Prior knowledge-infused Self-Supervised Learning and explainable AI for Fault Detection and Isolation in PEM electrolyzers-Reference-Cited by-同舟云学术

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Prior knowledge-infused Self-Supervised Learning and explainable AI for Fault Detection and Isolation in PEM electrolyzers

Published:2024-08 Issue: Volume:594 Page:127871
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Dash Balyogi Mohan^ORCID,Bouamama Belkacem Ould,Pekpe Komi Midzodzi,Boukerdja Mahdi

Publisher

Elsevier BV

Reference34 articles.

1. Robust diagnosis of PEM electrolysers using LFT bond graph;Sood;Int. J. Hydrog. Energy,2022

2. Diagnostic bond graphs for online fault detection and isolation;Samantaray;Simul. Model. Pract. Theory,2006

3. LFT bond graph model based robust control and diagnosis;Djeziri,2011

4. Hydrogen fuel cell diagnostics using random forest and enhanced feature selection;Lin;Int. J. Hydrog. Energy,2020

5. Enhancing reliability and lifespan of PEM fuel cells through neural network-based fault detection and classification;Dhimish;Int. J. Hydrog. Energy,2023

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