Using neural networks for fault detection in a distillation column. (27th October 2008)

• Record Type: Journal Article
• Authors: Manssouri, I.; Chetouani, Y.; El Kihel, B.
• Is Part Of: International journal of computer applications technology. Volume 32:Number 3(2008)
• Page Start: 181
• Page End: 186
• Publication Date: 2008-10-27
• Subjects: classification -- distillation column -- fault detection -- process safety -- radial basis function -- RBF -- reliability -- neural networks; Technology -- Data processing -- Periodicals; 620.00285
• Languages: English
• ISSNs: 0952-8091

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.