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Article(id=1208054447486374097, tenantId=1146029695717560320, journalId=1146123222451335185, issueId=1208054446576215005, articleNumber=1671-1807(2025)13-0006-08, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1731427200000, receivedDateStr=2024-11-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1765952224847, onlineDateStr=2025-12-17, pubDate=1752076800000, pubDateStr=2025-07-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1765952224847, onlineIssueDateStr=2025-12-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1765952224847, creator=13701087609, updateTime=1765952224847, updator=13701087609, issue=Issue{id=1208054446576215005, tenantId=1146029695717560320, journalId=1146123222451335185, year='2025', volume='25', issue='13', pageStart='1', pageEnd='310', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1765952224630, creator=13701087609, updateTime=1765952288340, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1208054713870815567, tenantId=1146029695717560320, journalId=1146123222451335185, issueId=1208054446576215005, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1208054713870815568, tenantId=1146029695717560320, journalId=1146123222451335185, issueId=1208054446576215005, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=6, endPage=13, ext={EN=ArticleExt(id=1208054447884832979, articleId=1208054447486374097, tenantId=1146029695717560320, journalId=1146123222451335185, language=EN, title=Research Status and Prospect of Landslide Monitoring Technology, columnId=1151876674645226399, journalTitle=Science Technology and Industry, columnName=Technology Innovation, runingTitle=null, highlight=null, articleAbstract=

The research of landslide monitoring technology plays a key role in preventing landslide disasters, which is not only reflected in the pre-disaster early warning, but also provides a theoretical basis in the post-disaster reconstruction. A clear understanding of the history of landslide monitoring technology can not only understand the development situation of landslide monitoring, but also contribute to the improvement and update of the monitoring technology in the future. Through summarizing the work of a large number of domestic and foreign scholars, the research progress of landslide monitoring technology was expounded from three historical stages: manual monitoring stage, semi-automatic and manual monitoring stage, and semi-intelligent and automatic monitoring stage. The main instruments and methods of common monitoring technology in each period are reviewed. Combining the latest landslide monitoring technology research status, some problems necessary for further research and discussion were proposed from the four perspectives of data inversion, technology comprehensive, intelligent and low-cost technology of landslide monitoring technology.

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滑坡监测技术研究在预防滑坡灾害中发挥着关键作用,不仅体现在灾前预警,在灾后的重整中也能提供理论依据。清楚认识滑坡监测技术历史不仅可以了解滑坡监测发展状况,也有助于监测技术的完善与更新。通过对国内外学者工作研究的总结,从3个历史阶段阐述滑坡监测技术研究进展,即人工监测阶段,半自动化、人工监测阶段,半智能、自动化监测阶段。对各个时期常用监测技术的主要仪器、方法进行评述。结合最新的滑坡监测技术研究现状,从滑坡监测技术的数据反演、技术综合、智能化以及技术低成本化4个角度提出今后滑坡监测技术需要进一步深入研究与探讨的问题。

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康钦容(1980—),女,重庆人,博士,副教授,研究方向为矿山安全与灾害治理
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=AGJ58U9+psuORLVao0vThQ==, magXml=u32/UowpoeXByxNY8+loqg==, pdfUrl=null, pdf=PZQMV+/QEHnDBRrNcUfq7g==, pdfFileSize=3540705, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=ZtXeY2SnJkBKgBWel62nCA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=FBzix2xtEb83pAj8Ryg0hA==, mapNumber=null, authorCompany=null, fund=null, authors=

邓荣斌(1979—),男,重庆人,工程师,研究方向为矿山安全;

陈俊宇(2002—),男,重庆人,工程师,研究方向为矿山顶板管理与控制;

吕麟(1979—),男,重庆人,工程师,研究方向为矿山顶板管理与控制;

赵洪宝(1980—),男,山东德州人,博士,教授,研究方向为矿山岩体力学与矿井瓦斯防治;

张卫中(1977—),男,河南漯河人,博士,教授,研究方向为矿山岩体力学与灾害治理。

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邓荣斌(1979—),男,重庆人,工程师,研究方向为矿山安全;

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邓荣斌(1979—),男,重庆人,工程师,研究方向为矿山安全;

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陈俊宇(2002—),男,重庆人,工程师,研究方向为矿山顶板管理与控制;

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陈俊宇(2002—),男,重庆人,工程师,研究方向为矿山顶板管理与控制;

