DocumentCode :
1246812
Title :
A neural network approach for identification and fault diagnosis on dynamic systems
Author :
Bernieri, A. ; Apuzzo, M.D. ; Sansone, L. ; Savastano, M.
Author_Institution :
Dipartimento di Ingegneria Ind., Cassino Univ., Italy
Volume :
43
Issue :
6
fYear :
1994
fDate :
12/1/1994 12:00:00 AM
Firstpage :
867
Lastpage :
873
Abstract :
The possibilities offered by neural networks for system identification and fault diagnosis problems in dynamic systems are investigated. In particular, an original “neural” procedure is illustrated: its sensitivity and response time enable it to be used in on-line fault diagnosis applications. Some examples are also reported. Even though they pertain to a simple linear dynamic system, these examples highlight the general applicability and advantages of a neural approach
Keywords :
fault diagnosis; learning (artificial intelligence); neural nets; parameter estimation; C language; Explorenet 3000; dynamic systems; fault diagnosis; identification; linear dynamic system; neural network; on-line fault diagnosis; response time; second order band-pass filter; Artificial neural networks; Biological neural networks; Delay; Fault diagnosis; Humans; Neural network hardware; Neural networks; Nonlinear dynamical systems; Nonlinear systems; System identification;
fLanguage :
English
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9456
Type :
jour
DOI :
10.1109/19.368083
Filename :
368083
Link To Document :
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