WO2020151023A1 - 一种基于图像识别技术的关键块体动态搜索系统及方法 - Google Patents

一种基于图像识别技术的关键块体动态搜索系统及方法 Download PDF

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WO2020151023A1
WO2020151023A1 PCT/CN2019/074201 CN2019074201W WO2020151023A1 WO 2020151023 A1 WO2020151023 A1 WO 2020151023A1 CN 2019074201 W CN2019074201 W CN 2019074201W WO 2020151023 A1 WO2020151023 A1 WO 2020151023A1
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image
image acquisition
block
module
key block
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PCT/CN2019/074201
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English (en)
French (fr)
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王述红
朱宝强
董福瑞
贾蓬
杨天鸿
陈猛
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东北大学
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Publication of WO2020151023A1 publication Critical patent/WO2020151023A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/13—Edge detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion

Definitions

  • the invention relates to the technical field of geotechnical engineering information technology, in particular to a key block dynamic search system and method based on image recognition technology.
  • the current search for rock tunnel blocks is mainly by collecting the deterministic structural surface information of tunnel excavation faces in different surrounding rock sections, and then according to its division
  • the feature uses the Monte-Carlo simulation method to generate internal random structural planes, and the deterministic structural planes and random structural planes cut each other to form a block.
  • This method reflects the whole by part, obviously there are big shortcomings. Because there are a large number of complex structural planes inside the rock mass, if the deterministic structural planes collected are not relatively developed, the actual internal structural plane division method may be There is a large deviation from the division of random structural planes generated by the probability and statistics method.
  • the technical problem to be solved by the present invention is to provide a key block dynamic search system and method based on the image recognition technology in view of the above-mentioned shortcomings of the prior art.
  • the system can timely carry out the detection of the key blocks in the tunnel excavation process.
  • the search has the beneficial effects of simple and convenient use, high work efficiency, reliable search accuracy and strong practicability, and achieves the purpose of dynamic search for key blocks in the construction process.
  • the present invention provides a key block dynamic search system based on image recognition technology, including an image acquisition system, a computer operating system, a remote control system, and a wireless transmission system;
  • the wireless transmission system is used to connect the image acquisition system, the computer operating system and the remote control system to each other through wireless transmission;
  • the image acquisition system includes image acquisition equipment, laser rangefinders, auxiliary lighting devices, and benchmarks; the image acquisition equipment is used to acquire images and output the acquired images to the image processing module; the laser rangefinder is installed in The image acquisition equipment is used to measure the distance between the image acquisition equipment and the tunnel excavation face; the auxiliary lighting device is used to ensure that the image acquisition equipment can collect high-quality images of the tunnel face; the benchmark is used to Determine the range of images collected by the image acquisition device;
  • the computer operating system includes an image processing module, a block search module, and a key block instability dynamic simulation module;
  • the image processing module includes an image preprocessing unit, an edge detection unit, a boundary extraction unit, a boundary analysis unit, a structural plane information extraction unit, and a structural plane information analysis unit; the image preprocessing unit is used to capture the palm of the image acquisition device
  • the sub-surface image undergoes preliminary processing and transmits the processed image to the edge detection unit.
  • the preliminary processing includes binarization, de-drying, thinning and normalization; the edge detection unit is used to determine the boundary of the tunnel excavation.
  • the boundary extraction unit is used to extract the detected boundary and transmit the extracted boundary image to the boundary analysis unit;
  • the boundary analysis unit uses To analyze the extracted boundaries, remove some unnecessary boundaries and transmit them to the structural plane information extraction unit;
  • the structural plane information extraction unit is used to initially extract structural plane information and output the information to the structural plane information analysis Unit;
  • the structural plane information analysis unit is used to analyze the extracted structural plane information, extract some main deterministic structural planes, calculate the center point coordinates, disk radius, inclination, and inclination, and output the information to the block Body search module;
  • the block search module is used to store the mechanical parameters of the structural plane selected in the geological survey report and search for the movable block in the rock mass to be excavated and output the movable block information to the dynamic simulation of the instability of the key block Module, the mechanical parameters include cohesive force and internal friction angle;
  • the key block instability dynamic simulation module is used to intuitively simulate the dynamic sliding process of the movable block that is unstable, and the movable block The information and the dynamic sliding process of the instability movable block are output to the data storage module in the remote control system;
  • the remote control system includes a data storage module and an abnormal data analysis and feedback module; the data storage module is used to store the searched movable block data and the data of the movable block that is unstable; the abnormal data
  • the analysis feedback module is used to analyze the information output by the dynamic simulation module of key block instability, and feedback abnormal data to the image acquisition system through the wireless transmission system.
