DocumentCode :
533264
Title :
Application of BP neural network in analog circuits diagnosis
Author :
Shirong, Yin
Author_Institution :
Coll. of Electromech. & Automobile Eng., Chongqing Jiaotong Univ., Chongqing, China
Volume :
11
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
The theories of using neural network to construct the fault dictionary of analog circuits were studied The response signatures of fault and fault-free circuit under test were generated during a simulation of the circuit before the diagnosis phase and are used to train an neural network. If we have obtained the response signature of the circuit under test on line, we can identify the fault by inputting the signature to the neural network. Experiment on a continuous-time state-variable filter demonstrates that the method of this paper has high diagnose sensitivity and fast fault identification and deducibility.
Keywords :
analogue circuits; backpropagation; fault diagnosis; neural nets; BP neural network; analog circuit diagnosis; continuous time state variable filter; fault dictionary; fault free circuit; fault identification; Analog circuits; Artificial neural networks; Circuit faults; Dictionaries; Fault diagnosis; Neurons; Testing; analog circuits; fault diagnosis; neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5623266
Filename :
5623266
Link To Document :
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