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无人机技术在超高陡边坡危岩体半自动识别中的应用

程雨柯, 李亚虎, 夏金梧, 侯赠, 陈娜

程雨柯,李亚虎,夏金梧,等. 无人机技术在超高陡边坡危岩体半自动识别中的应用[J]. 中国地质灾害与防治学报,2024,35(1): 143-154. DOI: 10.16031/j.cnki.issn.1003-8035.202310028
引用本文: 程雨柯,李亚虎,夏金梧,等. 无人机技术在超高陡边坡危岩体半自动识别中的应用[J]. 中国地质灾害与防治学报,2024,35(1): 143-154. DOI: 10.16031/j.cnki.issn.1003-8035.202310028
CHENG Yuke,LI Yahu,XIA Jinwu,et al. Application UAV technology semi-automatic identification dangerous rock masses on ultra-high steep slopes[J]. The Chinese Journal of Geological Hazard and Control,2024,35(1): 143-154. DOI: 10.16031/j.cnki.issn.1003-8035.202310028
Citation: CHENG Yuke,LI Yahu,XIA Jinwu,et al. Application UAV technology semi-automatic identification dangerous rock masses on ultra-high steep slopes[J]. The Chinese Journal of Geological Hazard and Control,2024,35(1): 143-154. DOI: 10.16031/j.cnki.issn.1003-8035.202310028

无人机技术在超高陡边坡危岩体半自动识别中的应用

基金项目: 国家自然科学基金项目(52009038);新疆和田玉龙喀什水利枢纽工程专项科研实验(YLKS-SW-2022-016);爆破工程湖北省重点实验室开放基金(BL2021-21)
详细信息
    作者简介:

    程雨柯(1999—),男,湖北仙桃人,土木水利专业,硕士研究生,主要从事岩质边坡危险特征地质勘察研究。E-mail:cyk173628720392022@163.com

    通讯作者:

    陈 娜(1989—),女,博士,副教授,硕士生导师,主要从事边坡安全防控、土木建筑的智能监测与检测、三维模型重构等智能土木方向的研究。E-mail:cn_research@hbut.edu.cn

  • 中图分类号: P642.22

Application UAV technology semi-automatic identification dangerous rock masses on ultra-high steep slopes

  • 摘要:

    在新疆山区开展危岩体勘察时,由于工程区存在复杂且陡峭的山体,传统人工勘察危岩体的方案往往受限。为了有效地提高危岩体调查的效率与自动化程度,本研究提出了一种基于无人机的高陡边坡危岩体半自动勘察技术。将无人机贴近摄影测量技术与精确的仿地飞行路线规划相结合,获取超高边坡精确三维点云模型;应用CloudCompare软件点云剖分工具结合危岩体突出于边坡表面的形态特征对异型滑移式块体进行语义分割;并通过分析异型滑移式块体的三维特征,实现对危岩体的定性分析。将上述理论方法应用于玉龙喀什水利工程左岸超高边坡坝址,在试验区提取出了4块危岩体。所有危岩体稳定性系数(K)均低于0.9,平均体积均在2000 m3左右,最大高差在7~11 m。危岩体的空间位置分布和三维特征与现场人工勘测的基本一致。试验表明,结合危岩体特征的高精度边坡点云模型能有效识别危岩体,提高调查效率并解决人工数据模糊的问题,对高陡边坡的危岩体评估具有实际应用价值。

    Abstract:

    In the mountainous regions of Xinjiang, traditional manual survey methods for dangerous rock masses are often restricted by the complex and steep terrain. To improve the efficiency and automation of dangerous rock masses surveys, this study proposes a semi-automatic technique using unmanned aerial vehicle (UAV) for high and steep slopes. This methodology integrates close-range photogrammetry with precise terrain-following flight path planning to generate accurate 3D point cloud models of ultra-high steep slopes. Considering the distinctive shapes of dangerous rock masses protruding from the slope surfaces, this research leveraged CloudCompare software's point cloud segmentation tool to perform semantic segmentation of these profiled blocks. Furthermore, a qualitative assessment of dangerous rock masses is achieved through an analysis of their three-dimensional features. This methodology was applied to the ultra-high slope dam site on the left bank of the Yulong Kashi Hydropower Project. In the test area, four dangerous rock masses were identified (all with stability coefficients lower than 0.9, average around 2000 m³ in volume, with height differences ranging from 7-11m), aligning closely with manual field surveys. The research shows that high-precision slope point cloud models, integrated with rock body characteristics, can effectively detect dangerous rock masses, enhance survey efficiency, and mitigate the inaccuracies associated with manual data collection. This approach holds significant practical value for assessing dangerous rock masses on ultra-high steep slopes.

