An Evaluation Method of Safety Resilience for Highway Bridge Engineering Based on an Entropy Weight and Improved TOPSIS Model
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摘要: 针对交通建设过程中不充分的安全管理导致的高速公路桥梁工程施工安全隐患问题,研究了面向桥梁工程施工的风险-隐患-事故全过程安全韧性水平评价方法。通过文献计量分析、WBS理论等方法将韧性引入交通工程安全评价,提出基于安全韧性理论的高速公路桥梁工程评价体系,分析高速公路桥梁工程施工安全韧性机理,形成以安全韧性“4R”特性为一级指标的高速公路桥梁工程施工安全韧性评价指标。传统熵权-逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)评价未考虑异常值对于评价结果的影响,运用统计检测法对异常值进行筛查与二次采集,同时选择熵权法优化权重赋权,构建基于熵权-改进TOPSIS法的桥梁工程安全韧性评价模型,实现对桥梁工程安全韧性的定量评价。本研究选择4条高速公路桥梁施工路段,对其安全韧性水平进行评价并对模型可行性进行分析。结果表明:乙、丁路段属于中等级韧性;甲、丙路段属于低等级韧性。在传统的风险评价法中,乙、丁路段总体风险等级为Ⅰ级,甲、丙路段总体风险等级为Ⅱ级。评价结果与实际施工情况相符,验证了该模型的有效性和可行性。提出的熵权-改进TOPSIS法能够在确定安全韧性等级的基础上进行敏感性分析,实现风险因素的溯源,帮助决策者进行事前针对性改善。Abstract: Targeting to the safety risks in freeway bridge construction caused by inadequate safety management, this paper develops a safety resilience evaluation method for bridge construction considering the full lifecycle of risk-hazard-accident. Based on bibliometric analysis and WBS theory, the concept of resilience is integrated into safety evaluation for traffic engineering. An evaluation system for freeway bridge engineering based on safety resilience theory is proposed, where the safety resilience mechanism of freeway bridge construction is investigated and evaluation index system with"4R"characteristics as primary indicators are developed. Given that traditional technique for order preference by similarity to an ideal solution (TOPSIS) evaluation does not account for the impact of outliers, statistical methods are used to screen and resample the outliers. Meanwhile, entropy weight method is adopted to optimize the weights of indices. By doing so, an entropy weight-improved TOPSIS model is developed for safety resilience evaluation of bridge engineering. Four freeway sections containing bridge construction are selected and their levels of safety resilience are evaluated using the proposed model, whose feasibility is analyzed as well. Results show Sections B and D have a medium level of safety resilience, while Sections A and C have a low level. Comparing to the results from the traditional risk assessment method that Sections B and D are Level Ⅰ and Sections A and C are Level Ⅱ, results from the proposed model align with real situations. Therefore, the validity and feasibility of the model are confirmed. To sum up, the proposed entropy weight-improved TOPSIS model enables sensitivity analysis and risk factor tracing, and further contributes to targeted preemptive improvements for decision-makers.
