Method and system for evaluating rock mass facility

Abstract

The present invention relates to a method for evaluating a rock mass facility by an electronic device. The method comprises the steps of: acquiring first data which is 2D image data obtained by capturing a rock mass facility by using a camera sensor; acquiring second data which is 3D point cloud data obtained by capturing the rock mass facility by using a LIDAR sensor; and analyzing the second data on the basis of the first data and the second data in order to evaluate the risk of the rock mass facility.

Description

Rock facility evaluation method and system

[0001] The present invention relates to a method and system for evaluating rock structures. More specifically, the present invention relates to a method and system for evaluating the risk index of rock structures using data on rock structures acquired using camera sensors and lidar sensors.

[0002] Rock structures include various structures that contain rock mass, and if the rock structure collapses or is exposed to danger during use, significant human and material damage occurs.

[0003] In particular, if the risk of a rock structure is overlooked or an overlooked risk with a low probability leads to an actual collapse, significant human and material damage may occur.

[0004] There have already been frequent cases where the excavated rock face or slope at a tunnel site collapsed, causing numerous casualties or paralyzing the country's infrastructure.

[0005] To more accurately assess rock structures, 3D point cloud data is fundamentally necessary. However, the sheer volume of 3D point cloud data for rock structures is so enormous that a technology that can increase computational speed and efficiency while not compromising the accuracy of rock structure assessments is needed.

[0006] The present invention, in consideration of these problems, outputs discontinuities corresponding to rock structures and their boundaries in a different manner from the prior art using 2D image data and 3D point cloud data, and outputs a risk index for the output discontinuities based on the boundary difference, thereby increasing computational efficiency without compromising accuracy for the discontinuities, and thereby providing a method and system for evaluating rock structures that can further increase accuracy in terms of risk assessment.

[0007] In order to solve the above-described problem, a method for evaluating a rock structure by an electronic device according to an embodiment of the present invention is provided. The method may include the steps of: acquiring first data, which is 2D image data of a rock structure photographed using a camera sensor; acquiring second data, which is 3D point cloud data of the rock structure photographed using a lidar sensor; and analyzing the second data based on the first data and the second data to evaluate the risk of the rock structure.

[0008] According to one embodiment, the step of analyzing the second data based on the first data and the second data may include the steps of: obtaining a first boundary from the first data; aligning the first data and the second data; dividing the second data into a plurality of discontinuity segment data based on the first boundary; and determining a risk index of the rock structure based on the plurality of discontinuity segment data.

[0009] According to one embodiment, the step of determining the risk index of the rock facility based on the plurality of discontinuity surface segment data may include the step of: outputting a plurality of discontinuity surfaces corresponding to the plurality of discontinuity surface segment data based on the plurality of discontinuity surface segment data; obtaining a second boundary from the plurality of discontinuity surfaces; obtaining boundary difference data by comparing the first boundary and the second boundary; and determining the risk index of the rock facility based on the boundary difference data.

[0010] In one embodiment, the risk indicator can be determined based on the boundary of the discontinuity surface and the risk area.

[0011] According to one embodiment, the method may further include the step of acquiring third data, which is hyperspectral data obtained by photographing the slope using a hyperspectral sensor; and the step of determining a modified risk index of the rock structure based on the risk index and the third data.

[0012] To solve the aforementioned problem, a rock structure risk assessment system according to another embodiment of the present invention is provided. The system may include a rock structure photographing means including a camera sensor and a lidar sensor for photographing the rock structure; and a rock structure risk assessment server for determining a risk index for the rock structure based on first data and second data acquired from the rock structure photographing means for evaluating the rock structure.

[0013] According to one embodiment, the rock facility risk assessment server may obtain the first data, which is 2D image data of a rock facility photographed using the camera sensor; obtain the second data, which is 3D point cloud data of the rock facility photographed using the lidar sensor; and analyze the second data based on the first data and the second data to assess the risk of the rock facility.