  • 矿产开采诱发的地面塌陷现象十分普遍,加强对矿区地面塌陷研究已成为矿区可持续发展的重要课题之一。矿区地面塌陷与区域地质背景、矿床特征、开采方式和深度、采空区处置措施、水文地质条件等密切相关[1-2]。应城石膏矿位于湖北省云梦应城盆地的西北缘,面积约30 km2,距今已有近400年开采历史。1949年以前多为老窿开采,1960—1970年,老窿塌陷发育最多,2013—2016年,采空塌陷发育最多,早期的老窿型开采和后期的规模化开采相续形成了应城矿区地面塌陷。矿区内多处地面塌陷,表现为陷坑和地面不均匀沉降,造成道路和管线破坏、房屋开裂、农田毁坏等,对当地居民生产生活、道路和管道基础设施安全运营等造成了较大的影响。针对膏盐矿区地面塌陷,何伟等[3]根据采动岩层内冒落带、裂隙带和弯曲带的“三带”理论,结合实测资料,建立数值模型,对地下开采诱发的地表变形进行了分析。刘硕等[4] 基于Hoek-Brown 强度准则,建立数值仿真模型,结合山东肥城某石膏矿工程实践,评价了硬石膏采房群的整体稳定性。夏开宗等[5]针对采用房柱法开采石膏矿体,将石膏矿柱简化为满足西原模型的黏弹塑性体流变模型,建立了石膏矿矿柱−护顶层支撑体系的流变力学体模型,认为矿柱的塑性大变形流变特性对采空区的失稳起着至关重要的作用。陈乐求等[6]针对矿柱法开采石膏矿体,开展了石膏矿采空区充填加固技术的试验研究。刘轩廷等[7]针对充填开采法矿区,在考虑了充填体对间柱侧压作用的基础上,建立了顶板−间柱支撑体系的力学模型,探究了充填体作用下支撑体系的破坏机制。魏军才[8] 对邵东县城石膏矿老采空区地面变形的成因进行了分析,认为顶板岩性、地质构造是地面变形的基础条件,不规范开采是导致地面变形的主要诱发因素,地面不断加载及地下水动力作用加剧了地面变形的产生。郑怀昌等[9] 通过对石膏矿采空区顶板大面积冒落情况的调查,发现矿区水文地质和工程地质对顶板的冒落有很大影响,冒落也多集中于丰雨季,认为隔离矿柱对控制顶板大面积冒落及向相邻采空区扩展作用重大。章求才等[10]针对衡山石膏矿经过多年开采,于2009 年发生了大面积地面塌陷,分析了顶板破断机理及其影响因素。郑怀昌等[11]结合岩体力学的相关理论和数值模拟技术,认为石膏矿柱流变特性使其强度变低,采区扩大,石膏矿柱应力增大,诱发了石膏矿采场顶板冒落及大规模采空区顶板冒落。张向阳[12] 基于 Kachanov 蠕变损伤理论对采空区顶板的蠕变损伤过程进行了解析分析,采空区顶板的蠕变损伤断裂经历断裂孕育和裂隙扩展两个阶段。贺桂成等[13]采用FLAC3D对衡山县石膏矿闭坑前后空区引发的地面塌陷机理进行了分析,认为闭坑后矿柱不足以支承上覆围岩压力而引起采空区顶板垮落,形成垮落拱,最终在地表形成“漏斗型”塌陷区。Castellanza等[14] 针对废弃矿山遗留矿柱会受到风化作用的特性,根据膏岩试验数据拟合结果,建立风化模型对矿柱失稳时间预测。

    上述工作为膏盐矿区地面塌陷地质灾害研究奠定了较好的基础,然而,仍然存在有不足之处:对诱发石膏矿地面塌陷地质灾害成因机制的分析还存在不足,尤其是老窿对地面塌陷地质灾害影响的成因机制分析成果较少,由于不同区域的石膏矿,受膏组成矿特征、开采历史、开采方式等影响,地面塌陷地质灾害特征和成因机制具有明显的差异性,还需要结合实际情况进一步开展研究。

    为此,针对应城石膏矿区开展野外补充调查、工程地质测绘,进一步掌握矿区地质灾害的实际情况,采取内外动力多因子关联分析法和地质分析法,基于采动岩层内冒落带、裂隙带和弯曲带的“三带”理论,分析地面塌陷类型及发育分布规律,研究采空型地面塌陷地质灾害的主要影响因素,对老窿型和采空型地面塌陷的成因机制进行分析,对石膏矿风险管理和安全评估、监测预警体系构建具有一定的参考意义。

    应城市地处鄂中丘陵与江汉平原的过渡地带,整体地势为西北高,东南低,地貌类型按成因划分为河流冲积平原和丘陵两类。应城石膏矿位于湖北省云应盆地的西北缘,应城市现有10个膏矿开采区,矿区主要分布于丘陵地区,主要开采膏组为G-1—G-3、G-5和G-7—G-11,开采矿区分布如图1所示。矿区目前主要开采的含矿层位是谢家湾下含矿层和谢家湾上含矿层,谢家湾下含矿层含纤维石膏膏组五层G-1—G-5,总厚15.90~91.10 m;谢家湾上含矿层含纤维石膏膏组八层G-6—G-13,总厚23.92~181.51 m。

    图  1  矿区地形地貌及矿区分布图
    Figure  1.  The distribution map of landforms in the mining area

    应城石膏矿膏组矿体总体产状比较平缓,一般倾角为6°~8°,部分倾角近于或大于10°,与较深色的围岩接触界线较为明显,接触面较平整,极易从接触界面与围岩分开,其产状与围岩大体一致,见图2(a),局部与围岩有极微小角度斜交,见图2(b),在红色地层中,有时穿过层理插入不同围岩中,见图2(c)。

    图  2  应城市石膏矿膏组成矿特征
    Figure  2.  The characteristics of gypsum composition in Yingcheng City

    膏组矿体主要是薄层状、似层状纤维石膏矿层,厚度稳定,一般为2~25 cm,最厚可达47 cm左右,延长较远,相邻两个膏组间距8~17 m。矿体围岩以泥质粉砂岩和泥质石膏岩为主,单轴抗压强度为2.5~20.7 MPa,岩石强度较低,属软岩、极软岩。