  • the present invention also provides a key block dynamic search method based on image recognition technology, which is implemented by the described key block dynamic search system based on image recognition technology, including the following steps:
  • Step 1 According to the geological survey report on site, select the mechanical parameters of the structural surface, including cohesion and internal friction angle, and input them into the block search module in the computer operating system in advance;
  • Step 2 Arrange image acquisition equipment, auxiliary lighting devices and benchmarking poles in the tunnel, install the laser rangefinder on the image acquisition equipment, and judge whether the distance between the image acquisition equipment and the tunnel excavation face is based on the laser rangefinder If it meets the image acquisition standard, then the image acquisition will be carried out here. Otherwise, move the image acquisition equipment until it meets the image acquisition standard; place the auxiliary lighting device and the benchmark somewhere selected by the staff; the image acquisition standard is based on the work Distance requirements and clarity requirements specified by personnel;
  • Step 3 After setting the position of the image acquisition device, adjust it to the level, the shooting direction is perpendicular to the palm surface, collect the image and transmit it to the computer operating system by the wireless transmission system, extract the structure surface information, and compare the extracted structure Analysis of surface information and block search;
  • Step 4 Dynamically simulate the movable block that is instability, and store the searched movable block and the dynamic sliding process data of the movable block that is instability through the wireless transmission system, so as to further analyze the abnormality. The data is analyzed and fed back. If the abnormal data is not within the allowable error range, then go to step 3 to re-acquire the image and analyze. If the abnormal data is within the allowable error range, take reinforcement measures for the movable block that is unstable Go to step 5;
  • Step 5 Determine whether the distance between the image acquisition device and the palm surface meets the shooting standard by the laser rangefinder. If it does not, then go to step 2 to readjust the device position and perform image acquisition and analysis. If it does, continue. construction.
  • the image acquisition device adopts a digital camera or a smart phone with a camera function.
  • the laser rangefinder adopts a handheld laser rangefinder or a telescope laser rangefinder.
  • the auxiliary lighting device adopts an iodine tungsten lamp or an incandescent lamp.
  • the benchmark adopts wooden sticks with appropriate diameter and length determined by the excavation section.
  • the image processing module uses debugged image post-processing software.
  • the block search module and the key block instability dynamic simulation module adopt block search software developed based on the block theory.
  • the remote control system uses a computer installed with data statistical analysis software.
  • the wireless transmission system uses local area network or WIFI or mobile communication signals.
  • the present invention provides a key block dynamic search system and method based on image recognition technology.
  • the image acquisition system used in this method can collect the tunnel excavation in time.
  • Surface image information can be used to judge the secondary structure surface formed by tunnel excavation in time, and search for key blocks in time, and it is connected to the computer operating system and remote control system through the wireless transmission system, which has high work efficiency.
  • the advantage of fast command transmission; among them, the image acquisition device can be a digital camera and a mobile phone with a camera function, which is more convenient to install and use.
  • the computer operating system works by installing software with image processing function and software with block search function, and the accuracy of block search is relatively reliable.
  • the invention has the advantages of simple and convenient use, high work efficiency, reliable search accuracy, and strong practicability; it can achieve the purpose of dynamic search for key blocks, can guide construction in time, and has strong practicability.
  • FIG. 1 is a schematic diagram of a key block dynamic search system based on image recognition technology provided by an embodiment of the present invention
  • Fig. 2 is a schematic diagram of a dynamic search process for key blocks based on image recognition technology according to an embodiment of the present invention.
  • the method of this embodiment is as follows.
  • the invention provides a key block dynamic search system based on image recognition technology, including an image acquisition system, a computer operating system, a remote control system, and a wireless transmission system;
  • the wireless transmission system is used to connect the image acquisition system, the computer operating system and the remote control system to each other through wireless transmission;
  • the image acquisition system includes image acquisition equipment, laser rangefinders, auxiliary lighting devices, and benchmarks; the image acquisition equipment is used to acquire images and output the acquired images to the image processing module; the laser rangefinder is installed in The image acquisition equipment is used to measure the distance between the image acquisition equipment and the tunnel excavation face; the auxiliary lighting device is used to ensure that the image acquisition equipment can collect high-quality images of the tunnel face; the benchmark is used to Determine the range of images collected by the image acquisition device;
  • the image acquisition system can collect the image information of the face of the tunnel after the tunnel excavation in time, judge the secondary structural plane formed by the tunnel excavation in time, and search for the key blocks in time, that is, the rock mass
  • the search of movable blocks has high work efficiency.
  • the computer operating system includes an image processing module, a block search module, and a key block instability dynamic simulation module;
