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Detection of hydrogen gas leak using distributed temperature sensor in green hydrogen system

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Abstract
This study addresses the challenges of hydrogen gas detection in pipelines, focusing on the highly flammable nature and low ignition energy of hydrogen. It highlights the limitations of traditional point-based detection methods and emphasizes the need for advanced safety technologies. An integrated approach combining onsite monitoring with Internet of Things (IoT) technology is proposed to enhance systematic safety management and quick leak detection in hydrogen infrastructures. The study reviews various hydrogen detection methods, emphasizing distributed temperature sensing (DTS) techniques to identify leaks through temperature variations. Over nine months of monitoring, the results indicate that DTS temperature variations are more influenced by sensor location than chamber configuration, suggesting that external DTS chamber installation is more effective for leak detection. Additionally, the study integrates Gaussian Process Regression with Machine Learning to predict temperature distribution in pipelines, providing valuable insights for future hydrogen leak detection research. © 2024 Hydrogen Energy Publications LLC
Author(s)
Yang, DongukOh, JaedeokLee, GwonyeolLee, SukhoChoi, Seongim
Issued Date
2024-09
Type
Article
DOI
10.1016/j.ijhydene.2024.07.450
URI
https://scholar.gist.ac.kr/handle/local/9378
Publisher
Elsevier Ltd
Citation
International Journal of Hydrogen Energy, v.82, pp.910 - 922
ISSN
0360-3199
Appears in Collections:
Department of Mechanical and Robotics Engineering > 1. Journal Articles
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