基于结构变量动态贝叶斯网络的煤炭泥制备系统的动态风险评估
Ming Liu1, Liping Wu2, Mingjun Hou1
1School of Environment and Safety Engineering, Liaoning Petrochemical University, Fushun, Liaoning, China.
PloS one
|May 21, 2024
概括
本研究介绍了一种动态风险评估方法,用于煤泥系统,使用弓带 (BT) 模型和结构变量动态贝叶斯网络 (SVDBN). 该方法通过识别风险并提出预防措施来提高系统可靠性,从而提高安全管理.
科学领域:
- 工业安全 工业安全 工业安全
- 风险管理 风险管理
- 贝叶斯网络 贝叶斯网络 贝叶斯网络
背景情况:
- 煤泥制备系统面临着重大的安全挑战.
- 有效的安全管理需要强大的风险评估方法.
- 动态分析对于理解不断变化的系统风险至关重要.
研究的目的:
- 建立煤炭泥制备系统的动态风险评估方法.
- 将BT模型与结构变量动态贝叶斯网络 (SVDBN) 集成.
- 确定针对性安全干预的关键风险因素和弱点.
主要方法:
- 使用SVDBN算法将BT模型转换为静态贝叶斯网络 (BN) 模型.
- 通过Python编程来减去风险因素和预防措施.
- 模拟和与GeNIe软件进行比较以进行验证.
主要成果:
- 拟议的方法准确地评估了随着时间的推移系统故障率.
- 维护因素被证明可以显著提高系统可靠性.
- 模拟结果与已知软件 (GeNIe) 的结果非常相匹配.
结论:
- 开发的动态风险评估方法为增强煤系统安全提供了理论基础.
- BT和SVDBN模型的整合为风险分析提供了一个强大的工具.
- 考虑维护因素对于优化系统可靠性和安全性至关重要.
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