[0014] In order to solve the problem as described above, a method for evaluating a rock structure by an electronic device according to another embodiment of the present invention is provided. The method comprises the steps of: obtaining first data which is 2D image data of a rock structure photographed using a camera sensor; obtaining second data which is 3D point cloud data of the rock structure photographed using a lidar sensor; obtaining a first boundary from the first data; aligning the first data and the second data; dividing the second data into a plurality of discontinuous surface segment data based on the first boundary; outputting a plurality of discontinuous surfaces corresponding to the plurality of discontinuous surface segment data based on the plurality of discontinuous surface segment data; obtaining a second boundary from the plurality of discontinuous surfaces; comparing the first boundary and the second boundary to obtain boundary difference data - determining a boundary excluding the first boundary from the second boundary as a third boundary; And a step of determining a risk index of the rock facility based on the boundary difference data, wherein the step of determining the risk index of the rock facility may be characterized in that (i) if the ratio of the number or length of the third boundaries to the number or length of the first boundaries is greater than or equal to a predetermined ratio, a weight is applied to the risk index to determine that the rock facility has a higher risk; and if the ratio is less than the predetermined ratio, a reduction value is applied to the risk index to determine that the rock facility has a lower risk; and if a risk area among the plurality of discontinuities is closer to the third boundary than to the first boundary, a weight is applied to the risk index to determine that the rock facility has a higher risk; and (ii) if the risk area is closer to the first boundary than to the third boundary, a reduction value is applied to the risk index to determine that the rock facility has a lower risk.

[0015] Specific details of other embodiments are included in the specific contents and drawings for carrying out the invention.

[0016] The rock facility evaluation method and system according to the present invention outputs discontinuities and boundaries of discontinuities corresponding to rock facilities in a manner different from the prior art using 2D image data and 3D point cloud data, and outputs risk indices for the output discontinuities based on boundary differences, thereby increasing computational efficiency while not compromising accuracy for discontinuities and further increasing accuracy in terms of risk assessment.

[0017] Figure 1 is a schematic diagram illustrating a rock facility risk assessment system according to one embodiment.

[0018] Figure 2 is a flowchart showing a specific process of a method for evaluating a rock facility according to one embodiment.

[0019] FIG. 3 is a flowchart showing a specific process of analyzing second data based on first data and second data in a method for evaluating a rock facility according to one embodiment.

[0020] FIG. 4 is a diagram showing a process of segmenting a rock facility based on a first boundary and a second boundary in a method for evaluating a rock facility according to one embodiment.

[0021] FIG. 5 is a flowchart showing a specific process for determining a risk index of a rock facility in a method for evaluating a rock facility according to one embodiment.

[0022] FIG. 6 is a diagram showing a process of determining a third boundary based on a first boundary and a second boundary in a method for evaluating a rock facility according to one embodiment of the present invention.

[0023] In order to solve the above-described problem, a method for evaluating a rock structure by an electronic device according to an embodiment of the present invention is provided. The method may include the steps of: acquiring first data, which is 2D image data of a rock structure photographed using a camera sensor; acquiring second data, which is 3D point cloud data of the rock structure photographed using a lidar sensor; and analyzing the second data based on the first data and the second data to evaluate the risk of the rock structure.

[0024] According to one embodiment, the step of analyzing the second data based on the first data and the second data may include the steps of: obtaining a first boundary from the first data; aligning the first data and the second data; dividing the second data into a plurality of discontinuity segment data based on the first boundary; and determining a risk index of the rock structure based on the plurality of discontinuity segment data.

[0025] According to one embodiment, the step of determining the risk index of the rock facility based on the plurality of discontinuity surface segment data may include the step of: outputting a plurality of discontinuity surfaces corresponding to the plurality of discontinuity surface segment data based on the plurality of discontinuity surface segment data; obtaining a second boundary from the plurality of discontinuity surfaces; obtaining boundary difference data by comparing the first boundary and the second boundary; and determining the risk index of the rock facility based on the boundary difference data.

[0026] In one embodiment, the risk indicator can be determined based on the boundary of the discontinuity surface and the risk area.

[0027] According to one embodiment, the method may further include the step of acquiring third data, which is hyperspectral data obtained by photographing the slope using a hyperspectral sensor; and the step of determining a modified risk index of the rock structure based on the risk index and the third data.