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吕麟(1979—),男,重庆人,工程师,研究方向为矿山顶板管理与控制;

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吕麟(1979—),男,重庆人,工程师,研究方向为矿山顶板管理与控制;

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赵洪宝(1980—),男,山东德州人,博士,教授,研究方向为矿山岩体力学与矿井瓦斯防治;

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赵洪宝(1980—),男,山东德州人,博士,教授,研究方向为矿山岩体力学与矿井瓦斯防治;

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张卫中(1977—),男,河南漯河人,博士,教授,研究方向为矿山岩体力学与灾害治理。

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张卫中(1977—),男,河南漯河人,博士,教授,研究方向为矿山岩体力学与灾害治理。

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监测技术 检测方法 检测仪器 评述
传统
监测
技术		 传统大地测量法(三角测量法、导线测量法等) 相位式、脉冲式测距仪等 整个变形阶段检测都适用但受天气影响,精确度低
环境测量法(如地声测量法,水文测量法等) 地声探测仪,水位标尺,温度测量仪等 适用于边坡变形各个阶段,提供基本参考依据
缝隙测量法(手工,遥感等) 测缝仪,位移测量器等 人工测数据直观但费时;遥感测可远距离监控
应变测量法(测缝法,重锤法等) 重锤仪,多点位移计,斜向位移计等 适用于小型变位移以及切向位移,范围较小
新型
监测
技术		 新型大地测量法(3S4D技术) 卫星激光测距仪
甚长基线干涉测量仪等		 自动化程度提高,全天测量,不受地形通视的视角限制
TDR检测技术 同轴电缆,探头,控制器等 精度高、计算量小、方便实时实地测量
基于网络检测技术(GNSS网,传感器网等) 传感器,卫星导航系统等 高精确度,灵活性大,可全天候测量
基于InSAR检测技术(PS-InSAR/D-InSAR/InSAR检测技术) 合成孔径雷达,雷达传感器等 远距离监测,精确度达到毫米级
), ArticleFig(id=1208459470045295355, tenantId=1146029695717560320, journalId=1146123222451335185, articleId=1208054447486374097, language=CN, label=表1, caption=

常用滑坡监测技术评述

, figureFileSmall=null, figureFileBig=null, tableContent=
监测技术 检测方法 检测仪器 评述
传统
监测
技术		 传统大地测量法(三角测量法、导线测量法等) 相位式、脉冲式测距仪等 整个变形阶段检测都适用但受天气影响,精确度低
环境测量法(如地声测量法,水文测量法等) 地声探测仪,水位标尺,温度测量仪等 适用于边坡变形各个阶段,提供基本参考依据
缝隙测量法(手工,遥感等) 测缝仪,位移测量器等 人工测数据直观但费时;遥感测可远距离监控
应变测量法(测缝法,重锤法等) 重锤仪,多点位移计,斜向位移计等 适用于小型变位移以及切向位移,范围较小
新型
监测
技术		 新型大地测量法(3S4D技术) 卫星激光测距仪
甚长基线干涉测量仪等		 自动化程度提高,全天测量,不受地形通视的视角限制
TDR检测技术 同轴电缆,探头,控制器等 精度高、计算量小、方便实时实地测量
基于网络检测技术(GNSS网,传感器网等) 传感器,卫星导航系统等 高精确度,灵活性大,可全天候测量
基于InSAR检测技术(PS-InSAR/D-InSAR/InSAR检测技术) 合成孔径雷达,雷达传感器等 远距离监测,精确度达到毫米级
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滑坡监测技术研究现状与展望
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邓荣斌 1 , 陈俊宇 1 , 吕麟 1 , 康钦容 2 , 赵洪宝 3 , 张卫中 2
科技和产业 | 科技创新 2025,25(13): 6-13
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科技和产业 | 科技创新 2025, 25(13): 6-13
滑坡监测技术研究现状与展望
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邓荣斌1, 陈俊宇1, 吕麟1, 康钦容2, 赵洪宝3, 张卫中2
作者信息
  • 1 重庆铁公基工程安全检测技术有限公司, 重庆 401329
  • 2 武汉工程大学资源与安全工程学院, 武汉 430073
  • 3 中国矿业大学(北京)能源与矿业学院, 北京 100083

    • 邓荣斌(1979—),男,重庆人,工程师,研究方向为矿山安全;

    陈俊宇(2002—),男,重庆人,工程师,研究方向为矿山顶板管理与控制;