  • the image processing module includes an image preprocessing unit, an edge detection unit, a boundary extraction unit, a boundary analysis unit, a structural plane information extraction unit, and a structural plane information analysis unit; the image preprocessing unit is used to capture the palm of the image acquisition device
  • the sub-surface image undergoes preliminary processing and transmits the processed image to the edge detection unit.
  • the preliminary processing includes binarization, de-drying, thinning and normalization; the edge detection unit is used to determine the boundary of the tunnel excavation.
  • the boundary extraction unit is used to extract the detected boundary and transmit the extracted boundary image to the boundary analysis unit;
  • the boundary analysis unit uses To analyze the extracted boundaries, remove some unnecessary boundaries and transmit them to the structural plane information extraction unit;
  • the structural plane information extraction unit is used to initially extract structural plane information and output the information to the structural plane information analysis Unit;
  • the structural plane information analysis unit is used to analyze the extracted structural plane information, extract some main deterministic structural planes, calculate the center point coordinates, disk radius, inclination, and inclination, and output the information to the block Body search module;
  • the block search module is used to store the mechanical parameters of the structural plane selected in the geological survey report and search for the movable block in the rock mass to be excavated and output the movable block information to the dynamic simulation of the instability of the key block Module, the mechanical parameters include cohesive force and internal friction angle;
  • the key block instability dynamic simulation module is used to intuitively simulate the dynamic sliding process of the movable block that is unstable, and the movable block The information and the dynamic sliding process of the instability movable block are output to the data storage module in the remote control system;
  • the remote control system includes a data storage module and an abnormal data analysis and feedback module; the data storage module is used to store the searched movable block data and the data of the movable block that is unstable; the abnormal data
  • the analysis feedback module is used to analyze the information output by the dynamic simulation module of key block instability, and feedback abnormal data to the image acquisition system through the wireless transmission system.
  • the image acquisition device adopts a digital camera or a smart phone with a camera function.
  • the laser rangefinder adopts a handheld laser rangefinder or a telescope laser rangefinder.
  • the auxiliary lighting device adopts an iodine tungsten lamp or an incandescent lamp.
  • the benchmark adopts wooden sticks with appropriate diameter and length determined by the excavation section.
  • the image processing module uses debugged image post-processing software.
  • the block search module and the key block instability dynamic simulation module adopt block search software developed based on the block theory.
  • the remote control system uses a computer installed with data statistical analysis software.
  • the wireless transmission system adopts local area network or WIFI or mobile communication signal
  • the image acquisition equipment uses a digital camera;
  • the laser rangefinder uses a handheld laser rangefinder;
  • the auxiliary lighting device uses an iodine tungsten lamp;
  • the image processing module uses the adjusted ShapeMetriX3D three-dimensional evaluation software;
  • the wireless transmission system uses a local area network ;
  • the block search module uses GeoSMA-3D software;
  • the present invention also provides a key block dynamic search method based on image recognition technology, which is implemented by the described key block dynamic search system based on image recognition technology, as shown in FIG. 2, including the following steps :
  • Step 1 According to the geological survey report on site, select the mechanical parameters of the structural surface, including cohesion and internal friction angle, and input them into the block search module in the computer operating system in advance;
  • Step 2 Arrange image acquisition equipment, auxiliary lighting devices and benchmarking poles in the tunnel, install the laser rangefinder on the image acquisition equipment, and judge whether the distance between the image acquisition equipment and the tunnel excavation face is based on the laser rangefinder If it meets the image acquisition standard, then the image acquisition will be carried out here. Otherwise, move the image acquisition equipment until it meets the image acquisition standard; place the auxiliary lighting device and the benchmark somewhere selected by the staff; the image acquisition standard is based on the work Distance requirements and clarity requirements specified by personnel;
  • Step 3 After setting the position of the image acquisition device, adjust it to the level, the shooting direction is perpendicular to the palm surface, collect the image and transmit it to the computer operating system by the wireless transmission system, extract the structure surface information, and compare the extracted structure Analysis of surface information and block search;
  • Step 4 Dynamically simulate the movable block that is instability, and store the searched movable block and the dynamic sliding process data of the movable block that is instability through the wireless transmission system, so as to further analyze the abnormality. The data is analyzed and fed back. If the abnormal data is not within the allowable error range, then go to step 3 to re-acquire the image and analyze. If the abnormal data is within the allowable error range, take reinforcement measures for the movable block that is unstable Go to step 5;
  • Step 5 Determine whether the distance between the image acquisition device and the palm surface meets the shooting standard by the laser rangefinder. If it does not, then go to step 2 to readjust the device position and perform image acquisition and analysis. If it does, continue. construction.

