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A fuzzy inference system for fault detection and isolation : application to a fluid system

White, Christopher J. and Lakany, H. (2008) A fuzzy inference system for fault detection and isolation : application to a fluid system. Expert Systems with Applications, 35 (3). pp. 1021-1033. ISSN 0957-4174

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Abstract

This work focuses on the design and implementation of a fuzzy inference system for fault detection and isolation (FDI) which can learn from example fault data, and the determination of a suitable optimisation strategy for the membership functions. A FDI system was developed which is based on adaptive fuzzy rules. A number of optimisation strategies were then applied; it was found that an evolutionary algorithm not only produced the best results but did so with relatively little processing effort and with excellent consistency. The adaptive fuzzy system, thus optimised, was tested against a neural network, which was trained to produce analogue outputs as an indication of fault magnitude. The fuzzy solution produced the best accuracy. We can conclude that an adaptive fuzzy inference system for FDI, using an evolutionary algorithm to learn from examples, can provide an accurate and readily comprehensible solution to diagnosing and evaluating fluid process plant faults.

Item type: Article
ID code: 8247
Keywords: fuzzy inference system, fault detection, fluid system, bioengineering, optimisation, Bioengineering, Electronic computers. Computer science, Artificial Intelligence, Engineering(all), Computer Science Applications
Subjects: Technology > Engineering (General). Civil engineering (General) > Bioengineering
Science > Mathematics > Electronic computers. Computer science
Department: Faculty of Engineering > Bioengineering
Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 06 Aug 2009 12:01
    Last modified: 04 Sep 2014 21:22
    URI: http://strathprints.strath.ac.uk/id/eprint/8247

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