    吕麟(1979—),男,重庆人,工程师,研究方向为矿山顶板管理与控制;

    赵洪宝(1980—),男,山东德州人,博士,教授,研究方向为矿山岩体力学与矿井瓦斯防治;

    张卫中(1977—),男,河南漯河人,博士,教授,研究方向为矿山岩体力学与灾害治理。

通讯作者:

康钦容(1980—),女,重庆人,博士,副教授,研究方向为矿山安全与灾害治理
Research Status and Prospect of Landslide Monitoring Technology
Rongbin DENG1, Junyu CHEN1, Lin LÜ1, Qinrong KANG2, Hongbao ZHAO3, Weizhong ZHANG2
Affiliations
  • 1 Chongqing Tiegongji Engineering Safety Testing Technology Co., Ltd., Chongqing 401329, China
  • 2 School of Resources and Safety Engineering, Wuhan University of Engineering, Wuhan 430073, China
  • 3 School of Energy and Mining Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
出版时间: 2025-07-10
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摘要
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滑坡监测技术研究在预防滑坡灾害中发挥着关键作用,不仅体现在灾前预警,在灾后的重整中也能提供理论依据。清楚认识滑坡监测技术历史不仅可以了解滑坡监测发展状况,也有助于监测技术的完善与更新。通过对国内外学者工作研究的总结,从3个历史阶段阐述滑坡监测技术研究进展,即人工监测阶段,半自动化、人工监测阶段,半智能、自动化监测阶段。对各个时期常用监测技术的主要仪器、方法进行评述。结合最新的滑坡监测技术研究现状,从滑坡监测技术的数据反演、技术综合、智能化以及技术低成本化4个角度提出今后滑坡监测技术需要进一步深入研究与探讨的问题。

滑坡监测技术  /  现状  /  展望  /  滑坡灾害

The research of landslide monitoring technology plays a key role in preventing landslide disasters, which is not only reflected in the pre-disaster early warning, but also provides a theoretical basis in the post-disaster reconstruction. A clear understanding of the history of landslide monitoring technology can not only understand the development situation of landslide monitoring, but also contribute to the improvement and update of the monitoring technology in the future. Through summarizing the work of a large number of domestic and foreign scholars, the research progress of landslide monitoring technology was expounded from three historical stages: manual monitoring stage, semi-automatic and manual monitoring stage, and semi-intelligent and automatic monitoring stage. The main instruments and methods of common monitoring technology in each period are reviewed. Combining the latest landslide monitoring technology research status, some problems necessary for further research and discussion were proposed from the four perspectives of data inversion, technology comprehensive, intelligent and low-cost technology of landslide monitoring technology.

