Method and system for scanning and reconstructing three-dimensional form of underground cavity

Abstract

The invention discloses a method and a system for scanning and reconstructing a three-dimensional form of an underground cavity, and relates to the technical field of engineering geophysical prospecting karst detection. Comprising the steps of deploying detection equipment to a target space position and establishing detection system communication connection; setting detection area parameters and sampling parameters, and determining a space scanning strategy; executing space contour data acquisition to obtain a multi-layer space contour data set; reconstructing a spatial connection structure between adjacent sampling layers, and generating a local surface model; and fusing all local surface models, and constructing a complete three-dimensional form of the target space. According to the invention, by deploying the detection equipment integrated by multiple sensors and establishing real-time communication connection, all-directional sensing and stable data transmission of the underground cavity environment are realized; by scientifically setting detection parameters and a stratified sampling strategy, the optimal balance between sampling precision and efficiency is realized; spatial reconstruction is carried out by innovatively combining a shortest diagonal method and a bounding box method, and high-precision local surface reconstruction is realized.

Description

Technical Field

[0001] The invention relates to the technical field of engineering geophysical exploration karst detection, in particular to a method and system for scanning and reconstructing the three-dimensional morphology of underground cavities. Background Art

[0002] Underground cavities such as karst and cavities are highly concealed and harmful. Exploration by drilling is only a "one-hole view", and it is costly and inefficient. Traditional engineering geophysical exploration methods can delineate the location of the cave, but cannot accurately measure the three-dimensional shape and volume of the cave. Laser (sonar) can be used to achieve three-dimensional scanning and modeling of caves, but three-dimensional scanning and measurement equipment for underground cavities is rare. Our company uses the design idea of ​​constructing a three-dimensional geological body based on the results of layer-by-layer two-dimensional scanning to develop a set of underground cavity three-dimensional scanning equipment. The scanning probe is placed into the underground cavity to be measured through drilling, and then a 360° scan is performed layer by layer from top to bottom. Each layer can obtain the underground cavity section contour line corresponding to the position of the probe. However, the existing three-dimensional modeling software mainly uses point clouds for three-dimensional mapping, and the three-dimensional mapping effect of the contour lines obtained by layer-by-layer scanning is not ideal. Summary of the invention

[0003] In view of the problems existing in the prior art, the present invention is proposed.

[0004] Therefore, the problem to be solved by the present invention is how to make up for the deficiencies of the prior art so as to realize three-dimensional laser (sonar) scanning measurement and modeling of underground cavities.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] In a first aspect, an embodiment of the present invention provides a method for scanning and reconstructing the three-dimensional morphology of an underground cavity, which includes deploying a detection device to a target spatial position and establishing a communication connection between the detection system;

[0007] Set detection area parameters and sampling parameters, and determine the spatial scanning strategy;

[0008] Perform spatial contour data collection to obtain multi-layer spatial contour data sets;

[0009] Reconstruct the spatial connection structure between adjacent sampling layers and generate a local surface model;

[0010] All local surface models are fused to construct a complete three-dimensional shape of the target space.

[0011] As a preferred solution of the method for scanning and reconstructing the three-dimensional morphology of underground cavities according to the present invention, the setting of detection area parameters and sampling parameters includes:

[0012] Dividing the target detection space into a plurality of parallel scanning layers, and setting the spacing between adjacent scanning layers to a predetermined distance value;

[0013] The sampling resolution of each scanning layer is set to a preset number of points, and the sampling points are evenly distributed along the circumference of the scanning layer;

[0014] Set the starting depth and ending depth of the detection area to the scanning range boundary value;

[0015] Set the system operating parameters to standard parameter values ​​under the predetermined working mode.

[0016] As a preferred solution of the method for scanning and reconstructing the three-dimensional morphology of underground cavities according to the present invention, the execution of spatial contour data acquisition includes:

[0017] Position the detection device to a preset scanning starting point, and determine the current position as the initial sampling layer position;

[0018] The detection device is rotated circumferentially at a predetermined rate, and coordinate data of the spatial contour points are obtained during the rotation process;

[0019] Move the detection device to the next sampling layer position, wherein the distance between adjacent sampling layers is a preset spacing value;

[0020] The circumferential scanning and inter-layer movement process is executed in a loop until data collection of the entire detection area is completed.

[0021] As a preferred solution of the method for scanning and reconstructing the three-dimensional morphology of underground cavities according to the present invention, the reconstruction of the spatial connection structure between adjacent sampling layers includes:

[0022] Inputting the spatial contour data of two adjacent layers into a reconstruction processing unit, and converting the data into a unified coordinate system;

[0023] Perform spatial standardization on the converted contour data and store the processing results in a data buffer area;

[0024] Establishing a spatial mapping relationship for the standardized contour data, and using the mapping result to determine the connection point pairs;

[0025] The determined connection point pairs are constructed into local surface elements, and the surface elements are subjected to quality assessment.

