基于Logistic回归方法的油库事故因果关系定量分析

Xingguang Wu, Lei Hou, Zhuang Wu
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引用次数: 0

摘要

由于危险物质的不断积累和频繁转移,石油化工行业发生了大量事故。对于这些历史事件数据,大量的工作是利用描述性统计分析事件如何发生以及为什么发生,而深入探讨不同类型事件相关因果因素的表现特征的工作却很少。本文着重分析了不同原因因素对不同类型事件的相对重要性。收集了1960-2018年期间中国油库相关事件1144起,并根据事件的直观后果(火灾爆炸、物资损失、质量变化、设备损坏和人员伤害)以及是否涉及多米诺骨牌效应(多米诺骨牌事件和非多米诺骨牌事件)进行分类。将病因分为五大类,再细分为十五个小类。对各因素与具体后果类型的交互作用进行分析。采用logistic回归的方法,量化不同原因对不同类型事件的相对概率,确定哪些因素对触发多米诺骨牌事件有显著影响。研究发现,人的因素和组织/管理因素是导致不同后果的更常见的因果因素,同一因果因素对不同类型事件发生概率的影响是不同的。结果突出了每种类型事件的更关键的风险因素,该方法可用于指导事件预防和安全保护。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantitative Analysis of the Cause-Effect Relationship of Incidents Occurred in Tank Farm Based on the Method of Logistic Regression
A large number of incidents occurred in the petrochemical industry due to the continuous accumulation and frequent transfer of dangerous substances. For these historical incident data, a lot of efforts have been made to analyze how and why incidents occurred by use of descriptive statistics, while scarce work was done to in-depth explore the performance characteristics of the causal factors related to different types of incidents. This paper focuses on the relative importance of different causal factors for different types of incidents. A total of 1144 incidents related to tank farms of China during the period 1960–2018 were collected and classified with regard to the intuitive consequences of incidents (fire & explosion, material loss, quality variations, equipment damage and personnel harm) and whether the domino effect was involved (domino incidents and non-domino incidents). The causal factors were classified into five major categories and subdivided into fifteen subcategories. The interaction analysis of each factor with the specific consequence type was performed. The method of logistic regression was used to quantify the relative probability of different causal factors for different types of incidents and to determine which factors have a significant effect on triggering the domino incidents. It is found that human factors and organization/management factors were more common causal factors to lead to different consequences, and the same causal factor has distinct effects on the probability of occurrence for different types of incidents. The results highlight the more critical risk factors for each type of incident and the method can be applied to provide guidance on incident prevention and safety protection.
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