[0028] The advantages and features of the present invention, as well as the methods for achieving them, will become clearer with reference to the embodiments described in detail with the accompanying drawings. However, the present invention is not limited to the embodiments presented below, but can be implemented in various different forms, and it should be understood that all modifications, equivalents, and alternatives included within the spirit and technical scope of the present invention are included. The embodiments presented below are provided to ensure a complete disclosure of the present invention and to fully inform those skilled in the art of the invention of the scope of the invention.

[0029] In explaining the present invention, if it is determined that a detailed description of a related known technology may obscure the gist of the present invention, the detailed description is omitted.

[0030] The terminology used herein is for the purpose of describing embodiments and is not intended to limit the present invention. In this specification, singular forms also include plural forms, unless specifically stated otherwise. As used herein, the terms "comprises" and / or "comprising" do not exclude the presence or addition of one or more other components in addition to the components mentioned.

[0031] In addition, the term "unit" described in this specification means a unit that processes one or more functions or operations, which may be implemented by hardware, software, or a combination of hardware and software. In particular, in this specification, the data input unit, the adjacent point analysis unit, the principal plane calculation unit, the normal vector calculation unit, the density analysis unit, the boundary extraction unit, the closed plane calculation unit, the discontinuity output unit, and the rock facility evaluation unit may be implemented as a configuration included in an electronic device.

[0032] Hereinafter, various embodiments of the present invention will be described in detail with reference to the attached drawings.

[0033]

[0034] Figure 1 is a schematic diagram illustrating a rock facility risk assessment system according to one embodiment.

[0035] As illustrated in FIG. 1, the rock facility risk assessment system may include an electronic device (100) or a rock facility risk assessment server (100) that performs specific operations of a rock facility assessment method; a rock facility photographing means (200) that includes at least one of a camera sensor, a lidar sensor, and a hyperspectral sensor for photographing a rock facility; and a management server (300) and a public institution server (300) responsible for managing rock facilities configured to store or manage data related to rock facility assessment.

[0036] The electronic device (100) or the rock facility risk assessment server (100) can obtain various data related to the rock facility from the rock facility photographing means (200) and perform specific operations of the rock facility assessment method described below.

[0037] More specifically, the electronic device (100) or the rock facility risk assessment server (100) may obtain first data, which is 2D image data of a rock facility photographed using a camera sensor; obtain second data, which is 3D point cloud data of the rock facility photographed using a lidar sensor; obtain a first boundary from the first data; align the first data and the second data; divide the second data into a plurality of discontinuous surface segment data based on the first boundary; output a plurality of discontinuous surfaces corresponding to the plurality of discontinuous surface segment data based on the plurality of discontinuous surface segment data; obtain a second boundary from the plurality of discontinuous surfaces; obtain boundary difference data by comparing the first boundary and the second boundary, wherein a boundary excluding the first boundary from the second boundary is determined as a third boundary; and determine a risk index of the rock facility based on the boundary difference data.

[0038] The rock facility photographing means (200) may be configured to be equipped with at least one of a camera sensor, a lidar sensor, and a hyperspectral sensor on an aerial vehicle such as a drone or UAV, or a ground vehicle such as a management vehicle.

[0039] The management server (300) or public institution server (300) can store, manage, or utilize data related to the evaluation of rock facilities or data acquired or processed in the process of performing a method for evaluating rock facilities by an electronic device (100) or a rock facility risk assessment server (100).

[0040] In the present disclosure, the electronic device (100) or the rock facility risk assessment server (100) or the public institution server (300) or the management server (300) may be conveniently expressed as an electronic device or server, or as an electronic device connected to the server. In this case, the electronic device includes, but is not limited to, a mobile terminal, a smart phone, a laptop computer, a tablet PC, an e-book terminal, a digital broadcasting terminal, a PDA (Personal Digital Assistant), etc.

[0041] The electronic device (100) may include a data input unit (110), a boundary detection unit (120), a data alignment unit (130), a data segmentation unit (140), a discontinuity surface output unit (150), a risk indicator output unit (160), and a rock facility management unit (170).