[0026] As a preferred solution of the method for scanning and reconstructing the three-dimensional morphology of underground cavities according to the present invention, the fusion of all local surface models includes:

[0027] The generated local surface models are used to establish a model sequence according to the spatial adjacent relationship;

[0028] Matching and aligning the boundaries of adjacent local surface models, and using the matching results to determine connection parameters;

[0029] Perform boundary transition processing on the local surface model with connection relationship and smooth the transition area;

[0030] The processed local surface models are fused sequentially, and the fusion results are constructed into a complete spatial morphological model.

[0031] As a preferred solution of the method for scanning and reconstructing the three-dimensional morphology of underground cavities described in the present invention, the specific steps of the data standardization process include:

[0032] Match two adjacent layers of contour lines with a bounding box respectively, and use the geometric feature parameters of the bounding box as a standardized benchmark;

[0033] Set the center position of the bounding box of the adjacent layer contour line Determined by the following calculation formula:

[0034]

[0035] The side lengths (Δx, Δy) of the bounding boxes of the contour lines of the adjacent layers are determined by the following calculation formula:

[0036]

[0037] The original contour point coordinates are transformed to the standardized area through the following mapping formula:

[0038]

[0039] Map the transformed coordinate point to the unit square bounding box centered at (0, 0);

[0040] Verify the topological relationship and check the data integrity of the standardized contour points;

[0041] The verified standardized data is used as input data for subsequent reconstruction processing.

[0042] As a preferred solution of the method for scanning and reconstructing the three-dimensional morphology of underground cavities of the present invention, the specific steps of establishing the interlayer transition relationship include:

[0043] Store the normalized contour point data of adjacent layers into arrays a[M] and b[N] respectively, and sort them in a clockwise direction;

[0044] Select the initial connection point b[j] from the lower contour point array b[N] and calculate the spatial distance between it and each point in the upper contour point array a[M];

[0045] Determine the upper-layer point a[i] with the closest distance as the corresponding connection point, and record the index values of the initial connection point pair, bBegin = j, aBegin = i;

[0046] Determine the connection path between the current connection point pair b[j] and a[i] through the following steps:

[0047] Calculate the distance parameters D1 = |b[j] - a[i + 1]| and D2 = |a[i] - b[j + 1]|;

[0048] When D1 < D2, generate a triangular patch △b[j]a[i]a[i + 1], and increment the index i by 1 in a loop;

[0049] When D1 ≥ D2, generate a triangular patch △b[j]a[i]b[j + 1], and increment the index j by 1 in a loop;

[0050] Record the generated triangular patches into the structure array until one contour loop is completed, i.e., j = bBegin and i = aBegin;

[0051] Perform the following optimization processing on the generated set of triangular patches:

[0052] Verify the direction consistency of the triangular patches;

[0053] Optimize the shape quality of the triangular patches;

[0054] Adjust the connection transition of the triangular patches;

[0055] Use the optimized set of triangular patches as the transition connection structure between adjacent layers.

[0056] In a second aspect, an embodiment of the present invention provides a system for scanning and reconstructing the three-dimensional morphology of underground cavities, which includes a device deployment module, a parameter configuration module, a data acquisition module, a reconstruction processing module, and a model construction module;

[0057] The device deployment module is used to deploy detection devices to the target spatial position, establish a communication connection for the detection system, and perform device connection tests;

[0058] The parameter configuration module is used to set detection area parameters and sampling parameters, generate a scanning section layout plan, and configure system operation parameters;

[0059] The data acquisition module is used to control the detection devices to perform spatial contour data acquisition, obtain multi-layer spatial contour data sets, and monitor the acquisition process;

[0060] The reconstruction processing module is used to perform standardization processing on the acquired contour data, reconstruct the spatial connection structure between adjacent sampling layers, and generate a local surface model;

[0061] The model building module is used to optimize the local surface model, establish the inter-layer transition relationship, fuse all the local surface models, and build a complete three-dimensional form of the target space.

[0062] In a third aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the method for scanning and reconstructing the three-dimensional morphology of underground cavities as described in the first aspect of the present invention are implemented.

[0063] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the method for scanning and reconstructing the three-dimensional morphology of underground cavities as described in the first aspect of the present invention are implemented.

