寒区高铁隧道口边坡冻融失稳智能监测预警方法

doi:10.13229/j.cnki.jdxbgxb.20250577

摘要/Abstract

摘要：

针对寒区高铁隧道口边坡冻融失稳风险及监测数据孤立问题，本文提出融合北斗定位、毫米波雷达、InSAR等多源信息的“感知-传输-分析-预警”智能监测系统。该系统通过构建结构变形、环境扰动与异常响应3类指标，采用“点-线-面-体”部署策略，实现边坡状态的多维感知；同时，研发位移触发+图像复核+多源融合的预警模型，并开发数字化平台，实现风险分级响应。工程验证结果表明，该系统在冻融期具有高适应性，可有效识别滑坡前兆。

关键词: 道路工程, 寒区边坡, 冻融循环, 多源信息融合, 智能监测预警

Abstract:

Aiming at the freeze-thaw instability risks of high-speed railway tunnel portal slopes in cold regions and the issue of fragmented monitoring data， this paper proposes an intelligent monitoring system integrating multi-source information （including BeiDou positioning， millimeter-wave radar and InSAR） based on a "perception-transmission-analysis-warning" framework. The system constructs three categories of monitoring indicators—structural deformation， environmental disturbance， and abnormal response， and the "point-line-surface-volume" deployment strategy was adopted to achieve multi-dimensional perception of slope conditions. Furthermore， an early warning model incorporating displacement triggering， image verification， and multi-source fusion was developed， alongside a digital platform was developed to achieve risk hierarchical response. The results of engineering validation show that the system has high adaptability during freeze-thaw periods and can effectively identify landslides precursors.

Key words: road engineering, cold region slopes, freeze-thaw cycles, multi-source information fusion, intelligent monitoring and early warning

中图分类号:

李博,梁媛,马云东,于露. 寒区高铁隧道口边坡冻融失稳智能监测预警方法[J]. 吉林大学学报(工学版), 2025, 55(9): 2985-2997.

Bo LI,Yuan LIANG,Yun-dong MA,Lu YU. Intelligent monitoring and early warning for freeze⁃thaw instability of high⁃speed railway tunnel portal slopes in cold regions[J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(9): 2985-2997.

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监测类型	监测目标	监测项目	感知装置	精度说明
结构变形	坡顶、坡面、坡体监测点及对应区域的沉降位移	水平位移、垂直位移	北斗高精（毫米级）感知单元+北斗CORS站	水平±2.5 mm+0.5 ppm 垂直±3 mm+0.5 ppm
结构变形	坡体深层土体位移	角倾斜位移	固定测斜仪	±0.05 °
环境扰动	感知冻融期水热迁移（温度/含水率）及外部降雨输入，定位冻融相变	土体温度	土体温度传感器	±0.5 ℃
	感知冻融期水热迁移（温度/含水率）及外部降雨输入，定位冻融相变	土体含水率	土体湿度传感器	±1.5% VWC
	捕捉外部扰动事件	降雨量	雨量计	≤1%
异常响应	边坡坡面特定点状态图像	坡面特定点局部变化、防护栅栏状态	UWB单元感知模块
	实时动态影像监测	树木、危岩落石、异物侵限、防护栅栏状态等的实时图像	固定式毫米波雷达+角反射器+高清摄像头	变形监测精度≤±0.1 mm
	边坡局部点状态变化	边坡特定区域、特定时间内的坡面稳定状态图像	合成孔径雷达（InSAR）	精度≤±5 mm/年
	定期图像对比分析边坡状态变化	高分数据影像图像（监测周期大于InSAR图像监测周期）	高分数据影像分析单元	图像识别精度≤±1 pixel

预警等级	变形阶段	位移速率阈值/（mm·d^-1）	寒区特征参数	响应机制
四级（绿色）	初始变形	<0.5	地温<-5 ℃，含水率<18%	常规监测数据，每日汇总
三级（黄色）	等速变形	0.5~1.5	地温-5~0 ℃，含水率20%~25%	平台预警提示，每周现场巡查
二级（橙色）	加速变形	1.5~2.5	地温>0 ℃，裂缝扩展速率<1 mm/d	加密监测频次，启动应急值班
一级（红色）	加速临滑	>2.5	地温>5 ℃，裂缝扩展速率>1 mm/d	自动声光报警，联动线路封控，人员撤离

设备名称		均值/μ	均方差（S：σ_s）	均方差（P：σ_p）	统计阈值（μ+3σ）
1号设备	?H	0.28	5.31	5.25	16.13
1号设备	HD	2.86	2.76	2.73	11.10
2号设备	?H	-1.48	6.63	6.58	18.33
2号设备	HD	3.27	3.26	3.23	13.02
3号设备	?H	-0.03	4.49	4.43	13.34
3号设备	HD	1.17	0.91	0.90	3.88
4号设备	?H	-1.92	5.96	5.91	15.89