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Abstract

一种基于图像识别技术的关键块体动态搜索系统及方法，涉及岩土工程信息化技术领域。所述系统包括图像采集系统、计算机操作系统、远程控制系统、无线传输系统。所述图像采集系统包括：图像采集设备、激光测距仪、辅助照明装置、标杆，激光测距仪安装在图像采集设备上；辅助照明装置和标杆放置在距掌子面较近的位置。所述计算机操作系统包括：图像处理模块、块体搜索模块、关键块体失稳动态模拟模块，对采集的图像处理后搜索可移动块体；所述远程控制系统包括数据存储模块和异常数据处理模块，用于存储数据并反馈信息。无线传输系统用于上述系统之间的连接。所述系统使用简单方便、工作效率高、实用性强。

Description

一种基于图像识别技术的关键块体动态搜索系统及方法 技术领域
本发明涉及岩土工程信息化技术领域，尤其涉及一种基于图像识别技术的关键块体动态搜索系统及方法。
 背景技术
在自然条件下，岩体由结构面切割形成块体，这些块体有些是稳定的，有些是不稳定的，对于岩质隧道，其施工过程中发生的坍塌等灾害往往是由于关键块体的失稳所造成的，对这些块体进行搜索，从而判断可能发生失稳的关键块体具有非常重要的工程意义。
随着图像识别技术和计算机技术的不断发展和完善，目前对岩质隧道块体的搜索还主要是通过采集不同围岩段隧道开挖掌子面的确定性结构面信息，然后依据其分部特征采用Monte-Carlo模拟方法生成内部随机性结构面，确定性结构面与随机性结构面之间相互切割形成块体。这种方法通过部分来反映整体，显然存在很大的缺点，由于岩体内部存在大量复杂的结构面，若采集到的确定性结构面不是较为发育，则其内部实际的结构面分部方式可能与采用概率统计方法生成的随机性结构面的分部存在较大偏差，这时仅仅根据概率统计方法生成内部随机性结构面来判断岩体内部块体的分部存在一定的不足。另外，由于隧道开挖可能还会形成次生结构面，目前对次生结构面的判断主要是通过边开挖边进行钻孔岩芯取样，这种方法显然工作效率较低。
 技术问题
本发明要解决的技术问题是针对上述现有技术的不足，提供一种基于图像识别技术的关键块体动态搜索系统及方法，该系统可及时的对隧道开挖过程中存在的关键块体进行搜索，具有使用简单方便、工作效率高、搜索准确性可靠、实用性强等有益效果，达到了对施工过程中关键块体的动态搜索目的。
 技术解决方案
为解决上述技术问题，本发明所采取的技术方案是：
一方面，本发明提供一种基于图像识别技术的关键块体动态搜索系统，包括图像采集系统、计算机操作系统、远程控制系统、无线传输系统；
所述无线传输系统用于将图像采集系统、计算机操作系统和远程控制系统之间通过无线传输相互连接；
所述图像采集系统包括图像采集设备、激光测距仪、辅助照明装置、标杆；所述图像采集设备用于采集图像并将采集到的图像输出至图像处理模块；所述激光测距仪安装在图像采集设备上，用于测量图像采集设备与隧道开挖掌子面之间的距离；所述辅助照明装置用于保证图像采集设备可以采集到高质量的掌子面图像；所述标杆用于判断图像采集设备采集的图像范围；
所述计算机操作系统包括图像处理模块、块体搜索模块、关键块体失稳动态模拟模块；
所述图像处理模块包括图像预处理单元，边缘检测单元，边界提取单元，边界分析单元，结构面信息提取单元，结构面信息分析单元；所述图像预处理单元用于将图像采集设备采集的掌子面图像进行初步处理并将处理后的图像传输至边缘检测单元，所述初步处理包括二值化、去燥、细化和归一化；所述边缘检测单元用于根据隧道开挖的边界和标杆的位置检测图像的边界并将图像传输至边界提取单元；所述边界提取单元用于将检测到的边界提取出来并将提取出的边界图像传输至边界分析单元；所述边界分析单元用于对提取出的边界进行分析，剔除掉一些不必要的边界并传输至结构面信息提取单元；所述结构面信息提取单元用于初步提取结构面的信息并将该信息输出至结构面信息分析单元；所述结构面信息分析单元用于对提取出的结构面信息进行分析，提取出一些主要的确定性结构面，计算其中心点坐标、圆盘半径、倾向、倾角，将信息输出至块体搜索模块；
所述块体搜索模块用于储存地质调查报告中选取的结构面的力学参数和搜索即将开挖的岩体中的可移动块体并将可移动块体信息输出至关键块体失稳动态模拟模块，所述力学参数包括粘聚力和内摩擦角；所述关键块体失稳动态模拟模块用于直观的模拟发生失稳的可移动块体的动态滑落过程，并将可移动块体块的信息以及发生失稳的可移动块体的动态滑落过程输出至远程控制系统中的数据存储模块；