[0042] The data input unit (110) can acquire first data, which is 2D image data obtained by photographing a rock structure using a camera sensor; second data, which is 3D point cloud data obtained by photographing the rock structure using a lidar sensor; and third data, which is hyperspectral data obtained by photographing the slope using a hyperspectral sensor.

[0043] The boundary detection unit (120) can obtain a first boundary from the first data; obtain a second boundary from the plurality of discontinuities; and obtain boundary difference data by comparing the first boundary and the second boundary - determining a boundary excluding the first boundary from the second boundary as a third boundary.

[0044] The data alignment unit (130) can align the first data and the second data.

[0045] The data segmentation unit (140) can divide the second data into a plurality of discontinuous surface segment data based on the first boundary.

[0046] The discontinuous surface output unit (150) can output a plurality of discontinuous surfaces corresponding to the plurality of discontinuous surface segment data based on the plurality of discontinuous surface segment data.

[0047] The risk index output unit (160) determines a risk index of the rock facility based on the boundary difference data; and can determine a modified risk index of the rock facility based on the risk index and the third data.

[0048] The rock facility management unit (170) can perform various operations to store, manage, or utilize data related to rock facility evaluation, and can transmit and receive the data to and from a public institution server (300) or a management server (300).

[0049] In this disclosure, the term "rock structure" refers to various structures that are formed naturally or artificially, such as slopes, rock excavation faces, and landslide slopes, and that require risk management.

[0050]

[0051] Figure 2 is a flowchart showing a specific process of a method for evaluating a rock facility according to one embodiment.

[0052] In step S210, the electronic device (100) can obtain first data, which is 2D image data obtained by photographing a rock structure using a camera sensor.

[0053] In the present disclosure, the term first data means image information on a rock structure photographed using a camera sensor, but the first data does not simply mean image information in a photographed state, but means information including x, y, z geometric coordinates (location information), RGB information, or boundary information on the rock structure obtained by analyzing a plurality of photographed images of the rock structure.

[0054] In step S220, the electronic device (100) can obtain second data, which is 3D point cloud data obtained by photographing the rock structure using a lidar sensor.

[0055] In the present disclosure, the term second data means a 3D point cloud, which is a collection of 3D information on a rock structure photographed using a lidar sensor, and includes information expressed as x, y, z geometric coordinates (location information) or vectors, and the second data may also include other information that can be acquired using a lidar sensor, such as reflectance information, but is not limited thereto.

[0056] In step S230, the electronic device (100) can analyze the second data based on the first data and the second data to evaluate the risk of the rock facility.

[0057] Assessing the risk of rock structures using only secondary data has limitations in terms of computational efficiency because the amount of 3D point cloud data for rock structures is extremely large.

[0058] In the method for evaluating a rock facility according to the present invention, the risk of a rock facility can be evaluated by analyzing the second data based on the first data as well as the second data, thereby increasing computational efficiency without compromising evaluation accuracy, as will be described later.

[0059]

[0060] FIG. 3 is a flowchart showing a specific process of analyzing second data based on first data and second data in a method for evaluating a rock facility according to one embodiment.

[0061] In step S310, the electronic device (100) can obtain a first boundary from the first data.

[0062] Referring to FIG. 4, the electronic device (100) can determine and obtain a first boundary using various boundary extraction algorithms from first data, which is 2D image data obtained by photographing a rock structure using a camera sensor.

[0063] More specifically, the electronic device (100) can obtain 3D modeling data for a rock facility based on first data and determine a first boundary based on the 3D modeling data.

[0064] The first boundary determined based on the first data may have relatively lower accuracy than the boundary determined based on the second data, which is 3D point cloud data obtained by photographing the rock structure using a lidar sensor, but the computational efficiency is relatively very high.

[0065] In other words, the amount of computation required in the process of determining the first boundary using 3D modeling data acquired based on the first data is much less than the amount of computation required in the process of determining the boundary based on the second data.

[0066] In step S320, the electronic device (100) can align the first data and the second data.

[0067] The first data and the second data can be aligned based on location information associated with the rock facility or predetermined marking information included in the first data and the second data.

[0068] In step S330, the electronic device (100) can divide the second data into a plurality of discontinuous surface segment data based on the first boundary.

