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
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