Author： Manssouri I. Chetouani Y. Kihel B. El
Publisher： Inderscience Publishers
ISSN： 0952-8091
Source： International Journal of Computer Applications in Technology, Vol.32, Iss.3, 2008-10, pp. : 181-186
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Abstract
Several methods of fault detection have been put to testing with the purpose of securing the installations and reducing the risks of accidents. This paper presents a new approach of fault detection based on the realisation of a Bayesian neural separate at radial basis functions. In this paper, our contribution consists of demonstrating the way this kind of network can be used as faults separate, applied to a continuous distillation column containing a binary mixture of toluene/methylcyclohexane. The latter is carried out through the use of test base containing two operating modes: normal and abnormal.
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