[0069] As the first data and the second data are aligned, a first boundary obtained from the first data can be displayed on the second data, and a plurality of discontinuities constituting a rock facility on the second data can be divided into a plurality of discontinuity boundary segment data according to the first boundary.

[0070] Referring to FIG. 4, after the first data and the second data are aligned, the electronic device (100) displays a first boundary on the second data, so that a plurality of discontinuous surfaces constituting a rock facility on the second data can be divided into a plurality of discontinuous surface segment data.

[0071] In step S340, the electronic device (100) can determine a risk index of the rock facility based on the plurality of discontinuous surface segment data.

[0072] The risk index for a rock facility can be determined as the sum of risk indices for multiple discontinuity segment data constituting the rock facility or the discontinuity segment data corresponding to multiple discontinuity segment data.

[0073] According to one embodiment, the step of determining the risk index of the rock facility based on the plurality of discontinuity surface segment data may include the step of: outputting a plurality of discontinuity surfaces corresponding to the plurality of discontinuity surface segment data based on the plurality of discontinuity surface segment data; obtaining a second boundary from the plurality of discontinuity surfaces; obtaining boundary difference data by comparing the first boundary and the second boundary; and determining the risk index of the rock facility based on the boundary difference data.

[0074]

[0075] FIG. 5 is a flowchart showing a specific process for determining a risk index of a rock facility in a method for evaluating a rock facility according to one embodiment.

[0076] In step S510, the electronic device (100) can output a plurality of discontinuous surfaces corresponding to the plurality of discontinuous surface segment data based on the plurality of discontinuous surface segment data.

[0077] In the method for evaluating a rock structure according to the present invention, in order to determine the risk index of the rock structure, the entire discontinuity constituting the rock structure is not output at once from the second data, which is the entire cloud point data, but rather the second data is first divided into a plurality of discontinuity segment data using the first boundary obtained from the first data, the divided discontinuity segment data is analyzed in parallel to output a plurality of discontinuities corresponding to the discontinuity segment data, and all of them are combined to secondarily output the entire discontinuity. Accordingly, complex calculations, especially for the boundary portion, are first omitted, so the amount of calculation is greatly reduced, and the parallel calculation function of the CPU or GPU can be utilized to greatly increase the computational efficiency without compromising the accuracy of the discontinuity portion. A technique for supplementing the accuracy in terms of risk assessment of the rock structure by first omitting the complex calculations for the boundary portion will be described later.

[0078] Referring to FIG. 4, the electronic device (100) can output a discontinuous surface for each of a plurality of segment data distinguished from the second data, for example, the first segment, the second segment, the third segment, the fourth segment, and the fifth segment.

[0079] In the present disclosure, segment data may be expressed as segments for convenience.

[0080] The electronic device (100) can output a discontinuous surface using various algorithms that output a discontinuous surface using a 3D point cloud from the separated second data.

[0081] In step S520, the electronic device (100) can obtain a second boundary from the plurality of discontinuous surfaces.

[0082] Since the second boundary is likely to be relatively more accurate than the first boundary, the second boundary may contain information about a new boundary (i.e., the third boundary) that was not present in the first boundary.

[0083] This is because boundary extraction based on the second data, which is 3D point cloud data captured using a lidar sensor, is more likely to be accurate than boundary extraction based on the first data, which is 2D image data captured using a camera sensor. Due to the complexity of discontinuities, shading, and image overlapping issues, it may be difficult to determine a specific boundary by analyzing the first data acquired from the camera sensor.

[0084] Referring to FIG. 4, the electronic device (100) outputs a plurality of discontinuities by step S510, and can obtain the entire discontinuity surface for a specific rock facility area by collecting all of the plurality of discontinuities.

[0085] Since the process of outputting multiple discontinuous surfaces corresponding to multiple discontinuous surface segment data separated from the second data is an analysis of a 3D point cloud, the entire discontinuous surface already includes the second boundary, that is, the boundary determined as a result of analyzing the 3D point cloud data.

[0086] In step S530, the electronic device (100) can obtain boundary difference data by comparing the first boundary and the second boundary - determining the boundary excluding the first boundary from the second boundary as the third boundary.