所述远程控制系统包括数据存储模块和异常数据分析反馈模块；所述数据存储模块用于对搜索到的可移动块体数据和发生失稳的可移动块体的数据进行存储；所述异常数据分析反馈模块用于对关键块体失稳动态模拟模块输出的信息进行分析，将出现异常的数据通过无线传输系统反馈给图像采集系统。
另一方面，本发明还提供一种基于图像识别技术的关键块体动态搜索方法，通过所述的一种基于图像识别技术的关键块体动态搜索系统实现，包括以下步骤：
步骤1：根据现场的地质调查报告选取结构面的力学参数，包括粘聚力和内摩擦角，并且提前输入计算机操作系统中的块体搜索模块中；
步骤2：在隧道内布置图像采集设备、辅助照明装置和标杆，将激光测距仪安装在图像采集设备上，根据激光测距仪判断图像采集设备与隧道开挖掌子面之间的距离是否符合图像采集标准，是则在此处进行图像采集，否则移动图像采集设备，直至符合图像采集标准；将辅助照明装置和标杆放置在工作人员选定的某处；所述图像采集标准是根据工作人员规定的距离要求和清晰度要求；
步骤3：图像采集设备设定好位置后将其调整至水平，拍摄方向为垂直于掌子面，采集图像并由无线传输系统传输至计算机操作系统中，提取结构面信息，对提取出的结构面信息进行分析，进行块体搜索；
步骤4：对发生失稳的可移动块体进行动态模拟，并将搜索到的可移动块体及发生失稳的可移动块体的动态滑落过程数据通过无线传输系统进行存储，以便进一步对异常数据进行分析反馈，若异常数据不在允许的误差范围内，则转至步骤3重新采集图像并分析，若异常数据在允许的误差范围内，则对发生失稳的可移动块体进行加固措施，执行步骤5；
步骤5：由激光测距仪判断图像采集设备与掌子面之间的距离是否符合拍摄标准，若不符合则转至步骤2重新调整设备位置并进行图像采集和分析，若符合，则继续进行施工。
所述图像采集设备采用数码相机或带有拍照功能的智能手机。
所述激光测距仪采用手持式激光测距仪或望远镜式激光测距仪。
所述辅助照明装置采用碘钨灯或白炽灯。
所述标杆采用由开挖断面确定的直径和长度适宜的木棍。
所述图像处理模块采用经调试过的图像后处理软件。
所述块体搜索模块及关键块体失稳动态模拟模块采用基于块体理论开发的块体搜索软件。
所述远程控制系统采用安装了数据统计分析软件的计算机。
所述无线传输系统采用局域网络或WIFI或移动通讯信号。
 有益效果
采用上述技术方案所产生的有益效果在于：本发明提供的一种基于图像识别技术的关键块体动态搜索系统及方法，本方法中采用的图像采集系统可以及时的采集隧道开挖后的掌子面图像信息，可及时的对隧道开挖形成的次生结构面进行判断，并及时进行关键块体搜索，且其通过无线传输系统与计算机操作系统和远程控制系统相连接，具有工作效率高，指令传达快的优点；其中，图像采集设备可以是数码相机和带有拍照功能的手机，安装使用均较方便。计算机操作系统通过安装具有图像处理功能的软件和具有块体搜索功能的软件进行工作，其块体搜索的准确性较为可靠。本发明具有使用简单方便、工作效率高、搜索准确性可靠、实用性强；可达到对关键块体进行动态搜索的目的，可以及时的指导施工，具有较强的实用性。
 附图说明
图1为本发明实施例提供的基于图像识别技术的关键块体动态搜索系统示意图；
图2为本发明实施例提供的基于图像识别技术的关键块体动态搜索流程示意图。
 本发明的实施方式
下面结合附图和实施例，对本发明的具体实施方式作进一步详细描述。以下实施例用于说明本发明，但不用来限制本发明的范围。
如图1所示，本实施例的方法如下所述。
本发明提供一种基于图像识别技术的关键块体动态搜索系统，包括图像采集系统、计算机操作系统、远程控制系统、无线传输系统；
所述无线传输系统用于将图像采集系统、计算机操作系统和远程控制系统之间通过无线传输相互连接；
所述图像采集系统包括图像采集设备、激光测距仪、辅助照明装置、标杆；所述图像采集设备用于采集图像并将采集到的图像输出至图像处理模块；所述激光测距仪安装在图像采集设备上，用于测量图像采集设备与隧道开挖掌子面之间的距离；所述辅助照明装置用于保证图像采集设备可以采集到高质量的掌子面图像；所述标杆用于判断图像采集设备采集的图像范围；
