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金属矿山 ›› 2025, Vol. 54 ›› Issue (7): 172-181.

• 安全与环保 • 上一篇    下一篇

基于 AHP-EWM 与多源数据的尾矿库安全风险动态 监测评价 

冯  威1   张小龙1   唐立鹤1   孙铭骏1   骆明华2,3    

  1. 1. 辽宁首钢硼铁有限责任公司,辽宁 丹东 118000;2. 金属矿山开采安全与灾害防治全国重点实验室,安徽 马鞍山 243000; 3. 非煤露天矿山灾害防控国家矿山安全监察局重点实验室,安徽 马鞍山 243000
  • 出版日期:2025-07-15 发布日期:2025-08-12
  • 作者简介:冯  威(1988—),男,总经理,工程师。
  • 基金资助:
    “十三五”国家重点研发计划项目(编号:2020YFC1909801);中国工程院战略研究与咨询项目(编号:2024-XZ-28-01)。 

Dynamic Monitoring and Evaluation of Safety Risk in Tailings Reservoir Based on AHP-EWM and Multi-source Data 

FENG Wei 1   ZHANG Xiaolong 1   TANG Lihe 1   SUN Mingjun 1   LUO Minghua 2,3    

  1. 1. Liaoning Shougang Boron Iron Co. ,Ltd. ,Dandong 118000,China;2. State Key Laboratory of Metal Mine Mining Safety and Disaster Prevention and Control,Maanshan 243000,China; 3. Key Laboratory of Disaster Prevention and Control for Non-coal Open-pit Mines,Maanshan 243000,China
  • Online:2025-07-15 Published:2025-08-12

摘要: 尾矿库作为矿业生产中存储和处理废弃物的重要设施,其安全运行直接影响着周边环境和居民的生命 财产安全。 我国尾矿库数量众多,一旦发生溃坝等事故,可能导致严重的环境污染和人员伤亡。 精准评价尾矿库的安 全风险是实现尾矿库安全管理和风险防控的前提条件和关键技术。 针对传统评价方法缺乏对实时动态数据考虑的 不足,提出了一种层次分析法(Analytic Hierarchy Process,AHP)和熵权法(Entropy Weight Method,EWM)相结合的尾矿 库安全风险动态监测评价模型。 首先,系统梳理了国内外尾矿库安全风险评价的研究现状,详细分析了危险源和安 全风险,确定了涵盖库区周边环境、排洪系统、尾矿坝等 7 个方面的 38 个影响因子,构建了全面的安全风险评价指标 体系。 其次,将多源数据划分为静态数据和动态数据,采用 AHP-EWM 组合赋权方法计算各影响因子的综合权重,构 建了静态因子与动态因子相结合的安全风险动态评价模型,并将其嵌入在线监测预警系统,实现了尾矿库安全风险 的实时动态评价。 最后,以青山尾矿库为例进行实证分析,评价结果显示尾矿库处于安全状态,与人工定期核查结果 一致,验证了模型的有效性和准确性。 所提模型能够全面、科学地反映尾矿库的安全风险等级,为尾矿库安全管理和 风险防控提供了有力的技术支撑。 

关键词: 尾矿库  安全风险评价  层次分析法  熵权法  动态评价

Abstract: As an important facility for storing and disposing of waste in mining production,the safe operation of tailings reservoir directly affects the surrounding environment and the safety of residents′ lives and property. Due to the large number of tailings reservoirs in China,once an accident such as dam break occurs,it may lead to serious environmental pollution and casualties. Accurately evaluation the safety risks of tailings reservoir is a prerequisite and key technology for achieving safe management and risk prevention and control of tailings reservoir. This article proposes a dynamic monitoring and evaluation model for tailings pond safety risk,which combines the Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM),in response to the lack of consideration of real-time dynamic data in traditional evaluation methods. Firstly,the research status of safety risk evaluation of tailings reservoir at home and abroad was systematically reviewed,and the hazards and safety risks were analyzed in detail. A comprehensive safety risk evaluation index system was constructed,which included 38 influencing factors covering seven aspects,including the surrounding environment of the reservoir area,flood discharge system,and tailings dam. Secondly,the multi-source data is divided into static data and dynamic data,and the AHP-EWM combined weighting method is used to calculate the comprehensive weight of each influencing factor. A dynamic safety risk evaluation model combining static and dynamic factors is constructed and embedded into the online monitoring and early warning system,achieving real-time dynamic evaluation of the safety risk of the tailings reservoir. Finally,an empirical analysis was conducted using the Qingshan tailings reservoir as an example. The evaluation results showed that the tailings reservoir was in a safe state,consistent with the results of regular manual inspections,validating the effectiveness and accuracy of the model. The model proposed in this study can comprehensively and scientifically reflect the safety risk level of tailings reservoirs,providing strong technical support for the safety management and risk prevention and control of tailings reservoirs. 

Key words: tailings reservoir,security risk evaluation,AHP,EWM,dynamic evaluation 

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