[0087] Referring to Fig. 6, for the second segment, a third boundary, which is the difference between the first boundary and the second boundary, can be determined, and the third boundary can be expressed as a linearized boundary. In Fig. 6, the number of third boundaries is four, and the third boundary is boundary information including four straight lines.

[0088] In step S540, the electronic device (100) can determine a risk index of the rock facility based on the boundary difference data.

[0089] The risk index of a rock structure can be determined by classifying the rock structure using various classification methods, such as the rock mass rating (RMR), and utilizing various risk analysis factors used in such classification methods. For example, the electronic device (100) can utilize risk analysis factors, such as the RQD, the roughness and curvature of the discontinuity surface, and the area, boundary, and direction where the joint spacing is formed, to determine the risk index of a rock structure.

[0090] According to one embodiment, the electronic device (100) may determine a high-risk area, such as an area with a high probability of collapse, by considering risk analysis factors to determine a risk index of a rock structure. For example, the electronic device (100) may determine an area on a discontinuity surface where the roughness and curvature exceed a predetermined standard or where the joint spacing is below a predetermined standard as a risk area on the discontinuity surface.

[0091] In the rock facility evaluation method according to the present invention, the risk of the rock facility can be more accurately evaluated by using not only the elements for determining the risk index of the rock facility by using the first data and the second data, but also the boundary difference data, i.e., the third boundary.

[0092] The third boundary, as described above, includes information related to the boundary of the discontinuity that is not shown in the first boundary, so that the electronic device (100) can indirectly identify areas that are relatively more complex or difficult to identify in the discontinuity through the third boundary. In other words, considering the third boundary in the risk assessment of a rock structure allows for identifying areas that may be omitted in the risk assessment in the discontinuity, while at the same time reflecting the possibility that the actual possibility of collapse is higher due to the high complexity in the actual risk index, and further enabling analysis of areas that may be relatively more complex with high computational efficiency.

[0093] Accordingly, the electronic device (100) determines that the risk index is higher when the number or length of the third boundary is greater or the area containing the risk analysis elements (i.e., the risk area) is closer to or more distributed near the third boundary, thereby enabling the primary preparation for missed risks or more accurately reflecting the actual high risk possibility in the risk index.

[0094]

[0095] FIG. 6 is a diagram showing a process of determining a third boundary based on a first boundary and a second boundary in a method for evaluating a rock facility according to one embodiment of the present invention.

[0096] Referring to Fig. 6, the difference in the second segment of the first data and the second data in Fig. 5 is the third boundary.

[0097] Referring to Fig. 6, in the second segment, the number of third boundaries is 4. In contrast, in the first segment, the third segment, and the fourth segment, the number of third boundaries is 0, and in the fifth segment, the number of third boundaries is 1.

[0098] According to one embodiment, the electronic device (100) may determine the risk index of the second segment, which has the largest number of third boundaries and the longest length, as the highest risk grade when other risk analysis factors are determined to have the same risk level in the first to fifth segments; determine the risk index of the fifth segment, which has the largest number of third boundaries and the longest length, as the highest risk grade after the second segment; and determine the risk indexes of the first segment, the third segment, and the fourth segment as the lowest risk grade.

[0099] According to one embodiment, the electronic device (100) may determine that the first to fifth segments have the same risk level based on other risk analysis factors, and if the number or length ratio of the third boundaries to the number or length of the first boundaries is greater than or equal to a predetermined ratio, the electronic device may determine that the first to fifth segments have a higher risk level by applying a (predetermined) weight to the risk index; and if the number or length ratio of the third boundaries to the number or length of the first boundaries is less than the predetermined ratio, the electronic device may determine that the first to fifth segments have a lower risk level by applying a (predetermined) discount value to the risk index.

[0100] For example, if the predetermined ratio is 0.3, (i) the risk index of the second segment may have a predetermined weight because the ratio of the number of third boundaries (4) to the number of first boundaries (8) for the second segment is 0.5; and (ii) the risk index of the fifth segment may have a predetermined reduction because the ratio of the number of third boundaries (1) to the number of first boundaries (8) for the fifth segment is 0.125.