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Key words:
- bridge engineering /
- construction safety /
- safety resilience /
- entropy weight method /
- TOPSIS
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表 1 安全生产要素重点汇总
Table 1. Key summary of safety production elements
安全生产要素类型 主要表现 人员 技术人员、施工操作人员、管理人员的不安全行为 机械材料 机械设备的自身健康状况、适用性、可用性 技术 施工技术及方案合理性、施工工艺先进性、新技术新工艺普及性 管理 项目隐患排查治理体系、施工监控量测、安全主体责任、安全监管、施工安全培训及交底 环境 地质水文条件、施工自然环境(雨雪冰雹温度等) 表 2 高速公路工程桥梁施工安全韧性评价指标体系
Table 2. Evaluation index system for safety resilience of highway engineering bridge construction
一级指标 二级指标 评价等级范围 依据 优秀 良好 一般 较差 鲁棒性 高中及以上文化程度百分比/% > 75~100 > 50~75 > 20~50 > 0~20 ① 技术交底情况 > 75~100 > 50~75 > 25~50 > 0~25 ①② 现场巡检情况 > 75~100 > 50~75 > 25~50 > 0~25 ①② 安全培训情况 > 75~100 > 50~75 > 25~50 > 0~25 ① 工人日工作时长/h > 0~9 > 9~12 > 12~14 > 14~24 ①③ 自然条件 > 75~100 > 50~75 > 20~50 > 0~20 ①⑤ 安全预算投入百分比/% > 2.6~5 > 2.1~2.6 > 1.6~2.1 > 0~1.6 ④ 施工工艺成熟度 > 75~100 > 50~75 > 25~50 > 0~25 ①②④⑤ 施工工艺复杂程度 > 75~100 > 50~75 > 25~50 > 0~25 ①②③ 安全设施布设 > 75~100 > 50~75 > 25~50 > 0~25 ②③⑤ 机械设备管理 > 75~100 > 50~75 > 25~50 > 0~25 ①⑤ 施工便道设置 > 75~100 > 50~75 > 25~50 > 0~25 ⑥ 冗余性 极端天气管理制度 > 85~100 > 50~85 > 20~50 > 0~20 ①②③ 安全与应急技能培训情况 > 85~100 > 50~85 > 20~50 > 0~20 ①②⑤ 应急防护意识 > 85~100 > 50~85 > 20~50 > 0~20 ①②⑤ 岗前应急培训 > 85~100 > 50~85 > 20~50 > 0~20 ①②⑤ 设备先进适用性 > 85~100 > 50~85 > 20~50 > 0~20 ②⑤ 设备故障率/% > 0~5 > 5~10 > 10~20 > 20~100 ①④⑤ 应急设施设备 > 85~100 > 50~85 > 20~50 > 0~20 ④⑤ 快速性 现场安全员配备比例/ (x104m2 /人) > 5~10 > 3'5 > 2~3 > 0~2 ①③④⑤ 安全组织机构完善度 > 75~100 > 50~75 > 25~50 > 0~25 ①④⑤ 分包单位资质 > 75~100 > 50~75 > 25~50 > 0~25 ②④⑤ 季度应急演练次数/次 > 10~15 > 7~10 > 4~7 > 0~4 ①②④⑤ 安全监测系统完善度 > 75~100 > 50~75 > 25~50 > 0~25 ②④⑤ 智慧性 摄像头覆盖百分比/% > 90~100 > 75~90 > 60~75 > 0~60 ③⑦ 传感器抽样检查合格率/% > 95~100 > 85~95 > 75~85 > 0~75 ②③⑦ 传感器布设百分比/% > 90~100 > 75~90 > 60~75 > 0~60 ②③⑦ 自动化管理水平 > 75~100 > 50~75 > 25~50 > 0~25 ②③⑦ 智能设备配备台数百分比/% > 90~100 > 70~90 > 50~70 > 0~50 ②③⑦ 指标参考来源:①《公路水运工程施工安全风险评估指南:第2部分:桥梁工程》;②JTG B05—2015《公路项目安全性评价规范》;③《公路交通安全设施施工技术规范》;④公路工程技术标准;⑤JTGT 3650—2020《公路桥涵施工技术规范》;⑥JTG D20—2017《公路路线设计规范》;⑦T/CIIA 015-2022《智慧工地建设规范》。 表 3 安全韧性评价方法比选
Table 3. Comparison and selection of safety resilience evaluation methods