landslide monitoring technology  /  current status  /  outlook  /  landslide disaster
邓荣斌, 陈俊宇, 吕麟, 康钦容, 赵洪宝, 张卫中. 滑坡监测技术研究现状与展望. 科技和产业, 2025 , 25 (13) : 6 -13 .
Rongbin DENG, Junyu CHEN, Lin LÜ, Qinrong KANG, Hongbao ZHAO, Weizhong ZHANG. Research Status and Prospect of Landslide Monitoring Technology[J]. Science Technology and Industry, 2025 , 25 (13) : 6 -13 .
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中国作为一个地势复杂的国家,约60%的国土面积是山地和丘陵,许多地区每当产生剧烈的环境变化或频繁的人为活动都会发生地质灾害[1]。应对灾害发生的预防能力、灾害发生时紧急救援的避险能力、完善防灾体系、强化综合管理显得尤为重要[2]。鉴于露天矿山高陡边坡存在的安全隐患,以及近年来矿山事故频发的情况,为了加强矿山安全管理,提高边坡稳定性监测的准确性和及时性,国家应急管理部、中国林业产业联合会、中国国际科技促进会、河北省市场监督管理局分别发布了《金属非金属露天矿山高陡边坡安全监测技术规范》(AQ/T 2063—2018)、《露天矿山边坡安全监测技术规范》(T/LYCY3073—2024)、《高大边坡稳定安全智能监测预警技术规范》(T/CI 178—2023)、《金属非金属露天矿山采场边坡安全监测技术规范》(DB13/T 5958—2024),详细规定了露天矿山边坡在变形监测、采动应力监测、爆破振动监测、降雨和地下水监测等安全监测的内容、方法和预警等技术要求,监测系统的安装与运行要求,旨在提高监测的科学性和准确性,及时发现边坡变形风险,为露天矿山边坡的安全监测提供全面的技术指导。
滑坡灾害作为地质灾害中最频繁发生的事件,严重威胁国内外人民群众生命财产。滑坡监测的主要目的是预防滑坡灾害的发生,减少人民群众生命财产的损失,维护社会平稳。湖北省巴东县位于三峡库区腹地,是地质灾害多发区。为了有效应对地质灾害,巴东县采取了严密的滑坡监测措施,在滑坡体内开凿隧洞进行监测,设置了多个监测点,并安排监测员每天24 h值班,密切监测滑坡体的变化情况,成功预警并处置了多起突发地质灾害,创造了20年地质灾害零伤亡的奇迹。2006年2月17日菲律宾莱特岛Can-abag山发生了严重的滑坡灾害,造成大量人员伤亡和财产损失。在滑坡发生前,地质构造营力活跃、岩体结构破碎和极端降雨等危险因素已经被监测到。尽管采取了相应的监测和预警措施,但还是未能完全阻止滑坡的发生。通过科学的滑坡监测,对滑坡进行实时监测、预警和分析,可为滑坡灾害的预防和治理提供科学依据。因此研究滑坡监测技术,对预防滑坡发生,救助人民、维护社会平稳有重要的理论指导及现实意义。
1 滑坡监测技术综述
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近年来,随着科技的进步和监测技术的发展,国内外滑坡监测已经逐渐从人工监测向自动化、智能化方向发展。例如,在国内,许多山区已经安装了滑坡监测预警系统,通过全球定位系统(global position system,GPS)、合成孔径雷达(interferometric synthetic aperture radar,InSAR)等高精度监测技术,可以实时监测滑坡体的位移和变形情况,大大提高了监测的精确度和可靠性。同时,结合气象、地质等多源数据,还可以对滑坡灾害进行预警和风险评估。针对前人对滑坡监测技术的总结,可将其发展过程可以分为以下3个阶段。
1.1 人工监测阶段(1950年以前)
在这个阶段里,由于受到科技水平、相关理论以及监测仪器的制约,人们在监测过程中先从眼睛观察与耳朵倾听宏观滑坡变形程度,再用皮尺、罗盘、雨量计等仪器分别进行滑坡位移、倾斜度、降雨量等具体参数和环境影响因素测量,从而判断边坡失稳程度。
在这个时期里,滑坡监测主要依赖人工观察和使用简单仪器进行测量。滑坡监测精确度低,复杂度低,消耗大量人力资源。例如,在山区,当地居民和地质工作者常常通过肉眼观察滑坡体的变形情况,如裂缝的宽度、长度变化,以及滑坡体的位移等,同时利用皮尺、罗盘等工具进行简单的测量。此外,由于降雨是滑坡发生的重要诱因之一,因此雨量计也被广泛使用来监测降雨量,以评估其对滑坡稳定性的影响。然而,由于需要大量的人力资源进行持续观察和测量,因此监测成本较高,且受限于人的主观判断和观测条件,监测结果的准确性和可靠性也存在一定的局限性。