[0101] According to one embodiment, the electronic device (100) may determine that the first to fifth segments have the same risk level based on the risk area on the discontinuity plane, i.e., when the shape and size of the risk area on the discontinuity plane are the same, and when the risk area on the discontinuity plane is closer to the third boundary than to the first boundary, a weight may be applied to the risk index to determine that the risk area has a higher risk level; and when the risk area is closer to the first boundary than to the third boundary, a reduction value may be applied to the risk index to determine that the risk area has a lower risk level.

[0102] According to one embodiment, the step of determining the risk index of the rock facility may be characterized by: (i) determining a higher risk by applying a weight to the risk index when the ratio of the number or length of the third boundaries to the number or length of the first boundaries is greater than or equal to a predetermined ratio; and determining a lower risk by applying a reduction value to the risk index when the ratio is less than the predetermined ratio; and (ii) determining a higher risk by applying a weight to the risk index when a risk area among the plurality of discontinuities is closer to the third boundary than to the first boundary; and determining a lower risk by applying a reduction value to the risk index when the risk area is closer to the first boundary than to the third boundary.

[0103]

[0104] Although embodiments of the present invention have been described in more detail with reference to the attached drawings, the present invention is not necessarily limited to these embodiments, and various modifications may be made within a scope that does not depart from the technical spirit of the present invention.

[0105] Accordingly, the embodiments disclosed in the present invention are intended to illustrate, rather than limit, the technical concepts of the present invention, and the scope of the technical concepts of the present invention is not limited by these embodiments. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. The scope of protection of the present invention should be interpreted by the following claims, and all technical concepts within the scope equivalent thereto should be interpreted as being included within the scope of the rights of the present invention.

Claims

1. In a method for evaluating rock structures by an electronic device, A step of acquiring first data, which is 2D image data of a rock structure captured using a camera sensor; A step of acquiring second data, which is 3D point cloud data obtained by photographing the rock structure using a lidar sensor; and A method for evaluating a rock facility, comprising a step of analyzing the second data based on the first data and the second data to evaluate the risk of the rock facility.

2. In paragraph 1, The step of analyzing the second data based on the first data and the second data comprises: A step of obtaining a first boundary from the first data; A step of aligning the first data and the second data; A step of dividing the second data into a plurality of discontinuous surface segment data based on the first boundary; and A method comprising the step of determining a risk index of the rock facility based on the plurality of discontinuous surface segment data.

3. In paragraph 2, A method in which the above risk indicator is determined based on the boundary of the discontinuity surface and the risk area.

4. In paragraph 2, A method wherein the above risk indicator is determined based on the difference between the boundaries obtained from the first boundary data and the second boundary data.

5. In paragraph 2, A step of acquiring third data, which is hyperspectral data obtained by photographing the slope using a hyperspectral sensor; and A method further comprising the step of determining a modified risk index of the rock facility based on the risk index and the third data.

6. A rock structure photographing means including a camera sensor and a lidar sensor for photographing rock structures; and A rock facility risk assessment system, comprising a rock facility risk assessment server that determines a risk index for the rock facility based on first data and second data obtained from the rock facility photographing means to evaluate the rock facility.

7. In paragraph 5, The above rock facility risk assessment server is, Obtaining the first data, which is 2D image data of a rock structure captured using the camera sensor; Obtaining the second data, which is 3D point cloud data obtained by photographing the rock structure using the lidar sensor; and A rock facility risk assessment system that analyzes the second data based on the first data and the second data to assess the risk of the rock facility.

8. In paragraph 7, A rock facility risk assessment system, wherein the above risk indicator is determined based on multiple boundary values ​​and risk areas.

9. In paragraph 7, A rock facility risk assessment system, wherein the above risk index is determined based on the difference between the boundaries obtained from the first boundary data and the second boundary data.

10. In paragraph 7, The above rock facility risk assessment server is, Obtaining the third data, which is hyperspectral data obtained by photographing the slope using a hyperspectral sensor; and A rock facility risk assessment system that determines a modified risk index of the rock facility based on the above risk index and the third data.

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