评价方法 优点 缺点 层次分析法 可将复杂的问题层次化,更具条理 未充分利用已有定量信息。 模糊故障树分析 可评价潜在安全隐患事故发生可能性。 处理不确定性问题时存在缺陷。 遗传算法 可以进行多个个体的同时比。 编程实现比较复杂且参数选择影响解的品质。 模糊综合评价法 能够反映评价指标间的相对重要性;能够有效应对模糊、不确定的信息。 主观性较强,综合评价结果存在偏差信息时很难进行有效评价。 物元可拓分析法 可以根据实际情况选取重要的参数 无法体现评价对象的主动参与;只考虑评价向量中最大分量 模糊物元评价方法 可将评价对象与理想解和负理想解作比较,从而判断优劣。 实际计算中运算量大,运算过程复杂 人工神经网络评价法 充分考虑专家的经验和直觉思维模式 要求样本数据具有时间序列特性,操作性差 LEC法 综合考虑多个因素之间的关系和权重 主观性较强 熵权-TOPSIS法 评价结果客观真实;计算结果精度较高;能够较为全面的获取利用指标 应用范围有限 表 4 指标权重确定
Table 4. Determination of indicator weight
一级指标 二级指标 熵值 权重 正理想解 负理想解 鲁棒性 高中及以上文化程度百分比 0.710 19 0.031 41 0.031 41 0.000 03 技术交底情况 0.734 44 0.028 78 0.028 78 0.000 03 现场巡检情况 0.703 21 0.032 17 0.032 17 0.000 03 安全培训情况 0.730 59 0.029 20 0.029 20 0.000 03 工作时长 0.729 95 0.029 27 0.029 27 0.000 03 自然条件 0.778 16 0.024 04 0.024 04 0.000 02 安全预算投入百分比 0.750 37 0.027 05 0.027 06 0.000 03 施工工艺成熟度 0.460 12 0.058 51 0.058 52 0.000 06 施工工艺复杂程度 0.765 57 0.025 41 0.025 41 0.000 03 安全设施布设 0.729 95 0.029 27 0.029 27 0.000 03 机械设备管理 0.493 45 0.054 90 0.054 90 0.000 05 施工便道设置 0.729 95 0.029 27 0.029 27 0.000 03 冗余性 极端天气管理制度 0.703 21 0.032 17 0.032 17 0.000 03 安全与应急技能培训情况 0.478 13 0.056 56 0.056 56 0.000 06 应急防护意识 0.692 66 0.033 31 0.033 31 0.000 03 岗前应急培训 0.743 11 0.027 84 0.027 84 0.000 03 设备先进适用性 0.703 21 0.032 17 0.032 17 0.000 03 设备故障率 0.750 37 0.027 05 0.027 06 0.000 03 应急设施设备 0.729 95 0.029 27 0.029 27 0.000 03 快速性 现场安全员配备比例 0.460 12 0.058 51 0.058 52 0.000 06 安全组织机构完善度 0.729 95 0.029 27 0.029 27 0.000 03 分包单位资质 0.743 11 0.027 84 0.027 84 0.000 03 每季度应急演练次数 0.750 37 0.027 05 0.027 06 0.000 03 安全监测系统完善度 0.362 16 0.069 13 0.069 13 0.000 07 智慧性 摄像头覆盖百分比 0.761 26 0.025 87 0.025 88 0.000 03 传感器抽样检查合格率 0.761 26 0.025 87 0.025 88 0.000 03 传感器布设百分比 0.666 87 0.036 10 0.036 11 0.000 04 自动化管理水平 0.649 89 0.037 94 0.037 95 0.000 04 智能设备配备台数百分比 0.771 28 0.024 79 0.024 79 0.000 02 表 5 安全韧性等级划分表
Table 5. Classification table of security resilience levels
安全韧性等级 安全韧性总体得分 高等级韧性(Ⅰ级) >0.90~1 较高等级韧性(Ⅱ级) >0.75~0.90 中等级韧性(Ⅲ级) >0.50~0.75 低等级韧性(Ⅳ级) ≤0.5 表 6 桥梁施工安全总体风险分级标准
Table 6. Overall risk classification standards for bridge construction safety
风险等级 R 重大风险(Ⅳ级) > 60 较大风险(Ⅲ级) > 45~60 一般风险(Ⅱ级) > 30~45 较小风险(Ⅰ级) 30 表 7 总体安全风险等级
Table 7. Overall safety risk grade
路段 风险等级 甲 Ⅱ级 乙 Ⅰ级 丙 Ⅱ级 丁 Ⅰ级 -
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