基于ISM-BN的化工事故风险因素分析

IF 1.7 4区 工程技术 Q3 ENGINEERING, INDUSTRIAL
Yiming Ma, Mingguang Zhang, Mingliang Wang
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引用次数: 0

摘要

化学工业涉及许多易燃、易爆、有毒和其他危险化学品的生产、储存和使用。事故一旦发生,将对人类和经济活动造成严重的危害。为了预防化工事故,本文将解释结构模型(ISM)和贝叶斯网络(BN)相结合,定量研究化工事故风险因素之间的关系和相互作用强度。通过事故案例分析和问卷调查,选取了化工行业21个事故危险因素。根据专家的决策,确定了风险因素之间的影响关系,得到了ISM的多层次有向图。并将ISM模型转化为定量的BN模型。BN模型应用于正向推理、敏感性分析和逆向推理。结果表明,各类危险因素与化工事故存在正相关关系,其中监管机制在生产活动中发生的概率最高。非法操作对化工事故的敏感性最高,影响最大。材料和产品的固有危害是最容易发生事故的原因。根据研究结果,提出了提高化工行业安全管理水平的可行措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of accident risk factors in chemical industry based on ISM-BN
The chemical industry involves the production, storage, and use of many flammable, explosive, toxic, and other hazardous chemicals. Once an accident occurs, it will cause serious harm to human and economic activities. In order to prevent chemical accidents, this paper combines Interpretive Structural Modeling (ISM) and Bayesian network (BN) to quantitatively study the relationship and interaction strength among accident risk factors in chemical industry. Through the analysis of accident cases and questionnaire survey, 21 accident risk factors in chemical industry are selected. According to the decision of experts, the influence relationship between risk factors is determined, and a multi-level directed graph of ISM is obtained. And the ISM model is transformed into a quantitative BN model. The BN model is applied to forward reasoning, sensitivity analysis, and reverse reasoning. The results indicate that there is a positive correlation between various risk factors and chemical accidents, and the supervision mechanism has the highest probability of occurrence in production activities. Illegal operation has the highest sensitivity and the greatest impact on chemical accidents. Inherent hazards of materials and products is the most likely cause of accidents. Based on the research results, feasible measures have been proposed to improve safety management in the chemical industry.
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来源期刊
CiteScore
4.50
自引率
19.00%
发文量
81
审稿时长
6-12 weeks
期刊介绍: The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome
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