DocumentCode :
2208018
Title :
How to use neural networks to study the reliability of dynamic systems
Author :
Pasquet, S. ; Châtelet, E.
Author_Institution :
Univ. de Technol. de Troyes, France
Volume :
1
fYear :
1998
fDate :
4-8 May 1998
Firstpage :
226
Abstract :
Presents an application based on neural networks. The goal is to determine the event sequences that induce the failure of an industrial system, and also to calculate the different parameters of a reliability analysis. Associated with a flow diagram and tested with an ISdF test case, it is shown that this model is able to give results comparable to the ones obtained by classical methods. After an introduction of the different methods used in the reliability domain and their limitations, the studied case is presented. This model is well adapted to the study of dynamic systems using Monte Carlo simulation. Then the structure of the model “flow diagram and neural networks” is shown. Finally before concluding, the results are compared to others obtained by several methods
Keywords :
Monte Carlo methods; industrial plants; multilayer perceptrons; reliability; transfer functions; ISdF test case; Monte Carlo simulation; dynamic systems; event sequences; failure; flow diagram; industrial system; reliability analysis; Availability; Failure analysis; Maintenance; Neural networks; Paper technology; Pattern recognition; Predictive models; Safety; Signal processing; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
ISSN :
1098-7576
Print_ISBN :
0-7803-4859-1
Type :
conf
DOI :
10.1109/IJCNN.1998.682267
Filename :
682267
Link To Document :
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