基于云贝叶斯网络盾构下穿铁路近接施工安全风险动态评价

周立

doi:10.13204/j.gyjzG22010711

基于云贝叶斯网络盾构下穿铁路近接施工安全风险动态评价

doi: 10.13204/j.gyjzG22010711

周立

武汉地铁集团有限公司, 武汉 430040

基金项目:

国家重点研发计划(2016YFC0800208)；国家自然科学基金项目(51378235,71571078,51308240)。

详细信息

作者简介:
周立,男,1985年出生,硕士,高级工程师。电子信箱:zhoul3515@wuhanrt.com

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- 文章访问数: 70
- HTML全文浏览量: 19
- PDF下载量: 1
- 被引次数: 0
出版历程
- 收稿日期: 2022-01-07

Dynamic Evaluation of Construction Safety Risk for Approaching Excavation of Shield Tunnel Undercrossing High-Speed Railway Based on Cloud Bayesian Network

ZHOU Li

Wuhan Metro Group Co., Ltd., Wuhan 430040, China

摘要

摘要: 提出云模型和贝叶斯网络相结合的安全风险动态评价方法,用于盾构下穿铁路近接施工复杂系统的安全研究。基于文献和大量工程经验建立盾构下穿铁路施工风险评价指标体系和评价标准。通过云模型实现连续节点状态的离散化,获取先验概率。构建云贝叶斯网络推理模型预测盾构下穿铁路施工安全风险的聚合概率分布,并生成综合云获取定量风险值,有效实现风险定性概念与定量数值大小的转化。结合敏感性分析和风险诊断,实现事前、事中、事后阶段的实时安全动态管控。以某下穿铁路工程为例,利用该方法有效评估了系统风险水平,并结合反向诊断确定重点管控因素,验证了该方法为实现盾构近接施工安全管理预警决策提供有力支持。
- 云模型 /
- 贝叶斯网络 /
- 盾构下穿铁路施工 /
- 安全风险 /
- 评价标准 /
- 动态评价 /
- 风险诊断
Abstract: A dynamic safety risk evaluation method combining cloud model and Bayesian network was proposed to study the safety of complex approaching excavation of shield tunnel undercrossing railway. Based on literature and a lot of engineering experience, the risk evaluation index system and evaluation standard of shield undercrossing railway construction were established. The state of continuous nodes was discretized through cloud model and the prior probability was obtained. The cloud bayesian network reasoning model was established to predict the aggregation probability distribution of the construction safety risk of shield tunneling railway, and the comprehensive cloud was generated to obtain quantitative risk values, which effectively realized the transformation of qualitative concept of risk and quantitative values. Combined with sensitivity analysis and risk diagnosis, real-time security dynamic control was realized in the stage before, during and after the event. Taking an undercrossing railway project as an example, the method was used to effectively evaluate the system risk level, and the key control factors were determined by reverse diagnosis. It was verified that the method could provide a strong support for the safety management and early warning decision of shield close construction.
- cloud model /
- bayesian networks /
- shield tunneling under high-speed railway construction /
- safety risk /
- evaluation criteria /
- dynamic evaluation /
- risk diagnosis

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参考文献(19)

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