Guangju ; Shi, Sanbao ; Chen, Huawei
Author_Institution :
Sch. of Autom. Eng., Univ. of Electron. Sci. & Technol., Chengdu
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
2659
Lastpage :
2662
Abstract :
The fault diagnosis method based on wavelet-neural network in analog circuit was presented. The problems on feature extraction in analog circuit, data pre-processing, training and testing of network, fault pattern classification were all discussed here. Fault features were extracted by circuit simulation, after data preprocessed by wavelet-neural network, which can be constructed into samples aggregation, the samples for training and testing were used to train and test neural network respectively, the uniform pattern samples were used to diagnose faults, the fault diagnosis in analogy circuit was realized effectively. An illustration validated this method
Keywords :
analogue circuits; circuit simulation; fault diagnosis; feature extraction; neural nets; pattern classification; wavelet transforms; analog circuit; circuit simulation; data preprocessing; fault diagnosis; fault pattern classification; feature extraction; sample aggregation; wavelet-neural network; Analog circuits; Artificial neural networks; Circuit faults; Circuit simulation; Circuit testing; Fault diagnosis; Feature extraction; Intelligent networks; Neural networks; Wavelet analysis; Analog circuit; fault diagnosis; feature extraction; wavelet-neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1712845
Filename :
1712845
Link To Document :
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