    根据调查,应城市膏矿开采区共发育有27处地面塌陷,主要分布于城北街道办事处和杨岭镇境内(图1),规模以小—中型为主,其中小型11处,中型16处,如图3b所示。

    图  3  应城市膏矿区塌陷规模等级分布图及典型塌陷坑
    Figure  3.  The grade distribution and typical collapse pit in the mining area in Yingcheng City

    由于私人无序开采,导致矿区内留下许多废弃的井筒、巷道,截至1960年已形成大小老窿约240处,私人矿井开采面大都呈扇形展布且开采层埋深浅,一般小于100 m,由于开采深度较浅,采空区顶板变形对地面的影响较大,上覆岩体破坏后容易在地面产生塌陷坑。应城市老窿型塌陷共18处,陷坑整体呈NE向分布,与坑道展布方向基本一致,在地表多呈近圆形或不规则状,一般上大下小,上口直径2~2.5 m,大者达5 m,坑深2~3 m,大者达10 m,表现为直径大小和深度不等的陷坑单体或群体,主要发育在浅埋采空区和老窿分布范围内,如柳林村邓湾南塌陷点(图3a中CB-TX0003),为椭圆形塌陷单坑,发育在老窿周边,邹郭村黄花山水库塌陷点(图3a中CB-TX0012),为圆形单坑,地下开采深度仅35 m。

    采空型地面塌陷主要表现为地面不均匀沉陷,其变形强度较低,主要表现为地基下沉,地面房屋和道路出现开裂变形、农田毁坏等。应城市采空型塌陷共9处,其变形通常较为缓慢,但通过逐年累积,这些破坏日趋严重,部分房屋已成为危房,直接影响居民住户的居住和生产生活条件。有的裂缝贯穿墙体,严重危及房屋整体安全(图3c)。另外,区内由于不均匀地面沉降使部分农田出现倾斜,失水现象较为严重。这类变形在矿区分布十分普遍,主要出现在深埋采空区范围内或陷坑周边。

    通过调查和统计分析,应城市企业规模化开采形成采空区面积约16 km2,由于历史开采形成的老窿大约240处,应城市老窿及规模化开采采空区空间分布如图4所示,统计分析表明,下方为规模化开采采空区的老窿共128个,其中发生老窿型塌陷共18处,占比约12.5%;下方无规模化开采采空区的老窿共112个,未发生老窿型地面塌陷,说明老窿型地面塌陷与下方大范围采空区密切相关。

    图  4  地面塌陷与老窿及采空区空间分布
    Figure  4.  The spatial distribution of collapse and old holes and goaf

    通过统计分析,应城市共发育9处采空型地面塌陷,其中6处地面塌陷采深采厚比小于60,2处地面塌陷采深采厚比为60~80,1处地面塌陷采深采厚比为80~100,该处地面塌陷发育于李咀石膏矿区,虽然采深采厚比较大,推测是由于其他扰动因素的增强,或者李咀石膏矿区的开矿时间比较早,回填率较低,导致了该地面塌陷的发育(图5)。随着采深采厚比的减小,采空区地面塌陷逐渐增多,且采空型塌陷主要发育在采深采厚比小于60的区域,且采深采厚比越小,地面塌陷越容易发育,地表变形越强烈,塌陷影响越大。

    图  5  采空型地面塌陷与采深采厚比分布图
    Figure  5.  The distribution of ground collapse and mining depth to thickness ratio

    石膏矿开采工作面初次来压后,在其不断推进过程中,上覆岩体的破坏主要可分为三带:冒落带、断裂带和弯曲带。冒落带是采出空间顶板岩层在自重力作用下垮塌,堆积在采空区,形成冒落带;断裂带随着井下石膏矿采区的扩大而逐步向上发展,当到一定范围时,断裂带高度达到最大;弯曲带即弯曲下沉带,位于断裂带之上直至地表,弯曲带中的岩体移动基本上是成层的、整体性移动。

    充水型老窿塌陷下方规模化开采巷道采空区多有充填且埋深较深,下方规模化开采采空区冒裂带向上发展,但由于规模化开采采空区与老窿埋深间隔较大,冒落带、断裂带之和小于两者之间埋深间隔,规模化采空区并未与老窿连通(图6)。老窿采空后,采区内是半充填状态,或局部未充填状态,闭坑后,洞口被回填,但回填土并没有填满采区,仅填满老窿竖井,地下水通过透水的竖井回填土以及裂隙不断流入采空区,直至采空区完全饱水。采空区内的石膏层与泥岩夹层是隔水层,此时,老窿采空区内是饱水的,老窿回填后经过多年的沉积压密作用下处于相对平衡状态,老窿塌陷地表变形表现为小水坑常年积水无明显变化、周边地表无明显变形及农田无漏水现象,如图3a中CB-TX0003所示柳林村邓湾南地面塌陷点。

    图  6  充水型老窿型地面塌陷成因示意图
    Figure  6.  The genetic diagram of ground collapse with water filled old holes

