CHI Xiaoming. Experimental Research and Analysis of Infrared Imaging Detection Technology for Gas Leakage in Petrochemical Enterprises[J]. Infrared Technology , 2024, 46(8): 947-956.
Citation: CHI Xiaoming. Experimental Research and Analysis of Infrared Imaging Detection Technology for Gas Leakage in Petrochemical Enterprises[J]. Infrared Technology , 2024, 46(8): 947-956.

Experimental Research and Analysis of Infrared Imaging Detection Technology for Gas Leakage in Petrochemical Enterprises

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  • Received Date: September 22, 2023
  • Revised Date: October 16, 2023
  • To apply infrared imaging detection technology for gas leakage in petrochemical enterprises, experimental research has been conducted on common gases such as methane and ethylene. The influencing factors, such as gas infrared absorption characteristics, gas concentration, background temperature, and detector sensitivity, were systematically studied, and the characteristics of gas infrared thermal imaging technology and infrared spectral imaging technology were analyzed. Based on the experimental research and analysis, some suggestions have been put forward for the application of infrared imaging detection technology for gas leakage in petrochemical enterprises.

  • [1]
    李家琨, 金伟其, 王霞, 等. 气体泄漏红外成像检测技术发展综述[J]. 红外技术, 2014, 36(7): 513-520. http://hwjs.nvir.cn/article/id/hwjs201407001

    LI Jiakun, JIN Weiqi, WANG Xia, et al. Review of gas leak infrared imaging detection technology [J]. Infrared Technology, 2014, 36(7): 513-520. http://hwjs.nvir.cn/article/id/hwjs201407001
    [2]
    张振杰, 李志平, 张苗苗. 红外成像技术在石化装置易挥发性气体泄漏检测中的应用[J]. 山东化工, 2015, 44(12): 159-162. https://www.cnki.com.cn/Article/CJFDTOTAL-SDHG201512075.htm

    ZHANG Zhenjie, LI Zhiping, ZHANG Miaomiao. Infrared thermal imaging technology in petrochemical device application of volatile gas leak detection[J]. Shandong Chemical Industry, 2015, 44(12): 159-162. https://www.cnki.com.cn/Article/CJFDTOTAL-SDHG201512075.htm
    [3]
    环境保护部. 关于印发《石化行业VOCs污染源排查工作指南》及《石化企业泄漏检测与修复工作指南》的通知[EB/OL]. (2015-11-18) [2023-03-14]. https://www.mee.gov.cn/gkml/hbb/bgt/201511/t20151124_317577.htm.

    Ministry of Ecology and Environment of the People's Republic of China. Notice on Printing and Distributing "Guidelines for VOCs Pollution Source Investigation in Petrochemical Industry" and "Guidelines for Leak Detection and Repair Work in Petrochemical Enterprises"[EB/OL]. (2015-11-18) [2023-03-14]. https://www.mee.gov.cn/gkml/hbb/bgt/201511/t20151124_317577.htm.
    [4]
    住房和城乡建设部. 住房和城乡建设部关于发布国家标准《石油化工可燃气体和有毒气体检测报警设计标准》的公告[EB/OL]. (2019-9-25) [2023-03-14]. https://www.mohurd.gov.cn/gongkai/fdzdgknr/tzgg/201911./20191101_242517.html.

    Ministry of Housing and Urban-Rural Development of the People's Republic of China. Ministry of Housing and Urban-Rural Development on Issuing National Standards Announcement of "Petrochemical Combustible Gas and Toxic Gas Detection and Alarm Design Standards"[EB/OL]. (2019-9-25) [2023-03-14]. https://www.mohurd.gov.cn/gongkai/fdzdgknr/tzgg/201911/20191101_242517.html.
    [5]
    李家琨. 气体泄漏被动式红外成像检测理论及方法研究[D]. 北京: 北京理工大学, 2015.

    LI Jiakun. Research on the Theory and Method of Passive Gas Leak Infrared Imaging Detection[D]. Beijing: Beijing Institute of Technology, 2015.
    [6]
    FLIR. 气体泄漏检测热像仪[EB/OL]. [2023-03-14]. https://www.flir.com/browse/industrial/gas-detection-cameras/.

    FLIR. Gas detection cameras[EB/OL]. [2023-03-14]. https://www.flir.com/browse/industrial/gas-detection-cameras/
    [7]
    Savary S, Gagnon J P, Gross K, et al. Standoff identification and quantification of flare emissions using infrared hyperspectral imaging[C]// Conference on Advanced Environmental, Chemical, and Biological Sensing Technologies VIII, Proceedings of SPIE, 2011, 8024: 1-8.
    [8]
    朱亮, 邹兵, 高少华, 等. 红外成像光谱在泄漏气体处置中的应用研究[J]. 激光与光电子学进展, 2015, 52(8): 118-123. https://www.cnki.com.cn/Article/CJFDTOTAL-JGDJ201508016.htm

    ZHU Liang, ZOU Bing, GAO Shaohua, et al. Application research on infrared imaging spectroscopy in leakage gas disposal[J]. Laser & Optoelectronics Progress, 2015, 52(8): 118-123. https://www.cnki.com.cn/Article/CJFDTOTAL-JGDJ201508016.htm
    [9]
    Hagen N, Kester R T, Morlier C G, et al. Video-rate spectral imaging of gas leaks in the long-wave infrared[C]//Conference on Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XIV, Proceedings of the SPIE, 2013, 8710: 1-7.
    [10]
    刘欢, 胡畔宁, 魏莱. 气云成像摄像机气体泄漏监测技术研究及应用[J]. 天然气技术与经济, 2019, 13(1): 53-56, 83. https://www.cnki.com.cn/Article/CJFDTOTAL-TRJJ201901017.htm

