Explainability: Relevance based dynamic deep learning algorithm for fault detection and diagnosis in chemical processes

•An Explainability based methodology is employed for deriving contribution plots for fault diagnosis.•Pruning of irrelevant input variables for the supervised classification task results in enhanced fault detection and fault diagnosis accuracy.•The proposed relevance based method shows superior accu...

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Bibliographic Details

Published in:	Computers & chemical engineering Vol. 154; p. 107467
Main Authors:	Agarwal, Piyush, Tamer, Melih, Budman, Hector
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2021
Subjects:	Autoencoders Deep learning Explainability Fault detection and diagnosis Tennessee eastman process Deep learning Tennessee eastman process Autoencoders Explainability Fault detection and diagnosis
ISSN:	0098-1354, 1873-4375
Online Access:	Get full text
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