所述图像采集系统可以及时的采集隧道开挖后的掌子面图像信息，可及时的对隧道开挖形成的次生结构面进行判断，并及时进行关键块体的搜索，即对岩体中的可移动块体的搜索，工作效率高。
所述计算机操作系统包括图像处理模块、块体搜索模块、关键块体失稳动态模拟模块；
所述图像处理模块包括图像预处理单元，边缘检测单元，边界提取单元，边界分析单元，结构面信息提取单元，结构面信息分析单元；所述图像预处理单元用于将图像采集设备采集的掌子面图像进行初步处理并将处理后的图像传输至边缘检测单元，所述初步处理包括二值化、去燥、细化和归一化；所述边缘检测单元用于根据隧道开挖的边界和标杆的位置检测图像的边界并将图像传输至边界提取单元；所述边界提取单元用于将检测到的边界提取出来并将提取出的边界图像传输至边界分析单元；所述边界分析单元用于对提取出的边界进行分析，剔除掉一些不必要的边界并传输至结构面信息提取单元；所述结构面信息提取单元用于初步提取结构面的信息并将该信息输出至结构面信息分析单元；所述结构面信息分析单元用于对提取出的结构面信息进行分析，提取出一些主要的确定性结构面，计算其中心点坐标、圆盘半径、倾向、倾角，将信息输出至块体搜索模块；
所述块体搜索模块用于储存地质调查报告中选取的结构面的力学参数和搜索即将开挖的岩体中的可移动块体并将可移动块体信息输出至关键块体失稳动态模拟模块，所述力学参数包括粘聚力和内摩擦角；所述关键块体失稳动态模拟模块用于直观的模拟发生失稳的可移动块体的动态滑落过程，并将可移动块体块的信息以及发生失稳的可移动块体的动态滑落过程输出至远程控制系统中的数据存储模块；
所述远程控制系统包括数据存储模块和异常数据分析反馈模块；所述数据存储模块用于对搜索到的可移动块体数据和发生失稳的可移动块体的数据进行存储；所述异常数据分析反馈模块用于对关键块体失稳动态模拟模块输出的信息进行分析，将出现异常的数据通过无线传输系统反馈给图像采集系统。
所述图像采集设备采用数码相机或带有拍照功能的智能手机。
所述激光测距仪采用手持式激光测距仪或望远镜式激光测距仪。
所述辅助照明装置采用碘钨灯或白炽灯。
所述标杆采用由开挖断面确定的直径和长度适宜的木棍。
所述图像处理模块采用经调试过的图像后处理软件。
所述块体搜索模块及关键块体失稳动态模拟模块采用基于块体理论开发的块体搜索软件。
所述远程控制系统采用安装了数据统计分析软件的计算机。
所述无线传输系统采用局域网络或WIFI或移动通讯信号
本实施例中图像采集设备采用数码相机；激光测距仪采用手持式激光测距仪；辅助照明装置采用碘钨灯；图像处理模块采用经调试过的ShapeMetriX3D三维评价软件；无线传输系统采用局域网络；块体搜索模块采用GeoSMA-3D软件；
另一方面，本发明还提供一种基于图像识别技术的关键块体动态搜索方法，通过所述的一种基于图像识别技术的关键块体动态搜索系统实现，如图2所示，包括以下步骤：
步骤1：根据现场的地质调查报告选取结构面的力学参数，包括粘聚力和内摩擦角，并且提前输入计算机操作系统中的块体搜索模块中；
步骤2：在隧道内布置图像采集设备、辅助照明装置和标杆，将激光测距仪安装在图像采集设备上，根据激光测距仪判断图像采集设备与隧道开挖掌子面之间的距离是否符合图像采集标准，是则在此处进行图像采集，否则移动图像采集设备，直至符合图像采集标准；将辅助照明装置和标杆放置在工作人员选定的某处；所述图像采集标准是根据工作人员规定的距离要求和清晰度要求；
步骤3：图像采集设备设定好位置后将其调整至水平，拍摄方向为垂直于掌子面，采集图像并由无线传输系统传输至计算机操作系统中，提取结构面信息，对提取出的结构面信息进行分析，进行块体搜索；
步骤4：对发生失稳的可移动块体进行动态模拟，并将搜索到的可移动块体及发生失稳的可移动块体的动态滑落过程数据通过无线传输系统进行存储，以便进一步对异常数据进行分析反馈，若异常数据不在允许的误差范围内，则转至步骤3重新采集图像并分析，若异常数据在允许的误差范围内，则对发生失稳的可移动块体进行加固措施，执行步骤5；
步骤5：由激光测距仪判断图像采集设备与掌子面之间的距离是否符合拍摄标准，若不符合则转至步骤2重新调整设备位置并进行图像采集和分析，若符合，则继续进行施工。
最后应说明的是：以上实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明权利要求所限定的范围。

