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

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. • Developed new DTS technology with enhanced resolution for sensitive hydrogen leak detection. • Confirmed DTS system's reliability against IEC 61757-2-2 standards through rigorous testing. • Integrated IoT and 3D mapping in software for efficient hydrogen leak monitoring. • Found DTS temperature variations more influenced by installation location than chamber design. • Employed GPR and Machine Learning for predicting hydrogen pipeline temperature distribution. [ABSTRACT FROM AUTHOR]