Center for Rock Instability and Seismicity Research, Northeastern University

为克服单一信息源无法精确表征矿山滑坡灾害演化特征的问题，基于多源信息融合技术，从矿山边坡多源信息获取、矿山边坡多源信息融合、矿山边坡位移预测及滑坡风险评价3个方面概述了矿山边坡滑坡灾害研究进展。总结了典型的“天”“空”“地”边坡监测手段及“天−空−地”一体化协同监测方法；梳理了包含数据级、特征级和决策级融合的边坡多源信息融合流程；整理了位移与应力、位移与水文气象及其他不同类型的监测数据融合形式；阐述了基于多源信息融合的边坡位移预测及滑坡风险评价相关研究现状。基于当前矿山边坡滑坡灾害研究存在的灾害分析的准确性严重依赖监测数据质量、对岩石力学机理知识利用不足等问题，指出了矿山边坡滑坡灾害研究发展趋势：统一多源数据采集接入标准；开发监测数据与岩石力学机理融合的矿山边坡滑坡灾害分析方法；优化“天−空−地”多源信息的时空关联挖掘算法；加强基于多源信息融合的矿山边坡滑坡灾害预警平台建设。

In order to overcome the problem that a single information source cannot accurately characterize the evolution features of mining landslide disasters, based on multi-source information fusion technology, this paper summarizes the research progress of mine slope landslide disasters from three aspects: multi-source information acquisition of mine slopes, multi-source information fusion of mine slopes, and mine slope displacement prediction and landslide risk assessment. The study summarizes typical slope monitoring methods of "sky", "air", and "ground" , as well as integrated collaborative monitoring method of "sky-air-ground". The study sorts out the slope multi-source information fusion process that includes data level, feature level, and decision level fusion. The paper organizes the fusion forms of displacement and stress, displacement and hydrological and meteorological monitoring information, as well as other different types. This paper elaborates on the current research status of slope displacement prediction and landslide risk assessment based on multi-source information fusion. The accuracy of disaster analysis in current research on mine slope landslide disasters heavily depends on the quality of monitoring data and insufficient utilization of knowledge of rock mechanics mechanisms. Based on the above problems, the development trends of research on landslide disasters in mine slopes are pointed out. The multi-source data collection and access standards are unified. The method for analyzing landslide disasters in mine slopes is developed by integrating monitoring data with rock mechanics mechanisms. The spatiotemporal association mining algorithm for multi-source information from the "sky-air-ground" is optimized. The construction of a mine slope landslide disaster warning platform based on multi-source information fusion is strengthened.

“十四五”国家重点研发计划项目（2022YFC2903903）；国家自然科学基金青年基金项目（52304167）；中央高校基本科研业务费专项项目（N2301020）；辽宁省自然科学基金联合基金项目（2023-MSBA-122）。

李荟，韩晓飞，朱万成，等. 基于多源信息融合的矿山边坡滑坡灾害研究现状与展望[J]. 工矿自动化，2024，50（6）：6-15.

LI Hui, HAN Xiaofei, ZHU Wancheng, et al. Current status and prospects of research on landslide disasters in mine slopes based on multi-source information fusion[J]. Journal of Mine Automation，2024，50（6）：6-15.