    LIU Huan, HU Panning, WEI Lai. Gas-cloud imaging cameras to monitor gas leakage[J]. Natural Gas Technology, 2019, 13(1): 53-56, 83. https://www.cnki.com.cn/Article/CJFDTOTAL-TRJJ201901017.htm
    [11]
    US. Department of Commerce. NIST Chemistry WebBook [EB/OL]. [2023-03-14]. https://webbook.nist.gov/chemistry/form-ser/.
    [12]
    Flanigan D F. Limits of Passive Remote Detection of Hazardous Vapors by Computer Simulation[C]//Proceedings of SPIE, 1996, 2763: 117-127.
    [13]
    张旭, 金伟其, 李力, 等. 天然气泄漏被动式红外成像检测技术及系统性能评价研究进展[J]. 红外与激光工程, 2019, 48(S2): 53-65. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ2019S2008.htm

    ZHANG Xu, JIN Weiqi, LI Li, et al. Research progress on passive infrared imaging detection technology and system performance evaluation of natural gas leakage[J]. Infrared and Laser Engineering, 2019, 48(S2): 53-65. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ2019S2008.htm
    [14]
    迟晓铭, 肖安山, 朱亮, 等. 石化企业气体泄漏红外成像检测技术研究进展[J]. 安全、健康和环境, 2021, 21(2): 1-5. https://www.cnki.com.cn/Article/CJFDTOTAL-HWJS202408013.htm

    CHI Xiaoming, XIAO Anshan, ZHU Liang, et al. Research progress of infrared imaging detection technology for gas leakage in petrochemical enterprises[J]. Safety Health & Environment, 2021, 21(2): 1-5. https://www.cnki.com.cn/Article/CJFDTOTAL-HWJS202408013.htm
    [15]
    Sjaardema T, Smith C, Birch G. History and Evolution of the Johnson Criteria[R]. Albuquerque, Sandia National Lab, 2015: 1-40.
    [16]
    Vollmerhausen R H, Driggers R G, Wilson D L. Predicting range performance of sampled imagers by treating aliased signal as target-dependent noise[J]. JOSAA, 2008, 25(8): 2055-2065. DOI: 10.1364/JOSAA.25.002055
    [17]
    迟晓铭. 国产非制冷气体泄漏红外成像检测技术试验研究[J]. 安全、健康和环境, 2023, 23(2): 28-34. https://www.cnki.com.cn/Article/CJFDTOTAL-SAFE202302005.htm

    CHI Xiaoming. Experimental research on domestic uncooled infrared imaging technology of gas leakage[J]. Safety Health & Environment, 2023, 23(2): 28-34. https://www.cnki.com.cn/Article/CJFDTOTAL-SAFE202302005.htm
    [18]
    李明骏. 基于传感器阵列的危害气体快速预警与识别方法研发[J]. 传感技术学报, 2021, 34(8): 1069-1074. https://www.cnki.com.cn/Article/CJFDTOTAL-CGJS202108010.htm

    LI Mingjun. Research of rapid warning and recognition method for hazardous gases based on sensor array[J]. Chinese Journal of Sensors and Actuators, 2021, 34(8): 1069-1074. https://www.cnki.com.cn/Article/CJFDTOTAL-CGJS202108010.htm
    [19]
    李明骏. 基于声成像的泄漏源三维空间定位技术研究[J]. 消防科学与技术, 2023, 42(7): 978-982. https://www.cnki.com.cn/Article/CJFDTOTAL-XFKJ202307025.htm

    LI Mingjun. Research on three-dimensional spatial location of leakage source based on acoustic imaging[J]. Fire Science and Technology, 2023, 42(7): 978-982. https://www.cnki.com.cn/Article/CJFDTOTAL-XFKJ202307025.htm
    [20]
    WANG J, Tchapmi L P, Ravikumar A P, et al. Machine vision for natural gas methane emissions detection using an infrared camera[J]. Applied Energy, 2020, 257: 113998. DOI: 10.1016/j.apenergy.2019.113998
    [21]
    SHI J, CHANG Y, XU C, et al. Real-time leak detection using an infrared camera and faster R-CNN technique[J]. Computers & Chemical Engineering, 2020, 135: 106780.
    [22]
    何自芬, 曹辉柱, 张印辉, 等. 融合注意力分支特征的甲烷泄漏红外图像分割[J]. 红外技术, 2023, 45(4): 417-426. http://hwjs.nvir.cn/article/id/cd005b3d-e50a-4a17-bbaa-9acdb4b6a98c

    HE Zifen, CAO Huizhu, ZHANG Yinhui, et al. Infrared image segmentation of methane leaks incorporating attentional branching features[J]. Infrared Technology, 2023, 45(4): 417-426. http://hwjs.nvir.cn/article/id/cd005b3d-e50a-4a17-bbaa-9acdb4b6a98c
    [23]
    王琦, 潘夏童, 邢明玮, 等. 被动式红外成像气体目标智能检测算法及量化研究进展[J]. 控制与决策, 2023, 38(8): 2265-2282. https://www.cnki.com.cn/Article/CJFDTOTAL-KZYC202308016.htm

    WANG Qi, PAN Xiatong, XING Mingwei, et al. A survey of automatic gas leakage detection and quantification based on passive infrared imaging[J]. Control and Decision, 2023, 38(8): 2265-2282. https://www.cnki.com.cn/Article/CJFDTOTAL-KZYC202308016.htm

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