[0064] The beneficial effects of the present invention are as follows: the underground cavity three-dimensional morphological scanning and reconstruction method provided by the present invention breaks through the limitations of traditional drilling detection by deploying multi-sensor integrated detection equipment and establishing real-time communication connection, realizes all-round perception and stable data transmission of the underground cavity environment, and lays a hardware foundation for high-quality three-dimensional reconstruction; by scientifically setting detection parameters and layered sampling strategies, the optimal balance between sampling accuracy and efficiency is achieved, a standardized data acquisition scheme is established, and the integrity and representativeness of the data are ensured; through the automated rotation scanning and interlayer displacement of the detection equipment, the data acquisition efficiency is significantly improved, continuous and complete spatial contour data are obtained, and the problem of low efficiency of traditional point measurement methods is solved; by innovatively combining the shortest diagonal method and the bounding box method for spatial reconstruction, the problem of large differences in contours of adjacent layers in complex underground cavities is effectively overcome, and high-precision local surface reconstruction is achieved; by steps such as model sequence establishment, boundary matching and transition processing, the seamless fusion of local models is achieved, the computational complexity of large cavity modeling is reduced, and the continuity and authenticity of the overall model are guaranteed. The present invention has made significant progress in detection efficiency, reconstruction accuracy and application reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0066] Figure 1 Flow chart of the method for scanning and reconstructing the three-dimensional morphology of underground cavities;

[0067] Figure 2 Schematic diagram of the shortest diagonal method for scanning and reconstructing the three-dimensional morphology of underground cavities;

[0068] Figure 3 Schematic diagram of the equipment operating status for scanning and reconstructing the three-dimensional morphology of underground cavities. DETAILED DESCRIPTION

[0069] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0070] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0071] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0072] Example

[0073] Reference Figure 1-2 , which is the first embodiment of the present invention, provides a method for scanning and reconstructing the three-dimensional morphology of underground cavities, comprising:

[0074] S1: Deploy the detection equipment to the target space location and establish a detection system communication connection.

[0075] Deploying the detection equipment to the target space location and establishing a communication connection for the detection system can be achieved through an integrated quick-install device structure. Specifically, this embodiment adopts a portable combined device solution, including a lightweight portable host, an integrated detector, and an intelligent winch system. Among them, the host adopts an industrial-grade tablet computer, the detector adopts a fully sealed waterproof design, and the winch is made of carbon fiber composite materials.

[0076] In engineering applications, underground cavity surveys often face problems such as difficult equipment transportation and complex installation, especially in complex terrain environments such as mountainous areas and mining areas. This embodiment solves the problem of equipment deployment through modular quick-installation design and lightweight material selection.

[0077] Through the above method, the rapid deployment of detection equipment is achieved, and the entire set of equipment can be installed and debugged in a short time. This solution is particularly suitable for emergency surveys and field work environments, and significantly improves work efficiency.

[0078] S2: Set detection area parameters and sampling parameters, and determine the spatial scanning strategy.

[0079] This embodiment adopts an adaptive parameter configuration scheme. According to the preliminary detection results of the cavity, the system automatically calculates the optimal scanning parameters. Among them, the scanning layer spacing is automatically encrypted in complex areas (minimum up to 50mm), and appropriately relaxed in regular areas (maximum 200mm); the sampling point density is dynamically adjusted with depth to ensure data quality.

[0080] In engineering applications, different types of underground cavities have different structural characteristics, and fixed parameters are often difficult to adapt to changing environments. This embodiment achieves flexible configuration of sampling strategies through intelligent parameter adjustment.

[0081] This adaptive configuration solution not only ensures the quality of data collection, but also optimizes the efficiency of equipment resource utilization. The system can automatically adjust parameters based on real-time feedback without manual intervention.

[0082] S3: Execute spatial contour data collection to obtain a multi-layer spatial contour data set.

[0083] This embodiment adopts a spiral continuous scanning strategy to replace the traditional layered scanning method. The probe performs continuous spiral scanning during the ascent process, and the sampling interval is automatically adjusted. At the same time, it is equipped with a dual sensor system, which can automatically switch to the optimal distance measurement method in different media environments.

[0084] In engineering applications, traditional layered scanning easily results in discontinuous data and low efficiency. Spiral scanning can obtain more continuous spatial data and reduce information loss.

[0085] This innovative scanning method significantly improves the continuity and integrity of data collection, and is particularly suitable for the detection of complex underground cavities. The dual sensor system ensures reliable measurement in a variety of environments.

[0086] S4: Reconstruct the spatial connection structure between adjacent sampling layers and generate a local surface model.

[0087] This embodiment uses a local reconstruction algorithm based on dynamic grids, adopts an improved Delaunay triangulation method, and introduces a curvature-adaptive grid subdivision mechanism, automatically adjusts the grid density according to the regional complexity, and maintains key features.

