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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/24574

Title: Test and evaluation of a fuzzy diagnostic model for PEFC
Authors: Davies, Ben
Jackson, Lisa M.
Dunnett, Sarah J.
Issue Date: 2016
Publisher: © Taylor & Francis
Citation: DAVIES, B., JACKSON, L.M. and DUNNETT, S.J., 2016. Test and evaluation of a fuzzy diagnostic model for PEFC. IN: Walls, L., Revie, M. and Bedford, T. (eds.) Risk, Reliability and Safety: Innovating Theory and Practice: Proceedings of ESREL 2016 (Glasgow, Scotland, 25-29 September 2016), Boca Raton, Florida: CRC Press, pp. 1937-1941.
Abstract: Diagnosing faulty conditions of engineering systems is a highly desirable process within control structures, such that condition based maintenance (CBM) is made possible and effective. The goal herein is to enhance lifetime performance and extend system availability. Difficulty arises in developing a mathematical model which can describe all working and failure modes of complex systems. However the human ability to diagnose a system through experience is a powerful one, and can be represented in fuzzy logic. This paper presents the knowledge base of degradation modes in a polymer electrolyte fuel cell (PEFC), captured from experts and experimental findings. The defined rules produced for the fuzzy logic model connect ob-served operational modes and symptoms to component degradation. The system is then tested against common automotive stress conditions to assess operability.
Description: This book chapter is in closed access until 13th Sept 2017.
Sponsor: This project is supported by the Engineering and Physical Science Research Council (grant number EP/L015749/1).
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/24574
Publisher Link: https://www.crcpress.com/Risk-Reliability-and-Safety-Innovating-Theory-and-Practice-Proceedings/Walls-Revie-Bedford/p/book/9781138029972
ISBN: 9781138029972
Appears in Collections:Closed Access (Aeronautical and Automotive Engineering)

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