1.2 半自动化、人工监测阶段(1950—2000年)
该阶段随着科学水平的提高以及检测仪器的制作,伴随着数理统计与概率论、灰色理论、模糊数学等高等数学理论知识引入,滑坡监测方法得到了显著提升,进入半定量分析阶段。理论知识上,叶米里扬诺娃[3]深入研究总结出边坡失稳的由来、影响因子、产生原理以及整体变化趋势,为滑坡监测提供了重要的理论支持。Saito[4]通过室内室外实验总结推导出均质土滑坡预报公式并且成功防止一场滑坡灾害发生,这标志着滑坡监测技术在实践中的应用取得了重要突破。Hoek[5]利用类似Saito方法归纳总结出边坡失衡的外延法,进一步丰富了滑坡监测的理论体系。崔政权[6]首先使用地质工程学思维对滑坡进行检测分析,为滑坡监测提供了新的思路和方法。当时国内外比较流行的检测仪器[7]有方便测量孔洞竖直方向偏移量的杆式伸长器、带有数字显示模块的钻孔测斜仪、超视距电子水准仪、测量节理的岩石土检测器等。例如,在三峡库区科研人员利用先进的监测仪器和技术,对滑坡进行了长期、系统的监测和分析,为滑坡预警和防治提供了科学依据。
尽管滑坡监测技术在这一阶段取得了显著进步,滑坡监测工作仍然需要大量的人员进行实地观测和数据记录,还需要对数据进行后续处理分析,人力消费仍然很大。因此,如何在提高监测精度的同时降低人力成本,一直是滑坡监测领域需要解决的重要问题。
1.3 智能、自动化监测阶段(2000年至今)
该阶段随着人工智能、电子仪器、自动化机器的发展,滑坡监测技术得到了迅速发展与改善。可以分为以下6个大类。
1.3.1 3S4D监测技术
3S包含接受并处理来自地物的电磁波信息从而对其进行识别监控的远程遥感技术(RS),使用集成计算机运算设备存储并处理地理相关内容的地理信息系统(geographic information system,GIS),由美国构建并制作可以观测并摄影地形地貌的全球定位系统(GPS)。该类技术精确度较高,实时性比较好,适用于高空远距离滑坡监测分析。4D技术包含使用坡向图、等高线图等技术进行土方量、降雨量等地表形态分析的数字高程模型(digital elevation model,DEM),使用投影、坐标系统等技术进行地质调查的数字正射影像图(digital orthophoto map,DOM),使用几何矢量、色彩校正等技术进行数据集成分析的数字栅格地图(digital raster graphic,DRG)技术以及使用分幅、摄影等技术进行高精度解析制图的数字线划地图(digital line graphic,DLG)技术。3S4D监测技术组成如图1所示。
Gili等[8]使用全球定位系统监测西班牙东北部比利牛斯山脉的瓦尔塞布雷滑坡情况,相对于传统三角测量,导线生长计等测量手段更高效、准确。张建新等[9]、廖明生等[10]分别使用无人机遥感技术与雷达遥感技术远距离对复杂地形及大梯度滑坡变形进行测量与形变提取。3S4D技术监测精度高,实时性好,不受视角限制,可在全天进行。不过相关仪器价格高昂,不适于所有场合。
1.3.2 TDR检测技术
TDR(时域反射技术)最先用于处理信息交换问题,后被引入众多领域,在研究滑坡工程问题中,信号从发射机发出通过收发系统进入滑坡体中,当滑坡体发生位移等相关形变时,产生反射信号由接收机接收并进入处理器处理,最终在显示器上显示。其基本系统组成如图2所示。
其基本物理原理公式[11]为
V=2L/TR
式中:V为均匀物质里传播信号的速度;L为距离;TR为信号从探测物反射到反射器所经历的时间。
Yan等[12]对三峡水库重点灾害之一的重庆巫山玉皇阁滑坡分别使用了传统的倾角测试系统和时域反射技术进行深部形变测量,结果表明,TDR技术所测绘结果与倾角仪器结果相吻合,符合实际情况。Chung等[13]基于TDR检测技术,研发了大型直剪箱,使用新型物理模型,对探头类型、注浆环境、剪切范围、岩土类型进行了不同实验并准确地描绘了滑坡局部剪切面的产生及演化规律。该项技术可以有效测量土壤含水量,但是针对微小的位移变形不敏感,自动化程度低。不过制作简单,成本相对较低,使其应用范围很广。
1.3.3 TL-ERT技术
TL-ERT(时移电阻率层析成像技术)在地理工程与环境工程中有广泛的实际应用。第1阶段研究始于1995—2005年,针对滑坡监测,可以在极端环境天气中准确测量滑坡体表层含水率,更好地分析在降雨条件下土壤水饱和的阈值情况。其基本工作原理为
R=UΔT/Q
式中:R为电荷阻值;U为两端电势差;ΔT为时间差;Q为ΔT时间里流过的电荷量。电阻率层析成像技术原理如图3所示。
实际操作中,TL-ERT使用地下 2D 和 3D 静态电阻率图像的分析来处理电阻率图像的时间序列[14],从而获得土壤最表层含水量的时空变化规律。该项技术由于在探测中无辐射,可以自动测量,在国内外为重点研究技术之一。
