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雨量适应性滑坡监测框架集成FLAC3D数值模拟和多传感器优化:天山山脉的一个案例研究

Xiaomin Dai^1,2, Ziang Liu³, Qihang Liu³

¹School of Traffic and Transportation Engineering, Xinjiang University, Urumqi 830017, China.

Sensors (Basel, Switzerland)

|September 13, 2025

概括

本研究引入了一种优化的防滑监测传感器框架,通过整合数值模拟和适应性采样来改进预警系统,以捕捉降雨期间的关键水力机械过程.

科学领域:

地质技术工程地质技术工程
地质物理监测地质物理监测
环境科学环境科学

背景情况:

传统的山体滑坡监测系统在捕捉动态水力机械过程方面面临挑战,特别是在不和和和状态过渡期间.
在关键过渡期间的信号损失在降雨引起的山体滑坡监测中构成重大风险.
现有的方法往往缺乏准确性来识别关键的浅切削应变区.

研究的目的:

开发一个综合框架,以动态,基于风险的多传感器部署在山体滑坡监测.
建立一个合作的早期预警系统,降低虚假警报率.
创建一个适应性采样策略,以捕捉降雨事件期间的过渡性关键点.

主要方法:

在各种降雨场景下利用FLAC3D数值模拟进行合漏压力分析.
实施基于风险的传感器部署,优化纤维支格 (FBG) 密度和全球导航卫星系统 (GNSS) 间距.
开发了一个多参数合作的预警系统和基于降雨强度的适应性采样框架.

主要成果:

精确识别了浅切削应变度区域 (5-15米) 以优化传感器的放置.
建立了有效的早期预警值 (位移> 50 mm/h,孔隙水压> 0.4 MPa,应变> 6400 μm),减少了虚假警报.
在暴雨期间,证明了增强的测量频率 (GNSS采样速率高达10 Hz),以捕捉关键的过渡动态.

结论:

综合框架显著提高了在山体滑坡中捕捉关键的水力机械过渡过程.
拟议的方法为防范和管理斜坡灾害风险提供了科学 robust 和可靠的解决方案.
优化的传感器部署和自适应采样减少了监控冗余,同时在关键事件期间改进了数据采集.

关键词:

在FLAC3D中,可以使用FLAC3D.滑坡的监测和监测滑坡的监测和监测数字模拟的数字模拟.降雨引起的山体滑坡造成的山体滑坡传感器优化传感器优化

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