    不充水型老窿塌陷下方存在规模化开采巷道采空区,且下方规模化开采采空区与老窿埋深间隔较小,冒落带、断裂带之和远大于两者之间埋深间隔,规模化采空区直接与老窿连通(图7),大都表现为老窿洞口缓慢塌陷,具有发展性。由于老窿底部与规模化采空区连通,地下水的流动带动土中的细颗粒运移,导致老窿内负压,竖井中的土体向下垮落变形,慢慢扩展到地表,表现为地表塌陷坑持续扩大。此外,由于部分膏矿企业持续对规模化开采采空区进行抽水,老窿内的积水被疏干后,连接第四系潜水层、承压含水层以及基岩裂隙水与规模化开采采空区的通道,地下水缓慢的在此通道中不断的流动,从地表通过老窿到采空区,再被抽出到地表,老窿中回填的细颗粒也不断地发生移动,导致此类塌陷,经回填后一段时间还会再次产生塌陷,如图8所示新建街社区三矿2号地面塌陷点。

    图  7  不充水型老窿型地面塌陷成因示意图
    Figure  7.  The genetic diagram of ground collapse with water unfilled old holes
    图  8  新建街社区三矿2号地面塌陷
    Figure  8.  The ground collapse No.2 in Xinjian street community

    应城石膏矿规模化开采形成的采空区,开采深度较深,这种采空区造成的塌陷一般表现为地面的不均匀沉降,弯曲带影响地表,伴随地面下沉的一些表现形式为房屋裂缝、地表裂缝变形、农田失水等现象,影响范围一般比较大,如新建街社区三矿1号地面塌陷点。

    房柱法开采导致的采空区失稳主要表现为矿柱和顶板的破坏垮落。采用房柱式采矿过程中,随着矿石不断采出和矿柱侧向应力的逐渐消减,采场上覆岩层的应力转移到矿柱上,使矿柱应力增加并产生压缩变形。当矿山企业闭坑后,由于矿柱被回采破坏导致矿柱强度降低,个别或局部矿柱破坏从而引起顶板冒落。该采场顶板及上覆岩层压应力逐渐转移到相邻矿柱,导致相邻矿柱也相继遭到破坏,顶板冒落范围进一步扩大,从而引起采空区顶板垮落并通过三带影响逐渐传递到地面,地表主要见地面沉降、隆起和建筑物开裂等,如柳林村邓湾北地面塌陷点(图9)。

    图  9  矿柱破坏型采空塌陷成因机制
    Figure  9.  The formation mechanism of goaf collapse caused by pillar failure

    长壁式充填法开采的采空区主要采用矸石充填,将开采洗选过程中产生的矸石固体废物作为骨料充填入采空区,进而改善采场围岩变形和覆岩沉降程度,有效控制地表沉陷。因此采空区充填体的充填率及其强度对上覆岩层的运动状态起着至关重要的作用,不同充填率会导致上覆岩层运移结构形态和特征都存在明显区别。当采空区充填率低时,充填体不能对顶板下沉起到支撑作用,随着采空区范围的扩大,采空区顶板逐渐垮落破碎,与采空区固体充填体相互混合形成新的支撑体,直到采空区充填体被压密实,支撑体的压缩和采空区顶板的下沉达到平衡状态。此过程中采空区顶板随开采范围的扩大发生持续破断,形成的冒落带、断裂带及弯曲带随着工作面的推进而不断向上覆岩层传递,直到这种变形发展到地面,地表主要表现为建筑物开裂、地表裂缝等,如新建街社区三矿1号地面塌陷点(图10)。

    图  10  弯曲沉降型采空塌陷成因机制
    Figure  10.  The formation mechanism of bending goaf collapse

    (1)地面塌陷主要表现两种形式:一种是塌陷坑,在地表多呈近圆形或不规则状,表现为直径大小和深度不等的陷坑单体或群体,主要发育在浅埋采空区和老窿分布范围内;另一种是地面不均匀沉陷,其变形强度较低,主要表现为地基下沉,地面房屋、道路等地物出现开裂变形、农田毁坏。

    (2)地面塌陷发育规律:老窿型地面塌陷与下方大范围采空区密切相关,当老窿下方存在规模化开采采空区且埋深较浅时,老窿与采空区连通,老窿井口附近形成地面塌陷;采空型地面塌陷的发生则受采深采厚比的影响较大,随着采深采厚比的减小,采空区地面塌陷逐渐增多,且采空型地面塌陷主要发育在采深采厚比小于60的区域。

    (3)老窿型地面塌陷包含充水型和不充水型两种类型,充水型老窿塌陷下方规模化开采巷道采空区多有充填且埋深较深,冒裂带未影响至老窿,老窿与大范围采空区不连通,塌陷后表现为小水坑常年积水且塌陷趋于稳定;不充水型老窿塌陷下方存在规模化开采巷道采空区,且由于冒裂带的影响与老窿采空区连通,塌陷后表现为地表塌陷坑持续扩大,或者人工充填后一段时间又再次塌陷,重复回填又塌陷。

    (4)采空型地面塌陷主要与矿柱破坏和充填率相关。矿柱破坏主要是矿柱在闭坑前被回采导致强度降低,局部破坏垮塌,采空区顶板垮落并通过三带影响逐渐传递到地面,主要表现为地面沉陷、隆起和建筑物开裂等;在充填率低的情况下,上覆岩土体在重力作用下,逐渐形成冒落带、断裂带以及弯曲带并随着工作面的推进而不断向上覆岩层传递,直至变形发展到地面,主要表现为建筑物开裂、地表裂缝等。

  • 图  1   试验区三维地形概览

    Figure  1.   Three-dimensional terrain overview of the test area

    图  2   人工对左岸边坡的典型危岩体的初步调查

    注:(a)为试验区三维地形;(b)为试验区左岸边坡;(c)为左岸边坡样本区;(d)为人工调查的典型危岩体。

    Figure  2.   Preliminary investigation of typical dangerous rock masses on the left bank slope by manual methods