1.3.4 PS-InSAR、D-InSAR、InSAR检测技术
InSAR(合成孔径雷达)干涉测量技术通过对比两组目标成像的强度及相位信息来获得整体大小位移等参数。焦志平等[15]利用InSAR检测技术分析了冻融及降雨条件下西藏东部地区滑坡情况,成功识别并预防了高原地区滑坡发生。Zhou等[16]利用卫星影像-多时相合成孔径雷达干涉测量(MT-InSAR)技术获取滑坡灾害的精细变形,实现了滑坡灾害的有效预防。D-InSAR(基于差分干涉法的InSAR)技术,分别从不同位置获取物体相关信息。PS-InSAR(基于散射体的InSAR测量)技术,在InSAR基础上,针对雷达波后向散射较强且在时序上较稳定的物体(如建筑物、岩石等)进行干涉测量,在滑坡检测中可以达到毫米级精确度。国外学者Hari等[17]通过该技术对由于降雨导致拉贾马拉山西坡发生毁灭性滑坡进行研究,分析相关水平及垂直位移,为相关灾害管理打下基础。张钟远等[18]利用短基线子集干涉测量技术(SBAS-InSAR)对木场古滑坡监测进行降轨影像数据处理,分析滑坡的时序变形量,得出了滑坡的变形与降雨量的相关性。InSAR系列技术在成像中比较清晰,不易受空气湿度、天气变化的影响,在滑坡检测中其相关原理图如图4所示。
1.3.5 传感器网络检测技术
传感器网络技术基本组成分为传感器单元、汇聚单元、处理单元,交叉了硬件技术、软件技术、现代网络技术、通信技术等通过各个微小传感器无时无刻对检测对象感知,实现了实时性计算。河南交院工程技术集团有限公司研发的“高大边坡与堤坝工程智能监测预警技术”,依托健康监测管理平台,通过监测采集地表位移、深层水平位移等传感器数据,实现了远程对在建和运营公路高大边坡的智能化监测与预警,并在2021年“7·20”郑州暴雨期间成功预警了河南栾卢高速建设项目所监测区域的边坡地表浅层滑塌事故。华北水利水电大学研发的“基于微波光子相移的滑坡灾变监测预警关键技术及应用”,在相位噪声抑制和光子信号相位编码方面进行了创新,利用微波光子技术监测边坡的微小振动,实现了滑坡的智能化预警。传感器网络基本构成如图5所示。
王智伟等[19]使用位移传感器构建网络,远距离对黑方台党川滑坡进行滑坡位移监测获得了实时有效信息。Li等[20]在甘肃省黑方台地区构建倾斜传感器网络,研究当地土质滑坡与倾角关系,并根据倾角成功预测了当地滑坡发生时间。Hao等[21]使用无线电波控制传感器网络对滑坡含水量、当地降雨量、滑坡位移变化进行测量监控,克服现场采集、效率低等问题,实现了实时监控。传感器网络技术是一种集成化技术,在滑坡检测中,具有避免人工劳作、全天候监测、实时性强等优点。
1.3.6 基于GNSS检测技术
全球导航卫星系统(global navigation satellite system,GNSS),包含中国自主研发的卫星导航系统BDS、苏联制造的第二代军用卫星系统GLONASS,欧盟制作的伽利略导航系统GALILEO、美国制造的导航系统GPS。GNSS技术作为21世纪高新技术之一,其位移监测站在全球范围内被用于边坡安全监测,特别是在地形复杂、地震频发的地区,如成渝高速鸡公山路段,通过在边坡关键位置安装GNSS监测设备进行边坡监测,实时获取边坡位移数据,实现了对边坡微小变化的精确监测。何玉童等[22]基于北斗导航系统对当地滑坡进行了全天候高精度监测分析。张清华等[23]使用卫星导航技术对渣土山形成的滑坡进行内表位移监控。
GNSS技术可以有效提高滑坡监测中自动化程度以及精确度问题。其相关组成结构如图6所示。
针对滑坡的不同特点,以及不同目标要求,学者们还研究使用了各种不同检测技术。例如,刘卫南和谢谍文[24]基于云点密度的三维激光扫描技术对黄藏寺滑坡平面位移进行识别。侯圣山等[25]基于传统测水仪、声光传感器、含水仪等对甘肃省滑坡灾害较为严重的兰州市和岷县进行毫米级滑坡位移变形测量。胡开颜等[26]基于自然电位法,通过分析坡体内自然电位变化得出滑坡孔隙水压力相关变化。张峰和裴华富[27]基于光频反射技术(OFDR),研制新型测斜仪对滑坡体进行了长期有效的检测。刘晓宇等[28]基于MEMS加速度计的倾角传感器对土质滑坡进行时空演化分析。
2 常用滑坡监测技术评述
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在研究了众多文献基础上,按照滑坡监测技术出现时间以及监测内容特点。将常用的滑坡监测技术分为传统监测技术和新型监测技术,相关评述见表1。
3 发展趋势展望
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滑坡监测技术随着时间推移愈发成熟,伴随科技进步和人工智能的兴起,检测手段日益多样化。结合当前最新研究成果,滑坡监测技术在数据反演、多种技术综合监测、自动化与系统化、监测软件优化等方面仍有进一步提升的空间。
