中国安全科学学报 ›› 2025, Vol. 35 ›› Issue (10): 174-180.doi: 10.16265/j.cnki.issn1003-3033.2025.10.1302

• 公共安全 • 上一篇    下一篇

基于模糊贝叶斯网络的城市排水管网风险评估

杨文家1(), 吴良洪2, 林卫东3, 阳富强1,**()   

  1. 1 福州大学 环境与安全工程学院,福建 福州 350108
    2 福州市城市排水有限公司, 福建 福州 350008
    3 福建省建筑设计研究院有限公司,福建 福州 350001
  • 收稿日期:2025-05-07 修回日期:2025-07-16 出版日期:2025-10-28
  • 通信作者:
    **阳富强(1982—),男,湖南耒阳人,博士,教授,主要从事公共安全与应急管理方面的研究。E-mail:
  • 作者简介:

    杨文家 (1999—),男,河南漯河人,硕士研究生,研究方向为安全科学与工程管理。E-mail: ;

    吴良洪 高级工程师;

    林卫东 教授级高级工程师

  • 基金资助:
    国家自然科学基金资助(52274181); 福建省科技计划项目(2023Y3001)

Risk assessment of urban drainage networks based on fuzzy Bayesian networks

YANG Wenjia1(), WU Lianghong2, LIN Weidong3, YANG Fuqiang1,**()   

  1. 1 College of Environment and Safety Engineering, Fuzhou University, Fuzhou Fujian 350108, China
    2 Fuzhou City Drainage Co., Ltd., Fuzhou Fujian 350008, China
    3 Fujian Provincial Institute of Architectural Design and Research Co., Ltd., Fuzhou Fujian 350001, China
  • Received:2025-05-07 Revised:2025-07-16 Published:2025-10-28

摘要: 为提升城市排水管网的事故预防与风险管控水平,首先,梳理“人-机-管-环”4个方面的指标,得到19项评估指标,构建城市排水管网风险评估指标体系;其次,融合模糊理论与贝叶斯网络(BN)构建城市排水管网风险评估模型,引入三角模糊数量化处理专家评分,基于职称与工龄差异赋予专家权重,并采用α加权估值法将模糊评价转化为清晰概率,开展BN的正反向推理,计算关键节点的后验概率;最后,以某城区排水管网为例,评估该区域排水管网的风险等级,完成现场验证。结果表明:城市排水管网风险评估模型能有效处理风险评估过程中的不确定性与主观性,概率化表征排水管网风险,显著提升评估结果的可靠性;管道的外加保护是影响排水管网安全性的关键因素,防腐措施和接口方式次之;该城市排水管网整体安全性良好,风险处于可控范围;通过与历史监测数据和故障记录的对比分析,验证了该模型具有一定的实用性和可靠性。

关键词: 贝叶斯网络(BN), 排水管网, 风险评估, 后验概率, 风险等级

Abstract:

In order to improve the ability of accident prevention and risk control of urban drainage networks, first of all, based on the indicators from the four aspects of "human-material-management-environment", 19 assessment indicators were obtained to construct the risk assessment index system of urban drainage pipe networks, and a risk evaluation index system for urban drainage networks was established accordingly. Subsequently, a model of urban drainage networks was constructed by integrating fuzzy theory and BN. Triangular fuzzy numbers were introduced to quantify the scores of experts. Weights were assigned according to differences in professional titles and working years, and α-weighted valuation method was adopted to transform fuzzy evaluations into clear probabilities. Thus, a risk evaluation model for urban drainage networks was obtained, and forward and reverse reasoning of BN was conducted to calculate the posterior probabilities of key nodes. Finally, taking the drainage network of a certain urban area as an example, the risk level of the drainage network in a specific area of the city was evaluated, and investigations were conducted for verification. The results indicate that the model effectively handles uncertainties and subjectivity in the risk assessment process, achieves probabilistic characterization of drainage network risks, and improves the accuracy of evaluation outcomes. External pipe protection is identified as the most critical factor affecting drainage network safety, followed by anti-corrosion measures and joint methods. The overall safety performance of the urban drainage network is found to be satisfactory, with risks remaining within controllable limits. Comparative analysis with historical monitoring data and fault records confirms the practicality and reliability of the model.

Key words: Bayesian network (BN), drainage network, risk assessment, posterior probability, risk level

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