基于多源数据融合的尾矿坝溃坝风险评估方法研究

Research on risk assessment method for tailings dam failure based on multi-source data fusion

摘要

【目的】尾矿库溃坝事故作为一种高能级、低频率的极端突发事件，对下游人民生命财产安全构成严重威胁，为准确评估其溃坝风险，提出一种通过监测数据级和决策级融合的溃坝风险评估方法。【方法】基于尾矿库多源在线监测数据和四级风险体系框架，采用自适应加权融合算法(AWF)实现位移、最小干滩长度、浸润线等监测项目的数据级融合；针对D-S证据理论中的证据冲突问题，借助云模型构造基本概率分配(BPA),引入Wasserstein距离和改进的归一化投影方法(iNP)度量证据的冲突程度并构造融合权重，从而实现基于改进D-S证据理论的溃坝风险决策级融合。【结果】实例分析结果显示：应用所提方法对某尾矿坝进行风险评估的结果与实际一致，均为“低风险”,对评估结果支持度为0.891 5。【结论】结果表明：基于多源数据融合的风险评估模型相较于现有的典型改进方法对评估结果支持度更高，对尾矿坝进行风险评估更精确、可信度更高。

Abstract

[Objective] The tailings dam failure accident, as a high-energy, low-frequency extreme event, poses a serious threat to the safety of people's lives and property in the downstream. To accurately assess the risk of dam failure, a risk assessment method based on monitoring data-level and decision-level fusion is proposed. [Methods] Based on the multi-source online monitoring data of the tailings dam and a four-level risk system framework, an adaptive weighted fusion algorithm(AWF) was used to achieve data-level fusion of monitoring projects such as displacement, minimum dry beach length, and infiltration line. To address the issue of conflicting evidence in D-S evidence theory, the cloud model was used to construct the basic probability assignment(BPA). The Wasserstein distance and an improved normalized projection method(iNP) were introduced to measure the degree of conflict in the evidence bodies and construct fusion weights, thereby achieving decision-level fusion of dam failure risk based on the improved D-S evidence theory. [Results] The case analysis result showed that the application of the proposed method for risk assessment of a tailings dam yielded consistent result with actual observations, both indicating “low risk”, with a support degree of 0.891 5 for the assessment result. [Conclusion] The result indicate that the risk assessment model based on multi-source data fusion has a higher support degree for the assessment result compared to existing typical improved method, offering more accurate and reliable risk assessment for tailings dams.

关键词

多源数据融合 / 尾矿坝 / D-S证据理论 / 风险评估 / 冲突证据

Key words

multi-source data fusion / tailings dam / D-S evidence theory / risk assessment / conflicting evidence

基金资助

国家自然科学基金项目(42271026)