Risk assessment of gas explosion in coal mines based on fuzzy AHP and bayesian network

被引：0
作者：
Li M. [1 ,2 ]
Wang H. [1 ]
Wang D. [1 ]
Shao Z. [1 ]
He S. [3 ]
机构：
[1] School of Safety Engineering, China University of Mining and Technology, Xuzhou
[2] School of Safety and Environmental Engineering, Hunan Institute of Technology, Hengyang, Hunan
[3] School of Economic and Management, Hunan Institute of Technology, Hengyang, Hunan
来源：
Process Safety and Environmental Protection | 2020年 / 135卷
基金：
中国国家自然科学基金;
关键词：
Bayesian network; Fuzzy number; Gas explosion; Risk assessment;
D O I：
10.1016/j.psep.2020.01.003
中图分类号：
学科分类号：
摘要：
Gas explosion is one of the most deadly hazards in underground coal mining. Risk assessment has played an effective role in avoiding gas explosions and revising coal mine regulations. However, the traditional methods are deficient in quantitative evaluation, dynamic control and dealing with uncertainty. In this paper, a method of quantitative assessment the risk of gas explosion in underground coal mine using Bayesian network was proposed. A fuzzy analytic hierarchy process (FAHP) method based on subjective and objective information of experts was developed in the process of fuzzification. Through the Bayesian inference, the probability of occurrence of potential risk events and the probability distribution of risk factors can be calculated in real time according to on prior knowledge and evidence updating. Meanwhile, the most likely potential causes of accidents can be determined. A sensitivity analysis technique was utilized to investigate the contribution rate of each risk factor to a risk event, so as to determine the most critical risk factor. Taking Babao Coal Mine in China as the case, this study conducted a gas explosion risk assessment. The results show that the mothed of fuzzy AHP and Bayesian Network is feasible and applicable. It can be used as a decision-making tool to prevent coal mine gas explosions and provide decision makers with a technical guide for managing the coal mine gas explosion risk. © 2020 Institution of Chemical Engineers
引用
收藏
页码：207 / 218
页数：11
相关论文
共 59 条
[1]  
Andrews-Speed P., Yang M., Lei S., Et al., The regulation of China's township and village coal mines: a study of complexity and ineffectiveness[J], J. Clean. Prod., 11, 2, pp. 185-196, (2003)
[2]  
Bagherpour R., Yarahmadi R., Khademian A., Safety risk assessment of Iran’’s underground coal mines based on preventive and preparative measures[J], Hum. Ecol. Risk Assess., 21, 8, pp. 2223-2238, (2015)
[3]  
Bobbio A., Portinale L., Minichino M., Et al., Improving the analysis of dependable systems by mapping fault trees into Bayesian networks[J], Reliab. Eng. Syst. Saf., 71, 3, pp. 249-260, (2001)
[4]  
Cai B., Kong X., Liu Y., Et al., Application of bayesian networks in reliability evaluation[J], IEEE Trans. Industr. Inform., 99, (2018)
[5]  
Cai B., Min X., Liu Y., Et al., Availability-based engineering resilience metric and its corresponding evaluation methodology[J], Reliab. Eng. Syst. Saf., 172, (2017)
[6]  
Chan H.K., Sun X., Chung S., When should fuzzy analytic hierarchy process be used instead of analytic hierarchy process?[J], Decis. Support Syst., 125, (2019)
[7]  
Chen S.J., Chen S.M., Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers[J], Appl. Intell., 26, 1, pp. 1-11, (2007)
[8]  
Cioca I., Moraru R.I., Explosion and/or fire risk assessment methodology: a common approach, structured for underground coalmine environments/Metoda szacowania ryzyka wybuchu i pożarów: podejście ogólne, dostosowane do środowiska kopalni podziemnej[J], Arch. Min. Sci., 57, 1, pp. 53-60, (2012)
[9]  
Cooper G.F., Herskovits E., A Bayesian method for the induction of probabilistic networks from data[J], Mach. Learn., 9, 4, pp. 309-347, (1992)
[10]  
Crowl D.A., Understanding Explosions[Z], (2003)
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