Fault Diagnosis of RC-coupled Amplifier Using Slope Fault Feature and Comparision with Different Neural Networks

This paper describe fault diagnosis of RC-Coupled amplifier using slope fault feature. These slope fault feature technique utilized to construct the fault dictionary for RC-Coupled amplifier. This fault dictionary used to generate different fault diagnosis model for analog circuit using artificial n...

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Vydané v:2015 Fifth International Conference on Communication Systems and Network Technologies s. 1163 - 1166
Hlavní autori: Gupta, Shashank Kumar, Ayub, Shahanaz, Saini, J. P.
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.04.2015
Predmet:
Analog circuits
Circuit faults
Dictionaries
Fault diagnosis
feed forward backpropagation algorithm
Feeds
Neural networks
perceptron neural network
radial basis function neural network
RC-Coupled amplifier
Resistance
slope fault feature
voltage relation function
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Shrnutí:This paper describe fault diagnosis of RC-Coupled amplifier using slope fault feature. These slope fault feature technique utilized to construct the fault dictionary for RC-Coupled amplifier. This fault dictionary used to generate different fault diagnosis model for analog circuit using artificial neural network technique. For generate the fault model three different type neural networks utilized. These neural networks are radial basis function neural network, perceptron neural network and feed forward back propagation algorithm neural network. In theses network radial basis function neural network shows 100 percentage efficiency, perceptron neural network shows 87.5 percentage efficiency and feed forward back propagation algorithm shows 99.31 percentage efficiency in the training and testing for fault dictionary.
DOI:10.1109/CSNT.2015.75