    图  3   研究技术方法

    Figure  3.   Research technical scheme

    图  4   无人机设备

    Figure  4.   UAV equipment

    图  5   第一张正射影照片路线规划(分辨率2.5 cm)

    Figure  5.   Route planning of the first orthophoto photograph (resolution 2.5 cm)

    图  6   精细的仿地飞行路线规划

    Figure  6.   Detailed terrain-following flight path planning

    图  7   无人机三维模型建模并生成点云模型

    注:(a)为构造三角网TIN;(b)为生成模型白膜;(c)为模型纹理映射;(d)LAS点云格式转换

    Figure  7.   UAV three-dimensional modeling and point cloud model generation

    图  8   边界点云密度与密度变化率

    Figure  8.   Boundary point cloud density and density change rate

    图  9   异型滑移式块体的后壁平面提取

    Figure  9.   Extraction of the rear wall plane of profiled block

    图  10   异型滑移式块体的后壁面积与块体体积计算

    Figure  10.   Calculation for the rear wall area and block volume ofprofiled block

    图  11   异型滑移式块体的后壁倾角与最大高差计算

    Figure  11.   Calculation of the rear wall inclination angle and maximum height difference of profiled blocks

    图  12   左岸整体点云,左岸样本区区域

    Figure  12.   Overall point cloud on the left bank and sample area on the left bank

    图  13   异型滑移式块体点云模型提取

    Figure  13.   Point cloud model extraction of profiled blocks

    图  14   异型滑移式块体下采样

    Figure  14.   Downsampling of profiled block

    图  15   依据点云密度提取的异型滑移式块体后壁平面边缘点云

    Figure  15.   Edge point cloud of the rear wall plane of profiled blocks extracted based on point cloud density

    图  16   最小二乘法的后壁平面拟合

    Figure  16.   Rear wall plane fitting using the least square method

    图  17   异型滑移式块体L1的后壁平面和点云投影

    Figure  17.   Rear wall plane and point cloud projection of profiled block L1

    图  18   Alpha Shape算法分别计算异型滑移式块体的后壁面积与体积

    Figure  18.   Alpha Shape algorithm for separate calculation of the rear wall area and volume of profiled block

    表  1   单平面滑动岩体稳定性评价

    Table  1   Stability evaluation of single-plane sliding rock mass

    稳定性系数 稳定性分级
    $ K\geqslant 1.15 $ 稳定
    $ 1.05\leqslant K < 1.15 $ 基本稳定
    $ 1.00\leqslant K < 1.05 $ 欠稳定
    $ K < 1.00 $ 不稳定
    下载: 导出CSV

    表  2   水电工程危险岩体规模分级

    Table  2   Scale classification of dangerous rock mass in hydropower projects

    评价依据 小型 中型 大型 超大型
    体积/m3 $ V\leqslant 100 $ $ 100\leqslant V < 1\;000 $ $ 1000\leqslant V < 1\;0000 $ $ 10\;000\leqslant V $
    下载: 导出CSV

    表  3   异形滑移式块体特征数据统计

    Table  3   Statistical analysis of characteristic data for profiled blocks

    块体编号 后壁倾角/(°) 后壁面积/m2 块体体积/m3 最大高差/m
    L1 50.35 728.15 1712.30 7.65
    L2 45.58 835.53 2398.60 10.60
    L3 40.42 842.94 2299.47 9.48
    L4 26.23 706.89 3294.37 14.53
    L5 46.61 886.78 1690.18 7.71
    下载: 导出CSV

    表  4   异形滑移式块体物理力学参数

    Table  4   Physical and mechanical parameters of profiled block

    参数 块体重度/(kN·m−3 结构面黏聚力/MPa 结构面内摩擦角/(°)
    取值 25.8 0.100 35
    下载: 导出CSV

    表  5   危险岩体稳定系数的计算与定性

    Table  5   Calculation and qualitative characterization of stability coefficient of dangerous rock mass

    块体编号 稳定性系数 稳定性分析 块体性质
    L1 0.58 不稳定
    L2 0.69 不稳定
    L3 0.82 不稳定
    L4 1.42 稳定
    L5 0.66 不稳定
    下载: 导出CSV

    表  6   危险岩体与岩体体积评价

    Table  6   dangerous rock mass and rock massvolume evaluation

    危岩体编号 危岩体体积/m3 危岩体体积评价
    L1 1712.30 大型
    L2 2398.60 大型
    L3 2299.47 大型
    L5 1690.18 大型
    下载: 导出CSV
  • [1] 黄发明, 石雨, 欧阳慰平, 等. 基于证据权和卡方自动交互检测决策树的滑坡易发性预测[J]. 土木与环境工程学报(中英文),2022,44(5):16 − 28. [HUANG Faming, SHI Yu, OUYANG Weiping, et al. Landslide susceptibility prediction modeling based on weight of evidence and Chi-square automatic interactive detection decision tree[J]. Journal of Civil and Environmental Engineering,2022,44(5):16 − 28. (in Chinese with English abstract)]

    HUANG Faming, SHI Yu, OUYANG Weiping, et al. Landslide susceptibility prediction modeling based on weight of evidence and Chi-square automatic interactive detection decision tree[J]. Journal of Civil and Environmental Engineering, 2022, 445): 1628. (in Chinese with English abstract)