Claims (10)

  1. 一种基于图像识别技术的关键块体动态搜索系统，其特征在于：包括图像采集系统、计算机操作系统、远程控制系统、无线传输系统；
    所述无线传输系统用于将图像采集系统、计算机操作系统和远程控制系统之间通过无线传输相互连接；
    所述图像采集系统包括图像采集设备、激光测距仪、辅助照明装置、标杆；所述图像采集设备用于采集图像并将采集到的图像输出至图像处理模块；所述激光测距仪安装在图像采集设备上，用于测量图像采集设备与隧道开挖掌子面之间的距离；所述辅助照明装置用于保证图像采集设备可以采集到高质量的掌子面图像；所述标杆用于判断图像采集设备采集的图像范围；
    所述计算机操作系统包括图像处理模块、块体搜索模块、关键块体失稳动态模拟模块；
    所述图像处理模块包括图像预处理单元，边缘检测单元，边界提取单元，边界分析单元，结构面信息提取单元，结构面信息分析单元；所述图像预处理单元用于将图像采集设备采集的掌子面图像进行初步处理并将处理后的图像传输至边缘检测单元，所述初步处理包括二值化、去燥、细化和归一化；所述边缘检测单元用于根据隧道开挖的边界和标杆的位置检测图像的边界并将图像传输至边界提取单元；所述边界提取单元用于将检测到的边界提取出来并将提取出的边界图像传输至边界分析单元；所述边界分析单元用于对提取出的边界进行分析，剔除掉一些不必要的边界并传输至结构面信息提取单元；所述结构面信息提取单元用于初步提取结构面的信息并将该信息输出至结构面信息分析单元；所述结构面信息分析单元用于对提取出的结构面信息进行分析，提取出一些主要的确定性结构面，计算其中心点坐标、圆盘半径、倾向、倾角，将信息输出至块体搜索模块；
    所述块体搜索模块用于储存地质调查报告中选取的结构面的力学参数和搜索即将开挖的岩体中的可移动块体并将可移动块体信息输出至关键块体失稳动态模拟模块，所述力学参数包括粘聚力和内摩擦角；所述关键块体失稳动态模拟模块用于直观的模拟发生失稳的可移动块体的动态滑落过程，并将可移动块体块的信息以及发生失稳的可移动块体的动态滑落过程输出至远程控制系统中的数据存储模块；
    所述远程控制系统包括数据存储模块和异常数据分析反馈模块；所述数据存储模块用于对搜索到的可移动块体数据和发生失稳的可移动块体的数据进行存储；所述异常数据分析反馈模块用于对关键块体失稳动态模拟模块输出的信息进行分析，将出现异常的数据通过无线传输系统反馈给图像采集系统。
  2. 根据权利要求1所述的一种基于图像识别技术的关键块体动态搜索系统，其特征在于：所述图像采集设备采用数码相机或带有拍照功能的智能手机。
  3. 根据权利要求1所述的一种基于图像识别技术的关键块体动态搜索系统，其特征在于：所述激光测距仪采用手持式激光测距仪或望远镜式激光测距仪。
  4. 根据权利要求1所述的一种基于图像识别技术的关键块体动态搜索系统，其特征在于：所述辅助照明装置采用碘钨灯或白炽灯。
  5. 根据权利要求1所述的一种基于图像识别技术的关键块体动态搜索系统，其特征在于：所述标杆采用由开挖断面确定的直径和长度适宜的木棍。
  6. 根据权利要求1所述的一种基于图像识别技术的关键块体动态搜索系统，其特征在于：所述图像处理模块采用经调试过的图像后处理软件。
  7. 根据权利要求1所述的一种基于图像识别技术的关键块体动态搜索系统，其特征在于：所述块体搜索模块及关键块体失稳动态模拟模块采用基于块体理论开发的块体搜索软件。
  8. 根据权利要求1所述的一种基于图像识别技术的关键块体动态搜索系统，其特征在于：所述远程控制系统采用安装了数据统计分析软件的计算机。
  9. 根据权利要求1所述的一种基于图像识别技术的关键块体动态搜索系统，其特征在于：所述无线传输系统采用局域网络或WIFI或移动通讯信号。
  10. 一种基于图像识别技术的关键块体动态搜索方法，通过权利要求1所述的一种基于图像识别技术的关键块体动态搜索系统实现，其特征在于：包括以下步骤：
    步骤1：根据现场的地质调查报告选取结构面的力学参数，包括粘聚力和内摩擦角，并且提前输入计算机操作系统中的块体搜索模块中；
    步骤2：在隧道内布置图像采集设备、辅助照明装置和标杆，将激光测距仪安装在图像采集设备上，根据激光测距仪判断图像采集设备与隧道开挖掌子面之间的距离是否符合图像采集标准，是则在此处进行图像采集，否则移动图像采集设备，直至符合图像采集标准；将辅助照明装置和标杆放置在工作人员选定的某处；所述图像采集标准是根据工作人员规定的距离要求和清晰度要求；
    步骤3：图像采集设备设定好位置后将其调整至水平，拍摄方向为垂直于掌子面，采集图像并由无线传输系统传输至计算机操作系统中，提取结构面信息，对提取出的结构面信息进行分析，进行块体搜索；
    步骤4：对发生失稳的可移动块体进行动态模拟，并将搜索到的可移动块体及发生失稳的可移动块体的动态滑落过程数据通过无线传输系统进行存储，以便进一步对异常数据进行分析反馈，若异常数据不在允许的误差范围内，则转至步骤3重新采集图像并分析，若异常数据在允许的误差范围内，则对发生失稳的可移动块体进行加固措施，执行步骤5；
    步骤5：由激光测距仪判断图像采集设备与掌子面之间的距离是否符合拍摄标准，若不符合则转至步骤2重新调整设备位置并进行图像采集和分析，若符合，则继续进行施工。
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* Cited by examiner, † Cited by third party
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CN113781441A (zh) * 2021-09-13 2021-12-10 中铁一局集团第二工程有限公司 一种应用于节理岩体隧道开挖过程中的注浆范围优化方法
CN114565848A (zh) * 2022-02-25 2022-05-31 佛山读图科技有限公司 一种复杂场景的药液液位检测方法及系统
CN117211886A (zh) * 2023-11-07 2023-12-12 南京派光智慧感知信息技术有限公司 一种隧道掌子面多元信息一体化采集系统及其使用方法
CN117395983A (zh) * 2023-11-16 2024-01-12 深圳市创芯智汇电子科技有限公司 一种pcb板贴片自动检测方法及其装置