[0088] In engineering applications, traditional reconstruction algorithms often have difficulty accurately representing the local features of cavities. This solution uses dynamic mesh technology to achieve accurate reconstruction of complex structures.

[0089] This method is particularly suitable for processing underground cavities with complex shapes, and can better maintain features such as edges, corners, and bumps. At the same time, adaptive meshing reduces the amount of calculation and improves processing efficiency.

[0090] S5: Fuse all local surface models to construct the complete 3D shape of the target space.

[0091] This embodiment adopts a distributed parallel processing strategy. Large holes are reconstructed in regions, and the overlapping region registration technology is used to stitch the model. Efficient computing is achieved through GPU acceleration, and a multi-resolution hierarchical modeling mechanism is adopted.

[0092] In engineering applications, the overall reconstruction of large cavities often faces the problems of large computational complexity and low efficiency. Distributed processing strategies significantly improve modeling efficiency.

[0093] This method not only speeds up model reconstruction, but also ensures the accuracy of the splicing area. The multi-resolution mechanism can provide model expressions with different precisions as needed.

[0094] Example 2

[0095] Reference Figure 1 to Figure 3 , which is the second embodiment of the present invention, and provides a method for scanning and reconstructing the three-dimensional morphology of underground cavities, comprising:

[0096] S1, deploy detection equipment to the target space location and establish a communication connection with the detection system;

[0097] In the embodiment of the present application, the equipment used is currently achievable, and the structure of the equipment is composed of a ground host 101, a communication cable 102, a winch 103, a guide bracket 105, a downhole probe 106, etc. The ground host 101 and the downhole probe 106 are connected and communicated through a winch cable 104; the downhole probe 106 integrates laser ranging, sonar ranging, azimuth measurement, mechatronics, infrared photography and other technologies, and can scan the internal contour of the cavity horizontally, uniformly and clockwise under the control of the ground host 101, and can use an infrared camera to view the environmental conditions around the downhole probe in real time through the ground host 101; the ground host 101 is composed of a processor and a memory, etc., and the processor runs acquisition and processing software, which realizes functions such as video acquisition and display, two-dimensional contour vertex data acquisition, and three-dimensional modeling; the winch 103 is designed with a motor and a bidirectional screw, and can realize the automatic winding function under the control of the ground host 101, so as to achieve the purpose of automatically retracting and releasing the downhole probe 106.

[0098] The above-mentioned equipment, under the control of the ground host 101, after the current section (layer) is scanned for one circle, the winch 103 motor automatically places the downhole probe 106 to the next section (layer) and starts a new round of two-dimensional contour line scanning, and repeats this cycle until the entire underground cavity 107 is scanned layer by layer from top to bottom (from bottom to top); the two-dimensional contour vertex data of the underground cavity 107 obtained at each layer are obtained by automatically scanning the underground cavity 107 360° clockwise at different depths with the borehole 108 as the center, and the layers are parallel to each other, and the total number of contour vertices scanned on each layer and the spacing between two layers can be customized.

[0099] It should be noted that the equipment connection and test: connect all the parts of the equipment, and after the test is normal, place the probe through the drill hole into the starting position of the underground cavity to be tested (i.e. the first scanning section).

[0100] S2, setting detection area parameters and sampling parameters, and determining the spatial scanning strategy;

[0101] In the embodiment of the present application, the setting of detection area parameters and sampling parameters includes:

[0102] Dividing the target detection space into a plurality of parallel scanning layers, and setting the spacing between adjacent scanning layers to a predetermined distance value;

[0103] The sampling resolution of each scanning layer is set to a preset number of points, and the sampling points are evenly distributed along the circumference of the scanning layer;

[0104] Set the starting depth and ending depth of the detection area to the scanning range boundary value;

[0105] Set the system operating parameters to standard parameter values ​​under the predetermined working mode.

[0106] Furthermore, the parameter settings include: mainly setting the total number of contour vertices for each layer scan, the spacing between two layers, the scanning start depth position, i.e., the first scanning section, and the scanning end depth position, i.e., the last scanning section;

[0107] It should be noted that there are multiple scanning sections between the first scanning section and the last scanning section; the layers are parallel to each other, and the total number of contour vertices scanned in each layer and the distance between two layers can be customized.

[0108] S3, executing spatial profile data collection to obtain a multi-layer spatial profile data set;

[0109] In an embodiment of the present application, the performing of spatial profile data collection includes:

[0110] Position the detection device to a preset scanning starting point, and determine the current position as the initial sampling layer position;

[0111] The detection device is rotated circumferentially at a predetermined rate, and coordinate data of the spatial contour points are obtained during the rotation process;

[0112] Move the detection device to the next sampling layer position, wherein the distance between adjacent sampling layers is a preset spacing value;

[0113] The circumferential scanning and inter-layer movement process is executed in a loop until data collection of the entire detection area is completed.