3.1 滑坡监测技术应加强对数据反演的研究
随着时代发展,对边坡监测技术实时性有更高的要求,在对新型检测技术进行数据分析反演方法研究方面,可以使得数据获取更快速准确。例如,Oware等[29]、Delforge等[30]针对TLERT技术,引入典卡尔曼滤波器、贝叶斯马尔可夫链蒙特卡、聚类程序等数据反演技术,使得数据获取更快并且在后续状态中变化很小。目前,相关技术主要用于地球物力学,未来在研究滑坡监测相关方面,可跨学科借鉴新思维方法研究数据反演,可使后续处理分析更有效准确。
3.2 滑坡多种技术综合监测研究将加强
由于滑坡过程的复杂性,检测技术的单一使得数据获取受到阻碍、延迟。综合多种检测技术与手段,可使处于复杂地形地貌、不良气候的滑坡检测更准确有效。可将遥感技术和合成孔径雷达技术进行大范围检测[31];统筹无线传感器网络技术和北斗系统技术获得高效数据流[32];综合地面激光扫描技术、无人机技术、全球导航卫星系统定量分析滑坡变形及磨损状态[33];联合LiDAR高精度激光雷达和DEM数字高程模型对滑坡进行时序像素分析[34]。以后的滑坡监测可融合更多检测技术来进行。对滑坡进行实时有效控制。
3.3 滑坡智能监测技术——自动化与系统化加强
伴随着5G以及人工智能的快速发展,滑坡自动化监测系统的建立对于未来更加准确、省时地进行滑坡研究预测,以及应对复杂地形、多端天气对滑坡监测的影响具有重要意义。建立减灾棒设备(一种参数检测系统),设计计算机辅助自动化实时监测系统(EWS),建立远程滑坡监控网络以及高智能预警云平台网络系统等对滑坡进行监测控制[35-37]。
3.4 滑坡监测技术将往低成本化发展——监测软件算法、仪器、方法等优化
各种科学技术发展、新理论的诞生与跨学科交流将会使滑坡监测从以往检测精度低、人力资源耗费严重走向可靠的机器化发展。学者们针对各种滑坡监测系统算法,以及测量仪器、方法等方面进行优化,使得监测成本降低。针对TDR技术,设计低成本节能无线传感器用于滑坡快速变形监测[38];针对GNSS检测技术,研究设计开发了只有原先1/4体积的监测设备,使得每个设备研制成本降低2 000元左右[39];使用低成本微电子系统MEMS加速度计进行滑坡监测并记录了准确数据[40];基于物联网检测技术使用语音响应新技术,减少了通信过程中拒绝服务(denial of service,DoS)干扰,提高了数据可靠性并节能50%以上[41]。
4 结语
收起
目前,滑坡检测技术越来越成熟。从传统手工到遥感、三维激光再到大数据、5G。从地面地下监测到无人机,再到太空卫星监测[41-43],取得了令人可观的成就。在面对多变的滑坡灾害时,通过国内外学者共同努力,有望使检测技术更加高效、可靠、高自动化、低成本。
基金
收起
  • 国家自然科学基金(51804222)
文献
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2025年第25卷第13期
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  • 接收时间：2024-11-13
  • 首发时间：2025-12-17
  • 出版时间：2025-07-10
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  • 收稿日期：2024-11-13
基金
国家自然科学基金(51804222)
作者信息
    1 重庆铁公基工程安全检测技术有限公司, 重庆 401329
    2 武汉工程大学资源与安全工程学院, 武汉 430073
    3 中国矿业大学(北京)能源与矿业学院, 北京 100083

通讯作者:

康钦容(1980—),女,重庆人,博士,副教授,研究方向为矿山安全与灾害治理
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2种不同金属材料的力学参数
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Number of
species		 占总种数比例
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total species (%)		 属
Genus		 种数
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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