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CN111894054A (zh) * 2020-09-08 2020-11-06 铁科院(深圳)研究设计院有限公司 基于激光测距仪组网的基坑开挖状态监控系统和方法

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN207423114U (zh) * 2017-11-30 2018-05-29 中国地质调查局水文地质环境地质调查中心 一种滑坡多点位移智能监测装置
CN108254205A (zh) * 2017-12-15 2018-07-06 山东大学 隧道危石垮塌室内大型综合模拟试验平台及方法

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101739716B (zh) * 2009-12-04 2011-12-28 东北大学 工程岩体三维空间结构建模与关键块识别方法
CN106225770B (zh) * 2016-08-26 2018-12-25 招商局重庆交通科研设计院有限公司 隧道掌子面地质多维数字化记录识别方法及系统
CN106780284B (zh) * 2016-12-28 2023-05-02 中铁工程装备集团有限公司 隧道洞壁围岩完整性信息采集装置及评价方法
CN109211137A (zh) * 2018-09-11 2019-01-15 华东交通大学 一种快速识别隧道掌子面岩性的装置及方法

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN207423114U (zh) * 2017-11-30 2018-05-29 中国地质调查局水文地质环境地质调查中心 一种滑坡多点位移智能监测装置
CN108254205A (zh) * 2017-12-15 2018-07-06 山东大学 隧道危石垮塌室内大型综合模拟试验平台及方法

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
SA, WENQI ET AL.: "Real-Time Safety Evaluation and Early Warning of Large-Scale Underground Cavern Group during Construction Period Based on Internet of Things", CHINESE JOURNAL OF ROCK MECHANICS AND ENGINEERING, vol. 33, no. 11, 30 November 2014 (2014-11-30), ISSN: 1000-6915 *
WANG, FEILI ET AL.: "Instability Characterization Coefficient of Key Block and Evaluation of Rock Slope Stability", JOURNAL OF TRAFFIC AND TRANSPORTATION ENGINEERING, vol. 18, no. 4, 31 August 2018 (2018-08-31), ISSN: 1671-1637 *
WANG, SHUHONG ET AL.: "Spatial Modeling of Refined Structural Plane of Rock Mass and Block Stability Analysis", JOURNAL OF NORTHEASTERN UNIVERSITY (NATURAL SCIENCE), vol. 33, no. 8, 31 August 2012 (2012-08-31), ISSN: 1005-3002 *
WANG, SHUHONG ET AL.: "Spatial Modelling and Quick Identification of Unstable Rock Blocks Based on Digital Photogrammetry", CHINESE JOURNAL OF ROCK MECHANICS AND ENGINEERING, vol. 29, 30 May 2010 (2010-05-30), ISSN: 1000-6915, DOI: 2 *

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113781441A (zh) * 2021-09-13 2021-12-10 中铁一局集团第二工程有限公司 一种应用于节理岩体隧道开挖过程中的注浆范围优化方法
CN113781441B (zh) * 2021-09-13 2024-02-27 中铁一局集团第二工程有限公司 一种应用于节理岩体隧道开挖过程中的注浆范围优化方法
CN114565848A (zh) * 2022-02-25 2022-05-31 佛山读图科技有限公司 一种复杂场景的药液液位检测方法及系统
CN114565848B (zh) * 2022-02-25 2022-12-02 佛山读图科技有限公司 一种复杂场景的药液液位检测方法及系统
CN117211886A (zh) * 2023-11-07 2023-12-12 南京派光智慧感知信息技术有限公司 一种隧道掌子面多元信息一体化采集系统及其使用方法
CN117211886B (zh) * 2023-11-07 2024-01-19 南京派光智慧感知信息技术有限公司 一种隧道掌子面多元信息一体化采集系统及其使用方法
CN117395983A (zh) * 2023-11-16 2024-01-12 深圳市创芯智汇电子科技有限公司 一种pcb板贴片自动检测方法及其装置

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