[0114] Furthermore, the 2D contour line scanning includes the downhole probe rotating 360° clockwise at a constant speed under the control of the ground host, scanning and obtaining the contour vertices of the current section of the underground cavity, and obtaining a set of 2D contour lines with the origin located at the probe. Then, under the control of the ground host, the winch motor automatically places the probe to the next section and starts a new round of 2D contour line scanning.

[0115] It should be noted that the vertex data of the two-dimensional contour of each layer of the underground cavity are obtained by automatically scanning the underground cavity 360° clockwise at different depths with the borehole as the center. Under the control of the ground host, the equipment automatically places the probe to the next section after the current section is scanned for one circle, and the cycle continues until the entire underground cavity is scanned layer by layer from top to bottom (from bottom to top).

[0116] S4, reconstructs the spatial connection structure between adjacent sampling layers and generates a local surface model;

[0117] In an embodiment of the present application, reconstructing the spatial connection structure between adjacent sampling layers includes:

[0118] Inputting the spatial contour data of two adjacent layers into a reconstruction processing unit, and converting the data into a unified coordinate system;

[0119] Perform spatial standardization on the converted contour data and store the processing results in a data buffer area;

[0120] Establishing a spatial mapping relationship for the standardized contour data, and using the mapping result to determine the connection point pairs;

[0121] The determined connection point pairs are constructed into local surface elements, and the surface elements are subjected to quality assessment.

[0122] Furthermore, the three-dimensional surface model between two adjacent layers of contour lines is reconstructed: the ground host acquisition and processing software uses the shortest diagonal method to generate triangular faces, connects the previous section contour line A and the current section contour line B, and forms a three-dimensional surface model between two adjacent layers of contour lines. Then, under the control of the ground host, the winch motor automatically places the probe to the next section.

[0123] It should be noted that the processing steps of the shortest diagonal method include: reading the vertex coordinates of the upper and lower layers of contours obtained by clockwise scanning into two groups of arrays respectively, selecting the starting connection point and calculating the shortest distance, and determining the third vertex according to the distance comparison to form a triangular patch. The bounding box method is used for optimization processing, including calculating the center position and side length of the bounding box, mapping the points to the standardized area through translation and scaling, and finally performing the inverse transformation to restore the original position.

[0124] It should also be noted that the vertex coordinates of the upper and lower layers of contours obtained by clockwise scanning are respectively read into two arrays a[M] and b[N], where M and N respectively represent the total number of vertices of the two layers of contour lines. Select a point b[j] in the lower-layer contour vertex array b[N] as the starting point, calculate the distances from each point in the upper-layer contour vertex array a[M] to b[j], and select the point closest to b[j]. Suppose it is a[i], then b[j] and a[i] are the two vertices of the reconstructed triangular patch, and let bBegin = j and aBegin = i;

[0125] Calculate the distances D1 between the contour vertices b[j] and a[i + 1], and D2 between the contour vertices a[i] and b[j + 1] respectively;

[0126] Then make a comparison. If D1 < D2, the third vertex of the triangular patch is a[i + 1], forming the triangular patch △b[j]a[i]a[i + 1], and let i loop increment by 1; otherwise, the third vertex of the triangular patch is b[j + 1], then the triangular patch is △b[j]a[i]b[j + 1], and let j loop increment by 1;

[0127] Using the obtained 3 vertices, draw and reconstruct its corresponding triangular patch, and store the 3 vertices in the triangular patch vertex structure array t[K]. Loop and execute until one week around all contour vertices (that is, when j is equal to bBegin and i is equal to aBegin), and finally complete the reconstruction of the three-dimensional surface model between adjacent two layers of contour lines;

[0128] Due to the complex structure of the underground cavity, it may cause large differences in the shapes of some adjacent cross-section (layer) contour lines and a large distance between the center points. To prevent the splicing failure of adjacent layer contour lines;

[0129] Preferably, the bounding box method can also be used in the foregoing steps to optimize its method. The steps are as follows: Define a bounding box for each of the adjacent two layers of contour lines, and calculate the center position of the bounding box respectively and the side length of the bounding box (Δx, Δy, and the calculation formula is:

[0130]

[0131] where n is the number of contour line vertices;

[0132] Using the following mapping formula, the points in a[M] and b[N] are mapped to the unit square bounding box centered at (0, 0) by translation and scaling to form a'[M] and b'[N]:

[0133]

[0134] The transformed two adjacent layers of contour lines a'[M] and b'[N] are connected by triangles using the shortest diagonal method to form a triangle vertex structure array t'[K]. Finally, an inverse transformation is performed to transform each contour vertex to its original position to generate the final triangle vertex structure array t[K].

