Real-time data-driven fault diagnosis of proton exchange membrane fuel cell system based on binary encoding convolutional neural network
Author:
Publisher
Elsevier BV
Subject
Energy Engineering and Power Technology,Condensed Matter Physics,Fuel Technology,Renewable Energy, Sustainability and the Environment
Reference41 articles.
1. Designing the next generation of proton-exchange membrane fuel cells;Jiao;Nature,2021
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5. Characteristic analysis in lowering current density based on pressure drop for avoiding flooding in proton exchange membrane fuel cell;Li;Appl Energy,2019
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2. Spatial–temporal synchronous fault feature extraction and diagnosis for proton exchange membrane fuel cell systems;Energy Conversion and Management;2024-09
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4. Predicting water saturation and oxygen transport resistance in proton exchange membrane fuel cell by artificial intelligence;Fuel;2024-07
5. Addressing Data Scarcity in PEMFC Fault Diagnosis Using Adversarial Learning;2024 IEEE International Conference on Prognostics and Health Management (ICPHM);2024-06-17
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