基于AcciMap模型的燃气管道泄漏爆炸事故分析

doi:10.16265/j.cnki.issn1003-3033.2023.07.1011

中国安全科学学报 ›› 2023, Vol. 33 ›› Issue (7): 140-146.doi: 10.16265/j.cnki.issn1003-3033.2023.07.1011

基于AcciMap模型的燃气管道泄漏爆炸事故分析

孙逸林¹^,²(), 郑小强¹^,²^,^**(), 刘险峰¹, 贺艳艳¹, 王冶³

¹ 西南石油大学经济管理学院,四川成都 610500
² 西南石油大学能源安全与低碳发展重点实验室,四川成都 610500
³ 中国石油西南油气田分公司四川川港燃气有限公司,四川成都 610051

收稿日期:2023-02-25 修回日期:2023-05-19 出版日期:2023-07-28
通讯作者:
^** 郑小强(1981—)男,四川长宁人,博士,教授,博士生导师,主要从事能源经济、风险管理与可持续发展等方面的研究。E-mail:zhengxiaoqiang@163.com。
作者简介:
孙逸林 (1996—),男,安徽合肥人,博士研究生,研究方向为复杂社会技术系统建模、城镇燃气安全管理与事故分析。E-mail:SYLSWPU@163.com。
刘险峰,教授
王冶,工程师
基金资助:
国家社会科学基金(21BZZ058); 国家自然科学基金青年科学基金(52004241); 西南石油大学科研攻关项目(2019CXTD12)

Analysis of gas pipeline leakage and explosion accident based on AcciMap model

SUN Yilin¹^,²(), ZHENG Xiaoqiang¹^,²^,^**(), LIU Xianfeng¹, HE Yanyan¹, WANG Ye³

¹ School of Economics and Management, Southwest Petroleum University, Chengdu Sichuan 610500, China
² Key Laboratory of Energy Security and Low-carbon development, Southwest Petroleum University, Chengdu Sichuan 610500, China
³ Sichuan Chuangang Group Corporation, CNPC Southwest Oil & Gas field Company, Chengdu Sichuan 610051, China

Received:2023-02-25 Revised:2023-05-19 Published:2023-07-28

摘要/Abstract

摘要：

为探讨燃气管道泄漏爆炸事故系统及其致因的性质,以湖北十堰“6·13”重大事故为例进行分析。采用AcciMap模型系统辨识事故致因,构建“6·13”事故AcciMap模型;引入复杂网络(CN)与PageRank算法,分析整体系统与个体因素的属性特征,据此辨识关键致因;再通过贝叶斯网络(BN)进行参数学习和诊断推理,分析事故最大致因链。结果表明:安全生产监管工作严重失察、安全生产主体责任未落实、安全生产监督指导不力是关键致因;安全生产理念和属地责任未贯彻落实→安全生产监管工作严重失察→安全管理制度存在缺陷→安全培训教育存在缺陷→燃气管道维抢人员违规处置→明火引爆蓄积燃气→燃气泄漏爆炸并造成严重伤亡是最大致因链。研究认为:应从政府和企业等2类主体出发,采取多元化的风险防控策略以遏制事故再次发生。

关键词: AcciMap模型, 燃气管道, 泄漏爆炸, 复杂网络(CN), 贝叶斯网络(BN)

Abstract:

In order to explore the attribute characteristics of causes of gas pipeline leakage and explosion accident, the "6·13" accident was taken as an illustrative example. The AcciMap model of the "6·13" accident was built by identifying causes based on the AcciMap model. The CN and PageRank algorithms were introduced into the AcciMap model to analyze the attribute characteristics of accident systems and nodes and identify key causes. The BN was applied for parameter learning and inference learning to find out the key causes chain. The analysis results prove that the serious oversight of work safety supervision, failure to implement the main responsibilities of work safety, inadequate supervision and guidance of work safety are the key causes of the "6·13" accident. The concept of work safety and territorial responsibilities are not implemented → serious oversight of work safety supervision → defects in safety management system → defects in safety training and education → illegal disposal of gas pipeline maintenance and rescue staff → fire detonates accumulated gas → gas leakage explode and causes serious casualties is the biggest causal chain. It is concluded that diversified risk prevention and control strategies should be taken from the aspects of both government and enterprises to curb the recurrence of accidents.

Key words: AcciMap model, gas pipeline, leakage and explosion, complex network(CN), Bayesian network(BN)

孙逸林, 郑小强, 刘险峰, 贺艳艳, 王冶. 基于AcciMap模型的燃气管道泄漏爆炸事故分析[J]. 中国安全科学学报, 2023, 33(7): 140-146.

SUN Yilin, ZHENG Xiaoqiang, LIU Xianfeng, HE Yanyan, WANG Ye. Analysis of gas pipeline leakage and explosion accident based on AcciMap model[J]. China Safety Science Journal, 2023, 33(7): 140-146.

图/表 8

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事故致因	聚类系数	事故致因	聚类系数
A₁	0.419	C₃	0.222
A₂	0.502	C₄	0.286
A₃	0.501	E₇	0.253
B₂	0.255	F₁	0.417
C₁	0.244	F₃	0.252
C₂	0.244	F₄	0.267

节点	中间中心度	特征向量中心度	节点	中间中心度	特征向量中心度	节点	中间中心度	特征向量中心度
A₁	4.000	0.093	D₂	6.000	0.214	E₇	4.000	0.080
A₂	3.000	0.083	D₃	11.000	0.261	E₈	2.000	0.041
A₃	3.000	0.083	D₄	7.000	0.199	E₉	4.000	0.037
B₁	9.000	0.258	D₅	7.000	0.221	E₁₀	3.000	0.024
B₂	8.000	0.253	E₁	5.000	0.112	F₁	4.000	0.083
C₁	10.000	0.362	E₂	6.000	0.124	F₂	5.000	0.106
C₂	10.000	0.362	E₃	4.000	0.111	F₃	5.000	0.086
C₃	9.000	0.330	E₄	5.000	0.121	F₄	6.000	0.101
C₄	7.000	0.267	E₅	6.000	0.122	F₅	6.000	0.070
D₁	9.000	0.263	E₆	4.000	0.084	F₆	6.000	0.068

节点	PageRank值	节点	PageRank值	节点	PageRank值	节点	PageRank值	节点	PageRank值
A₁	0.037	C₂	0.034	D₄	0.020	E₅	0.025	F₁	0.007
A₂	0.020	C₃	0.027	D₅	0.017	E₆	0.014	F₂	0.017
A₃	0.020	C₄	0.015	E₁	0.012	E₇	0.018	F₃	0.028
B₁	0.044	D₁	0.028	E₂	0.020	E₈	0.018	F₄	0.017
B₂	0.031	D₂	0.013	E₃	0.014	E₉	0.062	F₅	0.071
C₁	0.042	D₃	0.037	E₄	0.026	E₁₀	0.202	F₆	0.062

节点	诊断推理概率值
E₁₀	E₉ (0.85), F₄ (0.87), F₆ (0.93)
F₆	E₃ (0.86), E₄ (0.93), E₆ (0.88), F₃ (0.83), F₅ (0.86)
E₄	D₁ (0.92), D₂ (0.85), D₃ (0.86)
D₁	C₁ (0.89), C₂ (0.87), C₃ (0.90)
C₃	B₁ (0.91), B₂ (0.89), C₁ (0.89), C₂ (0.87)
B₁	A₁ (0.92), A₂ (0.84), A₃ (0.85)

基于AcciMap模型的燃气管道泄漏爆炸事故分析

Analysis of gas pipeline leakage and explosion accident based on AcciMap model

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