[0135] S5, fuses all local surface models to construct the complete three-dimensional shape of the target space.

[0136] In an embodiment of the present application, the fusing of all local surface models includes:

[0137] The generated local surface models are used to establish a model sequence according to the spatial adjacent relationship;

[0138] Matching and aligning the boundaries of adjacent local surface models, and using the matching results to determine connection parameters;

[0139] Perform boundary transition processing on the local surface model with connection relationship and smooth the transition area;

[0140] The processed local surface models are fused sequentially, and the fusion results are constructed into a complete spatial morphological model.

[0141] Furthermore, the layer-by-layer cumulative 3D modeling includes cyclically executing steps S3 and S4, continuously integrating the newly generated 3D surface model between two adjacent layers of contour lines into the previous 3D model until the last scanning section, and finally generating an overall 3D surface model of the underground cavity.

[0142] It should be noted that the subsequent processing after the modeling is completed includes: saving the two-dimensional scanning data and the constructed three-dimensional model results to the ground host memory; turning off the power of the equipment according to the instruction manual, disconnecting all connections between components, and sorting and organizing them; copying the data from the ground host, and using computer-side processing software for comprehensive processing, including surface smoothing of the three-dimensional model of the underground cavity, observing the three-dimensional model of the underground cavity from different perspectives, and calculating the volume of the underground cavity.

[0143] Furthermore, this embodiment also provides a system for scanning and reconstructing the three-dimensional morphology of underground cavities, comprising:

[0144] Equipment deployment module, parameter configuration module, data acquisition module, reconstruction processing module, model building module;

[0145] The device deployment module is used to deploy the detection device to the target space location, establish a detection system communication connection, and perform a device connection test;

[0146] The parameter configuration module is used to set detection area parameters and sampling parameters, generate scanning section layout plans, and configure system operation parameters;

[0147] The data acquisition module is used to control the detection device to perform spatial profile data acquisition, obtain multi-layer spatial profile data sets, and monitor the acquisition process;

[0148] The reconstruction processing module is used to perform standardization processing on the collected contour data, reconstruct the spatial connection structure between adjacent sampling layers, and generate a local surface model;

[0149] The model building module is used to optimize the local surface model, establish the inter-layer transition relationship, fuse all the local surface models, and build a complete three-dimensional shape of the target space.

[0150] This embodiment also provides a computer device suitable for the method of scanning and reconstructing the three-dimensional morphology of underground cavities, including a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the method of scanning and reconstructing the three-dimensional morphology of underground cavities as proposed in the above embodiment.

[0151] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0152] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for scanning and reconstructing the three-dimensional morphology of underground cavities proposed in the above embodiment is implemented.

[0153] In summary, the underground cavity three-dimensional morphological scanning and reconstruction method provided by the present invention breaks through the limitations of traditional drilling detection by deploying multi-sensor integrated detection equipment and establishing real-time communication connections, realizes all-round perception of the underground cavity environment and stable data transmission, and lays a hardware foundation for high-quality three-dimensional reconstruction; by scientifically setting detection parameters and layered sampling strategies, the optimal balance between sampling accuracy and efficiency is achieved, a standardized data acquisition scheme is established, and the integrity and representativeness of the data are ensured; through the automated rotation scanning and interlayer displacement of the detection equipment, the data acquisition efficiency is significantly improved, continuous and complete spatial contour data are obtained, and the problem of low efficiency of traditional point measurement methods is solved; by innovatively combining the shortest diagonal method and the bounding box method for spatial reconstruction, the problem of large differences in contours of adjacent layers in complex underground cavities is effectively overcome, and high-precision local surface reconstruction is achieved; through the steps of model sequence establishment, boundary matching and transition processing, the seamless fusion of local models is achieved, the computational complexity of large cavity modeling is reduced, and the continuity and authenticity of the overall model are guaranteed. The present invention has made significant progress in detection efficiency, reconstruction accuracy and application reliability.

[0154] Example 3

[0155] This is the third embodiment of the present invention. This embodiment provides a method for scanning and reconstructing the three-dimensional morphology of underground cavities. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0156] In order to verify the actual effect of the method of the present invention, a detection test was carried out in an underground goaf of a large mining area. The test area is an irregular goaf with a depth of 15-45 meters, a maximum horizontal span of about 30 meters, and a vertical length of about 40 meters. The test adopted the scanning reconstruction method of the present invention and compared it with the traditional drilling geophysical method and the single laser ranging method.

