Construction method and application of real-time monitoring and early-warning model for anaerobic reactor leakage

被引:4
|
作者
Wang, Feng [1 ]
Deng, Fujie [1 ]
Wang, Yipeng [2 ]
机构
[1] Beijing Univ Chem Technol, Natl Fdn Res Lab Fault Prevent & Hazardous Chem P, Beijing, Peoples R China
[2] Chengdu Aircraft Ind Grp Co Ltd, Chengdu, Peoples R China
基金
中国国家自然科学基金;
关键词
biogas leakage; early-warning model; emergency response; quantitative calculation; real-time monitoring;
D O I
10.1002/prs.12144
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The anaerobic reactor is one of the most critical reaction devices for biogas engineering, wherein is usually a large amount of flammable gas methane. Fire and explosion accidents will be easily triggered if the gas leaks, threatening the surrounding buildings, equipment, personnel, and so forth. Avoiding the significant accidents caused by CH4 leakage has become a critical issue in the design and condition monitoring for an anaerobic reactor. This article presents a model construction method for leakage early-warning. Incident database and hazard and operability analysis (HAZOP) can be utilized to identify the leakage risks, and computational fluid dynamics (CFD) simulation and consequence quantity calculation can be used to determine the consequence influence ranges. The calculation results can be employed to establish prediction models for abnormal situations. Process safety management (PSM) data and risk analysis results can be combined with the possible abnormal situations to assist operators in adopting the right solutions. An early-warning system has been developed to illustrate the industrial application of the model. It can be concluded that collecting multi-parameter values according to the real-time changes in the actual production process, continuous monitoring and early-warning of leakage risk, and so forth, will contribute to accident avoiding and emergency response in reactor operations.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Construction method and application of real-time monitoring and warning model of ethylene oxide reactor leakage
    Zeng, Wenwen
    Deng, Fujie
    Cai, Jingbo
    Wang, Feng
    Huagong Jinzhan/Chemical Industry and Engineering Progress, 2019, 38 (11): : 5200 - 5209
  • [2] Rugged early-warning spectroscopic system for real-time environment water monitoring
    Ling, Bo
    Zeifman, Michael I.
    Hu, Jannias
    OPTICALLY BASED BIOLOGICAL AND CHEMICAL DETECTION FOR DEFENCE III, 2006, 6398
  • [3] Early-warning application for real-time detection of energy consumption anomalies in buildings
    Chou, Jui-Sheng
    Telaga, Abdi S.
    Chong, Wai K.
    Gibson, G. Edward, Jr.
    JOURNAL OF CLEANER PRODUCTION, 2017, 149 : 711 - 722
  • [4] Construction and application of water security early-warning model
    Guo, Lishuo
    Wang, Lifang
    WATER AND ENVIRONMENT JOURNAL, 2022, 36 (03) : 458 - 468
  • [5] A framework for real-time monitoring and early warning to scaffold safety at construction site
    Xue, Xiaolong
    Shi, Ning
    Chen, Xiang
    Wang, Chengwu
    Zhao, Qi
    Luo, Yazhuo
    Journal of Convergence Information Technology, 2012, 7 (19) : 140 - 146
  • [6] Sulfur Hexafluoride Gas Leakage Monitoring and Early-Warning Method for Electrical Power Facilities
    Liu, Chunrui
    Deng, Fume
    Shi, Lei
    Wang, Feng
    IEEE ACCESS, 2020, 8 : 128991 - 129001
  • [7] Real-time monitoring and early warning approach of TBM jamming and its application
    Liu Q.
    Liu H.
    Zhang P.
    Huang X.
    Luo C.
    Sang H.
    Yanshilixue Yu Gongcheng Xuebao/Chinese Journal of Rock Mechanics and Engineering, 2019, 38 : 3354 - 3361
  • [8] Construction and application of debris flow infrasound real-time monitoring and warning visualization platform
    Liu, Dunlong
    Wu, Qian
    Dong, Hanchuan
    Leng, Xiaopeng
    He, Lei
    Gao, Yan
    NATURAL HAZARDS, 2022, 112 (01) : 521 - 543
  • [9] Construction and application of debris flow infrasound real-time monitoring and warning visualization platform
    Dunlong Liu
    Qian Wu
    Hanchuan Dong
    Xiaopeng Leng
    Lei He
    Yan Gao
    Natural Hazards, 2022, 112 : 521 - 543
  • [10] Modelling an emergency vehicle early-warning system using real-time feedback
    Distributed Systems Group, Department of Computer Science, Trinity College Dublin, Dublin, Ireland
    Int. J. Intell. Inf. Database Syst., 2008, 2 (222-239):