基于模糊Petri网和HAZID方法的过程工业火灾风险评估系统及其应用

IF 1.7 4区工程技术 Q3 ENGINEERING, INDUSTRIAL

Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability Pub Date : 2023-09-02 DOI:10.1177/1748006x231195201

Xingbai Chen, Ziyun Wang, Cheng Zhang, Yue Xiang, Yiyang Dai

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引用次数: 0

摘要

过程工业的安全风险评估可以确定安全风险的程度，并根据事故发生的概率提醒或警示安全管理人员采取相应的措施。本文将危险识别(HAZID)方法与模糊Petri网相结合，构建了一个混合安全评价体系。首先，根据火灾统计数据确定HAZID的火灾危险因素。通过将整个工业过程划分为4个阶段，对工厂内的复杂危险源进行逐项调查，构建实时风险评估的模糊Petri网。本文以某醋酸企业为例，详细介绍了如何构建该风险评估体系，该体系能够随着工艺条件的变化动态预测风险。这也证明了该方法的可行性，可为相关研究提供参考。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A fire risk assessment system and application for process industry using fuzzy Petri net and HAZID method

The safety risk assessment of process industries can determine the degree of safety risk and remind or warn safety management personnel to take corresponding measures according to the probability of accidents. In this paper, hazard identification (HAZID) method is combined with fuzzy Petri net to construct a hybrid safety assessment system. Firstly, the fire risk factors of HAZID are determined according to the fire statistics data. By dividing the whole industrial process into four stages, the complex hazard sources in the factory are investigated item by item, thus the fuzzy Petri net of real-time risk assessment is constructed. Taking an acetic acid enterprise as a case, this paper introduces how to construct such a risk assessment system in detail, and the system can dynamically predict the risk with changes in process conditions. This also demonstrates the feasibility of this method, which can be used as a reference for related research.

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来源期刊

Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability ENGINEERING, MULTIDISCIPLINARY-ENGINEERING, INDUSTRIAL

CiteScore

4.50

自引率

19.00%

发文量

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