[0157] The test equipment includes: an integrated detection system (equipped with a high-precision laser rangefinder, sonar detector, 3D electronic compass and infrared imaging system), an industrial-grade portable host (equipped with an Intel i7-12700 processor and 32GB RAM), and an intelligent winch system (maximum lifting force 2000N, positioning accuracy ±1mm). The test was carried out in three areas, with 5 drill holes in each area, and the diameter of the drill holes was 150mm.

[0158] The specific implementation process is as follows: First, perform equipment calibration and communication testing to ensure data transmission stability. Adopt the adaptive parameter configuration method, and set the scanning layer spacing to 80-150mm (80mm in complex areas and 150mm in regular areas) according to the preliminary detection results. The number of sampling points per layer is dynamically adjusted between 200-500 points, and the sampling frequency is 10Hz. To improve data quality, perform three repeated measurements at each sampling point and take the average value. The probe rotation speed is set to 6° / s to ensure stable sampling.

[0159] In the data processing stage, the improved shortest diagonal method and bounding box method were used for spatial reconstruction. Through adaptive meshing technology, the mesh density in complex areas was increased to 20 mm, and the mesh density in regular areas was increased to 50 mm. The model fusion used overlapping area registration technology, and the overlapping area was set to 15% of the adjacent area. The entire experiment lasted for 5 days, and a total of about 250,000 valid data points were collected.

[0160] The test data and analysis results are shown in the following table:

[0161]

[0162] The following conclusions can be drawn from the analysis of the test data:

[0163] Model accuracy: The model accuracy of the method of the present invention (A1-A3 area) reaches ±30-35mm, which is about 80% higher than the ±150mm of the traditional drilling geophysical exploration method and about 60% higher than the ±80mm of the single laser scanning method. This significant improvement in accuracy is mainly due to the application of multi-sensor fusion and adaptive sampling strategies.

[0164] In terms of time efficiency: the method of the present invention only takes 24-26 hours to complete the detection and modeling of an area, while the traditional method takes 72 hours and a single laser scan takes 48 hours. The efficiency improvement mainly comes from the improvement of automation and the application of intelligent parameter configuration. In particular, the design of adaptive layer spacing and dynamic sampling point density significantly reduces the collection of redundant data while ensuring accuracy.

[0165] Coverage and data integrity: The method of the present invention achieved a spatial coverage of more than 97.8% in all three test areas, while the traditional method was only 85.5% and the single laser scan was 91.2%. At the same time, the number of data points of the method of the present invention reached more than 80,000 points, far exceeding other methods, which ensured the detail restoration of the model reconstruction.

[0166] Error rate control: The error rate of the method of the present invention is controlled below 1.2%, which is significantly lower than the 7.8% of the traditional method and the 4.5% of a single laser scan. This is mainly due to the application of multiple repeated measurements and automated data verification mechanisms.

[0167] From the perspective of engineering application, the method of the present invention not only achieves comprehensive improvement in technical indicators, but also shows obvious advantages in practical operability and reliability. Especially under complex terrain conditions, through adaptive parameter configuration and multi-sensor fusion technology, the detection blind spot problem of traditional methods in irregular spatial areas is successfully solved. In addition, the method of the present invention has a high degree of automation, which greatly reduces the errors caused by manual operation and improves work efficiency and safety.

[0168] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for scanning and reconstructing the three-dimensional morphology of underground cavities, characterized by: include, Deploy detection equipment to the target space location and establish communication connection with the detection system; Set detection area parameters and sampling parameters, and determine the spatial scanning strategy; Perform spatial contour data collection to obtain multi-layer spatial contour data sets; Reconstruct the spatial connection structure between adjacent sampling layers and generate a local surface model; All local surface models are fused to construct a complete three-dimensional shape of the target space.

2. The method for scanning and reconstructing the three-dimensional morphology of underground cavities according to claim 1, characterized in that: The setting of detection area parameters and sampling parameters includes: Dividing the target detection space into a plurality of parallel scanning layers, and setting the spacing between adjacent scanning layers to a predetermined distance value; The sampling resolution of each scanning layer is set to a preset number of points, and the sampling points are evenly distributed along the circumference of the scanning layer; Set the starting depth and ending depth of the detection area to the scanning range boundary value; Set the system operating parameters to standard parameter values ​​under the predetermined working mode.

3. The method for scanning and reconstructing the three-dimensional morphology of underground cavities according to claim 2, characterized in that: The execution of spatial profile data collection comprises: Position the detection device to a preset scanning starting point, and determine the current position as the initial sampling layer position; The detection device is rotated circumferentially at a predetermined rate, and coordinate data of the spatial contour points are obtained during the rotation process; Move the detection device to the next sampling layer position, wherein the distance between adjacent sampling layers is a preset spacing value; The circumferential scanning and inter-layer movement process is executed in a loop until data collection of the entire detection area is completed.