    [2] 赵树兴. 基于FLAC和极限平衡法的边坡稳定性分析[J]. 市政技术,2021,39(7):35 − 39. [ZHAO Shuxing. Slope stability analysis based on FLAC and limit equilibrium method[J]. Municipal Engineering Technology,2021,39(7):35 − 39. (in Chinese with English abstract)]

    ZHAO Shuxing. Slope stability analysis based on FLAC and limit equilibrium method[J]. Municipal Engineering Technology, 2021, 397): 3539. (in Chinese with English abstract)

    [3] 傅宏易, 刘远征. 激光测距仪在MATLAB辅助下的危岩体调查应用[J]. 科技通报,2021,37(1):34 − 38. [FU Hongyi, LIU Yuanzheng. Application of laser rangefinder in dangerous rock mass survey assisted by MATLAB[J]. Bulletin of Science and Technology,2021,37(1):34 − 38. (in Chinese with English abstract)]

    FU Hongyi, LIU Yuanzheng. Application of laser rangefinder in dangerous rock mass survey assisted by MATLAB[J]. Bulletin of Science and Technology, 2021, 371): 3438. (in Chinese with English abstract)

    [4]

    DUAN Shuqian,FENG Xiating,JIANG Quan,et al. In situ observation of failure mechanisms controlled by rock masses with weak interlayer zones in large underground cavern excavations under high geostress[J]. Rock Mechanics and Rock Engineering,2017,50(9):2465 − 2493. DOI: 10.1007/s00603-017-1249-4

    [5]

    WANG Xueliang,FRATTINI P,STEAD D,et al. Dynamic rockfall risk analysis[J]. Engineering Geology,2020,272:105622. DOI: 10.1016/j.enggeo.2020.105622

    [6] 陈文宝, 王立明, 张宏伟, 等. 基于ABAQUS的边坡稳定性分析[J]. 市政技术,2017,35(4):177 − 180. [CHEN Wenbao, WANG Liming, ZHANG Hongwei, et al. Slope stability analysis based on ABAQUS[J]. Municipal Engineering Technology,2017,35(4):177 − 180. (in Chinese with English abstract)]

    CHEN Wenbao, WANG Liming, ZHANG Hongwei, et al. Slope stability analysis based on ABAQUS[J]. Municipal Engineering Technology, 2017, 354): 177180. (in Chinese with English abstract)

    [7]

    BITENC M,KIEFFER D S,KHOSHELHAM K. Range versus surface denoising of terrestrial laser scanning data for rock discontinuity roughness estimation[J]. Rock Mechanics and Rock Engineering,2019,52(9):3103 − 3117. DOI: 10.1007/s00603-019-01755-2

    [8]

    SALVINI R,FRANCIONI M,RICCUCCI S,et al. Photogrammetry and laser scanning for analyzing slope stability and rock fall runout along the Domodossola–Iselle railway,the Italian Alps[J]. Geomorphology,2013,185:110 − 122. DOI: 10.1016/j.geomorph.2012.12.020

    [9]

    KUMHÁLOVÁ J,KUMHÁLA F,NOVÁK P,et al. Airborne laser scanning data as a source of field topographical characteristics[J]. Plant,Soil and Environment,2013,59(9):423 − 431.

    [10] 康尘云. 基于倾斜摄影的高位危岩特征获取和稳定性评价——以重庆万州观音山危岩带为例[J]. 中国地质灾害与防治学报,2022,33(5):66 − 75. [KANG Chenyun. Feature acquisition and stability evaluation of high dangerous rock mass based on oblique photography: a case study at Guanyinshan in Wanzhou, Chongqing Province[J]. The Chinese Journal of Geological Hazard and Control,2022,33(5):66 − 75. (in Chinese with English abstract)]

    KANG Chenyun. Feature acquisition and stability evaluation of high dangerous rock mass based on oblique photography: a case study at Guanyinshan in Wanzhou, Chongqing Province[J]. The Chinese Journal of Geological Hazard and Control, 2022, 335): 6675. (in Chinese with English abstract)

    [11]

    NIETHAMMER U,JAMES M R,ROTHMUND S,et al. UAV-based remote sensing of the Super-Sauze landslide:evaluation and results[J]. Engineering Geology,2012,128:2 − 11. DOI: 10.1016/j.enggeo.2011.03.012

    [12]

    RIQUELME A,TOMÁS R,CANO M,et al. Automatic mapping of discontinuity persistence on rock masses using 3D point clouds[J]. Rock Mechanics and Rock Engineering,2018,51(10):3005 − 3028. DOI: 10.1007/s00603-018-1519-9

    [13]

    ZEYBEK M,ŞANLıOĞLU İ. Point cloud filtering on UAV based point cloud[J]. Measurement,2019,133:99 − 111. DOI: 10.1016/j.measurement.2018.10.013

    [14] 赵婷婷, 高文娟, 李志林, 等. 实景三维技术在“8•8” 九寨沟地震地质灾害快速调查中的应用[J]. 中国地质灾害与防治学报,2023,34(3):93 − 99. [ZHAO Tingting, GAO Wenjuan, LI Zhilin, et al. Application of real-scene 3D technology in the rapid survey of geological disasters after the “8•8” Jiuzhaigou earthquake[J]. The Chinese Journal of Geological Hazard and Control,2023,34(3):93 − 99. (in Chinese with English abstract)]

    ZHAO Tingting, GAO Wenjuan, LI Zhilin, et al. Application of real-scene 3D technology in the rapid survey of geological disasters after the “8•8” Jiuzhaigou earthquake[J]. The Chinese Journal of Geological Hazard and Control, 2023, 343): 9399. (in Chinese with English abstract)

