DocumentCode :
2341211
Title :
A neural network-based approach for fault diagnosis in non-linear analog systems
Author :
Iuculano, G. ; Catelani, M. ; Gori, M. ; Bagnoli, S. ; Billi, D.
Author_Institution :
Dept. of Electron. Eng., Florence Univ., Italy
fYear :
1994
fDate :
10-12 May 1994
Firstpage :
197
Abstract :
A new interesting technique for fault diagnosis in non-linear analog systems is presented. The approach is based on a neural network interpolator for the construction of a fault dictionary in the frequency domain. A multi-layered architecture with one hidden layer is chosen in order to locate and to identify the most likely faulty element of the System Under Test (SUT)
Keywords :
automatic testing; computer architecture; electronic equipment testing; fault location; feedforward neural nets; interpolation; nonlinear systems; System Under Test; fault diagnosis; fault dictionary; frequency domain; hidden layer; multi-layered architecture; neural network interpolator; neural network-based approach; nonlinear analog systems; Automatic testing; Circuit faults; Computer science; Dictionaries; Fault diagnosis; Frequency; Intelligent networks; Neural networks; System testing; Tellurium;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1994. IMTC/94. Conference Proceedings. 10th Anniversary. Advanced Technologies in I & M., 1994 IEEE
Conference_Location :
Hamamatsu
Print_ISBN :
0-7803-1880-3
Type :
conf
DOI :
10.1109/IMTC.1994.352093
Filename :
352093
Link To Document :
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