Process fault diagnosis with model- and knowledge-based approaches: Advances and opportunities

Li, Weijun, Li, Hui, Gu, Sai and Chen, Tao (2020) Process fault diagnosis with model- and knowledge-based approaches: Advances and opportunities Control Engineering Practice, 105, 104637.

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Abstract

Fault diagnosis plays a vital role in ensuring safe and efficient operation of modern process plants. Despite the encouraging progress in its research, developing a reliable and interpretable diagnostic system remains a challenge. There is a consensus among many researchers that an appropriate modelling, representation and use of fundamental process knowledge might be the key to addressing this problem. Over the past four decades, different techniques have been proposed for this purpose. They use process knowledge from different sources, in different forms and on different details, and are also named model-based methods in some literature. This paper first briefly introduces the problem of fault detection and diagnosis, its research status and challenges. It then gives a review of widely used model- and knowledge-based diagnostic methods, including their general ideas, properties, and important developments. Afterwards, it summarises studies that evaluate their performance in real processes in process industry, including the process types, scales, considered faults, and performance. Finally, perspectives on challenges and potential opportunities are highlighted for future work.

Item Type:	Article
Divisions :	Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :	Name Email ORCID Li, Weijun weijun.li@surrey.ac.uk Li, Hui hl0024@surrey.ac.uk Gu, Sai sai.gu@surrey.ac.uk Chen, Tao T.Chen@surrey.ac.uk
Date :	December 2020
Funders :	Engineering and Physical Sciences Research Council (EPSRC), Biotechnology and Biological Sciences Research Council (BBSRC), Unilever, University of Surrey
DOI :	10.1016/j.conengprac.2020.104637
Copyright Disclaimer :	© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords :	Fault diagnosis; Fault detection; Process monitoring; Process knowledge; Process safety
Depositing User :	Clive Harris
Date Deposited :	06 Oct 2020 16:34
Last Modified :	06 Oct 2020 16:34
URI:	http://epubs.surrey.ac.uk/id/eprint/858681

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