4. The method for scanning and reconstructing the three-dimensional morphology of underground cavities according to claim 3, characterized in that: The reconstructing the spatial connection structure between adjacent sampling layers comprises: Inputting the spatial contour data of two adjacent layers into a reconstruction processing unit, and converting the data into a unified coordinate system; Perform spatial standardization on the converted contour data and store the processing results in a data buffer area; Establishing a spatial mapping relationship for the standardized contour data, and using the mapping result to determine the connection point pairs; The determined connection point pairs are constructed into local surface elements, and the surface elements are subjected to quality assessment.

5. The method for scanning and reconstructing the three-dimensional morphology of underground cavities according to claim 4, characterized in that: The fusion of all local surface models includes: The generated local surface models are used to establish a model sequence according to the spatial adjacent relationship; Matching and aligning the boundaries of adjacent local surface models, and using the matching results to determine connection parameters; Perform boundary transition processing on the local surface model with connection relationship and smooth the transition area; The processed local surface models are fused sequentially, and the fusion results are constructed into a complete spatial morphological model.

6. The method for scanning and reconstructing the three-dimensional morphology of underground cavities according to claim 5, characterized in that: The specific steps of the data standardization process include: Match two adjacent layers of contour lines with a bounding box respectively, and use the geometric feature parameters of the bounding box as a standardized benchmark; The center position (x, y) of the bounding box of the adjacent layer contour line is determined by the following calculation formula: The side lengths (Δx, Δy) of the bounding boxes of the contour lines of the adjacent layers are determined by the following calculation formula: The original contour point coordinates are transformed to the standardized area through the following mapping formula: Map the transformed coordinate point to the unit square bounding box centered at (0, 0); Verify the topological relationship and check the data integrity of the standardized contour points; The verified standardized data is used as input data for subsequent reconstruction processing.

7. The method for scanning and reconstructing the three-dimensional morphology of underground cavities according to claim 6, characterized in that: The specific steps of establishing the inter-layer transition relationship include: The standardized adjacent layer contour point data are respectively stored in arrays a[M] and b[N], and sorted in the clockwise direction; Select the initial connection point b[j] from the lower layer contour point array b[N], and calculate the spatial distances between it and each point in the upper layer contour point array a[M]; Determine the upper layer point a[i] with the closest distance as the corresponding connection point, and record the index values of the initial connection point pair bBegin = j, aBegin = i; Determine the connection path between the current connection point pair b[j] and a[i] through the following steps: Calculate the distance parameters D1 = |b[j] - a[i + 1]| and D2 = |a[i] - b[j + 1]|; When D1 < D2, generate the triangular patch △b[j]a[i]a[i + 1], and increment the index i by 1 in a loop; When D1 ≥ D2, generate the triangular patch △b[j]a[i]b[j + 1], and increment the index j by 1 in a loop; Record the generated triangular patches into the structure array until one contour loop is completed, that is, j = bBegin and i = aBegin; Perform the following optimization processing on the generated set of triangular patches: Check the direction consistency of the triangular patches; Optimize the shape quality of the triangular patches; Adjust the connection transition of the triangular patches; Use the optimized set of triangular patches as the transition connection structure between adjacent layers.

8. A system for scanning and reconstructing the three-dimensional morphology of underground cavities, based on the method for scanning and reconstructing the three-dimensional morphology of underground cavities according to any one of claims 1 to 7, characterized in that: It also includes a device deployment module, a parameter configuration module, a data acquisition module, a reconstruction processing module, and a model construction module; The device deployment module is used to deploy the detection device to the target space position, establish the communication connection of the detection system, and perform device connection testing; The parameter configuration module is used to set the detection area parameters and sampling parameters, generate the scanning section layout plan, and configure the system operation parameters; The data acquisition module is used to control the detection device to perform spatial contour data acquisition, obtain multi-layer spatial contour data sets, and monitor the acquisition process; The reconstruction processing module is used to perform standardized processing on the acquired contour data, reconstruct the spatial connection structure between adjacent sampling layers, and generate a local surface model; The model construction module is used to perform optimization processing on the local surface model, establish the inter-layer transition relationship, fuse all local surface models, and construct the complete three-dimensional form of the target space.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, it implements the steps of the method for scanning and reconstructing the three-dimensional form of the underground cavity according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the method for scanning and reconstructing the three-dimensional form of the underground cavity according to any one of claims 1 to 7.

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