基于雷达数据的动态过程相关性在矿山斜坡滑动早期预警应用的研究
Yuejuan Chen1,2, Yang Liu1,2, Yaolong Qi1,2
1College of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080, China.
Sensors (Basel, Switzerland)
|August 10, 2024
概括
这项研究引入了一种新的方法,通过分析相位噪声和变形数据来预测露天煤矿斜坡滑动. 该技术准确预测滑坡事件,增强斜坡监测和预警系统.
科学领域:
- 地质技术工程 地质技术工程
- 遥感 遥感 遥感 遥感
- 矿业安全 矿业安全
背景情况:
- 由于业务的扩大,露天煤矿山坡安全性越来越复杂.
- 斜坡故障在采矿区对生命和财产构成重大风险.
研究的目的:
- 开发一种方法来预测露天煤矿的斜坡滑动时间.
- 分析相位噪声和变形之间的关系,用于早期预警.
主要方法:
- 利用差分InSAR (D-InSAR) 来从雷达监测数据中获得微变形.
- 从雷达回声数据中提取相位噪声和计算的变形体积.
- 开发了一个基于变形体积与阶段噪声标准偏差的触角的预测模型.
主要成果:
- 在案例研究区域中,确定的最大变形速率为10.1mm/h和6.65mm/h.
- 计算的最大变形体积为2,619,521.74mm3和2,503,794.206mm3.3的最大变形体积.
- 预测的滑坡时间比实际发生的时间更早,验证了该方法的有效性.
结论:
- 拟议的相位噪声和变形分析方法有效预测斜坡滑动事件.
- 该技术提高了斜坡监测和预警系统的准确性和可靠性.
- 提高了山坡监测和采矿作业早期预警的效率.
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