    [15] 梁京涛, 成余粮, 王军, 等. 基于无人机遥感技术的汶川震区典型高位泥石流动态监测——以绵竹市文家沟泥石流为例[J]. 中国地质灾害与防治学报,2013,24(3):54 − 61. [LIANG Jingtao, CHENG Yuliang, WANG Jun, et al. Monitoring of a typical high position debris flow dynamic change in Wenchuan earehquake areas with unmanned aerial vehicles case study of Wenjiagou debris flows in Mianzhu County[J]. The Chinese Journal of Geological Hazard and Control,2013,24(3):54 − 61. (in Chinese with English abstract)]

    LIANG Jingtao, CHENG Yuliang, WANG Jun, et al. Monitoring of a typical high position debris flow dynamic change in Wenchuan earehquake areas with unmanned aerial vehicles case study of Wenjiagou debris flows in Mianzhu County[J]. The Chinese Journal of Geological Hazard and Control, 2013, 243): 5461. (in Chinese with English abstract)

    [16] 黄发明, 陈佳武, 唐志鹏, 等. 不同空间分辨率和训练测试集比例下的滑坡易发性预测不确定性[J]. 岩石力学与工程学报,2021,40(6):1155 − 1169. [HUANG Faming, CHEN Jiawu, TANG Zhipeng, et al. Uncertainties of landslide susceptibility prediction due to different spatial resolutions and different proportions of training and testing datasets[J]. Chinese Journal of Rock Mechanics and Engineering,2021,40(6):1155 − 1169. (in Chinese with English abstract)]

    HUANG Faming, CHEN Jiawu, TANG Zhipeng, et al. Uncertainties of landslide susceptibility prediction due to different spatial resolutions and different proportions of training and testing datasets[J]. Chinese Journal of Rock Mechanics and Engineering, 2021, 406): 11551169. (in Chinese with English abstract)

    [17]

    NICHOLSON L,MERTES J. Thickness estimation of supraglacial debris above ice cliff exposures using a high-resolution digital surface model derived from terrestrial photography[J]. Journal of Glaciology,2017,63(242):989 − 998. DOI: 10.1017/jog.2017.68

    [18] 王明辉, 曹熙平, 谯立家. 危岩体精细调查与崩塌过程三维场景模拟——以西南某水电站高边坡为例[J]. 中国地质灾害与防治学报,2023,34(6):86 − 96. [WANG Minghui, CAO Xiping, QIAO Lijia. Comprehensive analysis of hazardous rock mass and simulation of potential rockfall processes using 3D terrain model: a case study of the high cut slope near damsite of a hydropower station in Southern China[J]. The Chinese Journal of Geological Hazard and Control,2023,34(6):86 − 96. (in Chinese with English abstract)]

    WANG Minghui, CAO Xiping, QIAO Lijia. Comprehensive analysis of hazardous rock mass and simulation of potential rockfall processes using 3D terrain model: a case study of the high cut slope near damsite of a hydropower station in Southern China[J]. The Chinese Journal of Geological Hazard and Control, 2023, 346): 8696. (in Chinese with English abstract)

    [19] 党杰, 董吉, 何松标, 等. 机载LiDAR与地面三维激光扫描在贵州水城独家寨崩塌地质灾害风险调查中的应用[J]. 中国地质灾害与防治学报,2022,33(4):106 − 113. [DANG Jie, DONG Ji, HE Songbiao, et al. Application of airborne LiDAR and ground 3D laser scanning in geological hazard risk investigation of Dujiazhai collapse in Shuicheng, Guizhou[J]. The Chinese Journal of Geological Hazard and Control,2022,33(4):106 − 113. (in Chinese with English abstract)]

    DANG Jie, DONG Ji, HE Songbiao, et al. Application of airborne LiDAR and ground 3D laser scanning in geological hazard risk investigation of Dujiazhai collapse in Shuicheng, Guizhou[J]. The Chinese Journal of Geological Hazard and Control, 2022, 334): 106113. (in Chinese with English abstract)

    [20]

    RABATEL A,DELINE P,JAILLET S,et al. Rock falls in high-alpine rock walls quantified by terrestrial lidar measurements:a case study in the Mont Blanc Area[J]. Geophysical Research Letters,2008,35(10):L10502.

    [21]

    BAR N,KOSTADINOVSKI M,TUCKER M,et al. Rapid and robust slope failure appraisal using aerial photogrammetry and 3D slope stability models[J]. International Journal of Mining Science and Technology,2020,30(5):651 − 658. DOI: 10.1016/j.ijmst.2020.05.013

    [22]

    CARA S,FIORI M,MATZUZZI C. Assessment of landscape by photogrammetry proximity uav survey technique:a case study of an abandoned mine site in the Furtei Area (Sardinia-Italy)[J]. 2013.

