A stope stability monitoring method based on displacement of stope feature points
By acquiring video streams from the mining area and utilizing edge detection and feature point matching technologies, the problems of low efficiency and insufficient accuracy of traditional monitoring methods are solved, enabling efficient and accurate monitoring of mining area stability, adapting to complex environments, and ensuring mining area safety.
CN122416355APending Publication Date: 2026-07-17FUZHOU UNIV +1
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- FUZHOU UNIV
- Filing Date
- 2026-03-06
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Traditional methods for monitoring the stability of metal mines rely on manual observation or simple sensors, which are inefficient and easily affected by environmental interference, resulting in insufficient monitoring accuracy.
Method used
By acquiring video streams from the mining area, edge detection algorithms are used to identify the mining area boundaries, extract and match feature point displacements, and trigger warnings based on preset rules, continuous and real-time monitoring of mining area stability is achieved.
Benefits of technology
It enables efficient and accurate monitoring of mining stability, adapts to complex environments, significantly improves the targeting and accuracy of monitoring, and ensures mining safety.
✦ Generated by Eureka AI based on patent content.
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Figure CN122416355A_ABST
Abstract
一种基于采场特征点位移的采场稳定性监测方法，其包括以下步骤：获取各摄像头的金属矿采场视频流；对视频流进行预处理，形成连续的多帧图像；基于边缘检测算法识别每一帧图像采场边界，划定对应的图像监测区域；提取每一帧图像监测区域内的特征点，筛选每一帧图像的有效特征点；将连续的多帧图像的有效特征点进行匹配，获得有效特征点位移；基于有效特征点位移根据预设规则触发警告；采用以上技术方案能够很好地适应金属矿采场光照变化、粉尘干扰等复杂环境，准确、高效地识别采场内特征点的位移，实现智能化的采场稳定性监测，保障采场的安全管理。
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