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Article type: Research Article
Authors: Cui, Lu-Juna; b; * | Cao, Yan-Longa | Guo, Hong-Honga | Guo, Shi-Ruia | Zeng, Wenhanga | Wang, Pei-Xionga | Chen, Gangb
Affiliations: [a] The University Key Subject Opening Laboratory of Henan Province, School of Mechanical and Electronic Engineering, Zhongyuan University of Technology, Henan, China | [b] Anhui Key Laboratory of Mine Intelligent Equipment and Technology, Anhui University of Science and Technology, Anhui, China
Correspondence: [*] Corresponding author: Lu-Jun Cui, The University Key Subject Opening Laboratory of Henan Province, School of Mechanical and Electronic Engineering, Zhongyuan University of Technology, Henan 450007, China. E-mail: [email protected].
Abstract: In the process of long-distance transportation of different gas, the remote pipeline plays an irreplaceable role in energy transmission. When the pipeline is laid in remote areas for a long distance, it is easy to be influenced by geological disasters and complex working conditions, which may lead to corrosion and leakage. therefore, it is necessary to conduct pipeline gas real-time safety monitoring. An optical fiber gas leakage synchronous monitoring system was proposed and demonstrated based on distributed optical sensing technology for simultaneous multi-gas measurements. In this study, we discuss that the principle of multi-gas leakage synchronous monitoring system is investigated and then validated by the theoretical simulation experiments. Furthermore, gas concentration and leakage location discrimination tests are also conducted in laboratory. The experimental results show that the output intensity values increased obviously along with the gas concentration changes, and the response time of the sensor system is about 40 seconds, and it’s concluded that the multi-gas leakage synchronous monitoring system based on distributed optical fiber sensing technology exhibited good sensing and location discrimination performance.
Keywords: Multi-gas measurement, dielectric film filter (DFF), optical fiber sensing
DOI: 10.3233/JCM-215842
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 2, pp. 615-621, 2022
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