    [23]

    HAVAEJ M,COGGAN J,STEAD D,et al. A combined remote sensing–numerical modelling approach to the stability analysis of delabole slate quarry,cornwall,UK[J]. Rock Mechanics and Rock Engineering,2016,49(4):1227 − 1245. DOI: 10.1007/s00603-015-0805-z

    [24] 杜源, 王纯, 张勤, 等. 顾及黄土滑坡灾害状态特征的实时GNSS滤波算法[J]. 武汉大学学报(信息科学版),2023,48(7):1216 − 1222. [DU Yuan, WANG Chun, ZHANG Qin, et al. Real-time GNSS filtering algorithm considering state characteristics of loess landslide hazards[J]. Geomatics and Information Science of Wuhan University,2023,48(7):1216 − 1222. (in Chinese with English abstract)]

    DU Yuan, WANG Chun, ZHANG Qin, et al. Real-time GNSS filtering algorithm considering state characteristics of loess landslide hazards[J]. Geomatics and Information Science of Wuhan University, 2023, 487): 12161222. (in Chinese with English abstract)

    [25]

    ALI S,LIU Dong,FU Qiang,et al. Improving the resolution of GRACE data for spatio-temporal groundwater storage assessment[J]. Remote Sensing,2021,13(17):3513. DOI: 10.3390/rs13173513

    [26]

    YANG Boxiong,ALI F,ZHOU Bo,et al. A novel approach of efficient 3D reconstruction for real scene using unmanned aerial vehicle oblique photogrammetry with five cameras[J]. Computers and Electrical Engineering,2022,99:107804. DOI: 10.1016/j.compeleceng.2022.107804

    [27]

    INAM O,QURESHI M,LARAIB Z,et al. GPU accelerated Cartesian GRAPPA reconstruction using CUDA[J]. Journal of Magnetic Resonance,2022,337:107175. DOI: 10.1016/j.jmr.2022.107175

    [28] 黄发明, 殷坤龙, 蒋水华, 等. 基于聚类分析和支持向量机的滑坡易发性评价[J]. 岩石力学与工程学报,2018,37(1):156 − 167. [HUANG Faming, YIN Kunlong, JIANG Shuihua, et al. Landslide susceptibility assessment based on clustering analysis and support vector machine[J]. Chinese Journal of Rock Mechanics and Engineering,2018,37(1):156 − 167. (in Chinese with English abstract)]

    HUANG Faming, YIN Kunlong, JIANG Shuihua, et al. Landslide susceptibility assessment based on clustering analysis and support vector machine[J]. Chinese Journal of Rock Mechanics and Engineering, 2018, 371): 156167. (in Chinese with English abstract)

    [29] 武永彩. 基于LiDAR点云的电力线自适应密度聚类提取[J]. 工程勘察,2023,51(5):52 − 56. [WU Yongcai. Adaptive density clustering for extracting power line based on LiDAR point clouds[J]. Geotechnical Investigation & Surveying,2023,51(5):52 − 56. (in Chinese with English abstract)]

    WU Yongcai. Adaptive density clustering for extracting power line based on LiDAR point clouds[J]. Geotechnical Investigation & Surveying, 2023, 515): 5256. (in Chinese with English abstract)

    [30] 王道杰, 陈倍, 孙健辉. 机载LiDAR点云密度对DEM精度的影响[J]. 测绘通报,2022(5):140 − 144. [WANG Daojie, CHEN Bei, SUN Jianhui. Study on the effects of point density on DEM accuracy of airborne LiDAR[J]. Bulletin of Surveying and Mapping,2022(5):140 − 144. (in Chinese with English abstract)]

    WANG Daojie, CHEN Bei, SUN Jianhui. Study on the effects of point density on DEM accuracy of airborne LiDAR[J]. Bulletin of Surveying and Mapping, 20225): 140144. (in Chinese with English abstract)

    [31]

    MAYR A,RUTZINGER M,BREMER M,et al. Object-based classification of terrestrial laser scanning point clouds for landslide monitoring[J]. The Photogrammetric Record,2017,32(160):377 − 397. DOI: 10.1111/phor.12215

    [32]

    GOLDMAN R N. AREA OF PLANAR POLYGONS AND VOLUME OF POLYHEDRA[J]. Graphics Gems II,1991:170 − 171.

    [33]

    WANG Binbin,XIE Jiacheng,WANG Xuewen,et al. A new method for measuring the attitude and straightness of hydraulic support groups based on point clouds[J]. Arabian Journal for Science and Engineering,2021,46(12):11739 − 11757. DOI: 10.1007/s13369-021-05689-2

    [34]

    LATO M,KEMENY J,HARRAP R M,et al. Rock bench:establishing a common repository and standards for assessing rockmass characteristics using LiDAR and photogrammetry[J]. Computers & Geosciences,2013,50:106 − 114.

    [35]

    WANG Luqi,YIN Yueping,HUANG Bolin,et al. Damage evolution and stability analysis of the Jianchuandong Dangerous Rock Mass in the Three Gorges Reservoir Area[J]. Engineering Geology,2020,265:105439. DOI: 10.1016/j.enggeo.2019.105439

    [36]

    WU Wenlong,LIU Xiliang,GUO Jiaqi,et al. Upper limit analysis of stability of the water-resistant rock mass of a Karst tunnel face considering the seepage force[J]. Bulletin of Engineering Geology and the Environment,2021,80(7):5813 − 5830. DOI: 10.1007/s10064-021-02283-6

    [37]

    TAO Zhigang,FAN Fangzheng,YANG Xiaojie,et al. Prediction of deep rock mass quality and spatial distribution law of open-pit gold mine based on 3D geological modeling[J]. Geotechnical and Geological Engineering,2021,39(4):3221 − 3238. DOI: 10.1007/s10706-021-01690-6

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出版历程
  • 收稿日期:  2023-10-20
  • 修回日期:  2024-01-07
  • 网络出版日期:  2024-01-22
  • 刊出日期:  2024-01-31

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