辽宁石油化工大学学报

辽宁石油化工大学学报 ›› 2022, Vol. 42 ›› Issue (4): 47-52.DOI: 10.3969/j.issn.1672-6952.2022.04.009

• 机械工程 • 上一篇    下一篇

基于DBN的气化炉故障动态风险评估

马梦迪1(), 多依丽1(), 孙铁2   

  1. 1.辽宁石油化工大学 环境与安全工程学院,辽宁 抚顺 113001
    2.辽宁石油化工大学 机械工程学院,辽宁 抚顺 113001
  • 收稿日期:2021-11-08 修回日期:2021-11-29 出版日期:2022-08-25 发布日期:2022-09-26
  • 通讯作者: 多依丽
  • 作者简介:马梦迪(1997⁃),女,硕士研究生,从事煤化工装置动态风险评估研究;E⁃mail:1948861025@qq.com
  • 基金资助:
    国家重点研发计划资助项目(2018YFC0808500)

Dynamic Risk Assessment of Gasifier Failure Based on DBN

Mengdi Ma1(), Yili Duo1(), Tie Sun2   

  1. 1.School of Enviromental & Safety Engineering,Liaoning Petrochemical University,Fushun Liaoning 113001,China
    2.School of Mechanical Engineering,Liaoning Petrochemical University,Fushun Liaoning 113001,China
  • Received:2021-11-08 Revised:2021-11-29 Online:2022-08-25 Published:2022-09-26
  • Contact: Yili Duo

摘要:

气化炉是水煤浆气化系统的主要设备,为研究气化炉故障对气化系统的影响,提出一种基于动态贝叶斯网络与风险矩阵相结合的动态风险评估方法。以气化炉故障为例,首先建立了气化炉的动态贝叶斯网络模型,结合模糊评价方法计算根节点事件的先验概率,引入动态贝叶斯网络推算其后验概率;随后,基于层次分析法和Borda的原理,建立气化炉故障的综合风险评估体系,并引入维修因素,预测维修后气化炉的风险趋势并绘制了动态风险矩阵。结果表明,引入维修因素后系统整体风险水平显著下降,证明了维修因素对系统的积极作用,保障了系统的生产能力。

关键词: 动态贝叶斯网络, 风险矩阵, 气化炉, 动态风险评估

Abstract:

Gasifier is the main equipment of CWS gasification system. In order to study the influence of gasifier failure on gasification system, a dynamic risk assessment method based on dynamic Bayesian network and risk matrix is proposed in this paper. Taking the gasifier failure as an example, the dynamic Bayesian network model of the gasifier was first established, and the prior probability of the root node event was calculated by combining the fuzzy evaluation method, and the dynamic Bayesian network was introduced to calculate the posterior probability. Then, based on the principle of analytic hierarchy process (ahp) and Borda, a comprehensive risk assessment for gasifier failure was established, and maintenance factors were introduced to predict the risk trend of the gasifier after maintenance and draw a dynamic risk matrix. The results show that the risk of the system decreases after the maintenance factor is introduced, which proves that the maintenance factor has a positive effect on the system and guarantees the production capacity of the system

Key words: Dynamic Bayesian network, Risk matrix, Gasifier, Dynamic risk assessment

中图分类号: 

引用本文

马梦迪, 多依丽, 孙铁. 基于DBN的气化炉故障动态风险评估[J]. 辽宁石油化工大学学报, 2022, 42(4): 47-52.

Mengdi Ma, Yili Duo, Tie Sun. Dynamic Risk Assessment of Gasifier Failure Based on DBN[J]. Journal of Liaoning Petrochemical University, 2022, 42(4): 47-52.

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链接本文: http://journal.lnpu.edu.cn/CN/10.3969/j.issn.1672-6952.2022.04.009

               http://journal.lnpu.edu.cn/CN/Y2022/V42/I4/47