CN109993832B - Method for constructing refined three-dimensional model of fully mechanized coal mining face coal seam - Google Patents
Method for constructing refined three-dimensional model of fully mechanized coal mining face coal seam Download PDFInfo
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Abstract
The invention discloses a method for constructing a fine three-dimensional model of a fully mechanized coal mining face coal seam, and belongs to the technical field of coal mine unmanned mining. And comprehensively utilizing coal seam seismic wave detection data, roadway laser scanning data, underground drilling sampling data and coal mine well building data to build a coal seam refined three-dimensional model of the fully mechanized coal mining face. The construction method comprises the following steps: (1) acquiring geological data of a fully mechanized mining face to be mined and optimizing the geological data; (2) respectively constructing a refined triangular net of a coal seam, a fault/fold and a roadway; (3) calculating the topological relation among the triangular networks and carrying out association analysis on the topological relation so as to realize seamless fusion among the triangular networks; (4) and verifying the fused triangulation network, and constructing a coal seam refined three-dimensional model of the fully mechanized coal mining face. The advantages are that: the method can quickly and effectively establish a refined three-dimensional model of the coal bed of the working face, obtain high-precision coal bed information and provide accurate coal bed data for unmanned mining of the fully mechanized working face.
Description
Technical Field
The invention relates to a method for constructing a fine three-dimensional model of a fully mechanized coal mining face coal seam, and belongs to the technical field of coal mine unmanned mining.
Background
The coal mine unmanned mining is a leading-edge technology commonly pursued in the international coal mining field, is an important means for reducing casualties and guaranteeing safe production, and is an effective way for realizing safe, efficient and green mining of coal mines in China. At present, the main technical bottleneck for restricting the underground unmanned mining of coal mines is coal rock interface identification, from the sixty years of the last century, twenty different coal rock identification methods such as a gamma ray method, a radioactive isotope method, a radar detection method, a stress cutting tooth analysis method, an infrared thermal imaging method, an ultrasonic method, a high-pressure water jet method, a multi-sensor fusion method and the like are successively proposed in main coal producing countries (British, America, Australia, China, the front Soviet Union and the like) in the world, however, the existing coal rock identification technology is not applied to a fully mechanized caving face due to the complexity of the coal rock interface, the severe environment of the fully mechanized face and the like.
At present, the height of a roller of a coal mining machine can be adjusted by combining memory cutting and manual remote intervention on a fully mechanized mining face with relatively simple geological conditions, and automatic coal cutting is realized, but the geological conditions of most fully mechanized mining faces in China are very complicated (such as large fluctuation change of coal seams, dangerous geological structures such as faults and folds and the like exist), so that the automatic height adjustment control method of the coal mining machine based on the memory cutting is similar to 'blind feeling', only the coal cutting track of the previous cut is memorized, the information of the next cut coal seam is unknown, and the method cannot be suitable for the fully mechanized mining face with a complicated coal seam structure. Therefore, research on a coal seam refined three-dimensional modeling method capable of providing accurate coal seam information for a coal mining machine is urgently needed, interactive perception of the coal mining machine and a coal seam three-dimensional model is achieved, and the method is a key technology for unmanned mining of a fully mechanized mining face.
Disclosure of Invention
The technical problem is as follows: the invention aims to overcome the defects in the prior art and provides the method for constructing the coal seam refined three-dimensional model of the fully mechanized coal mining face, which can adapt to the fully mechanized coal mining face with a complex coal seam structure, quickly obtain high-precision coal seam information and provide accurate coal seam data for unmanned mining of the fully mechanized coal mining face.
The technical scheme is as follows: in order to achieve the purpose, the method for constructing the coal seam refined three-dimensional model of the fully mechanized coal mining face comprehensively utilizes coal seam seismic wave detection data, roadway laser scanning data, underground drilling sampling data and coal mine well construction data to construct the coal seam refined three-dimensional model of the fully mechanized coal mining face, and comprises the following specific steps:
(1) acquiring geological data of a fully mechanized mining face to be mined, and optimizing the geological data of the fully mechanized mining face; the geological data comprises: coal seam seismic wave detection data, roadway laser scanning data, underground drilling sampling data and coal mine well building data, wherein the coal mine well building data comprise bottom plate contour line data and fault/fold data;
(2) constructing a coal seam refined triangulation network, a fault/fold refined triangulation network and a stoping roadway refined triangulation network of the fully mechanized mining face;
(3) calculating the topological relation among the constructed coal bed triangulation network, the constructed fault/fold triangulation network and the constructed roadway triangulation network, sequentially embedding the fault/fold and the constructed roadway triangulation network into the coal bed triangulation network by utilizing a grid index method, enabling the fault/fold triangulation network and the constructed roadway triangulation network to become a local constraint area in the coal bed triangulation network, and optimizing and improving the local constraint area by adopting a constraint polygon embedding algorithm to realize seamless fusion among the coal bed refinement triangulation network, the fault/fold refinement triangulation network and the stoping roadway refinement triangulation network;
(4) and checking a refined triangulation network of the fused coal seam, fault/fold and stoping roadway, constructing the triangulation network again when the fusion precision is not met, continuing to perform smooth transition treatment on the triangulation network when the fusion precision is met, and completing construction of a refined three-dimensional model of the coal seam of the fully mechanized mining face.
The optimization processing in the step 1 comprises the following steps: and removing noise points by adopting a chord height difference method, carrying out smooth filtering by adopting an average filtering method, and carrying out data repair by adopting cubic spline interpolation.
The step 2 of constructing a coal seam refinement triangulation network comprises the following steps:
firstly, reading coal seam seismic wave detection data, combining high-line data of a bottom plate according to detected coal seam boundary constraint information, and realizing triangular mesh division of a top bottom plate of a coal seam by using a method of combining a regular grid and an irregular triangular mesh;
introducing regular virtual drilling data to interpolate triangulation network nodes of the space of the coal seam top and bottom plate according to a space statistical analysis method and a kriging method, and repeatedly utilizing the kriging method to perform triangulation interpolation on regions which are not triangulated;
and embedding vertexes and triangular edges on the triangular net template to construct a fine triangular net of the fully mechanized coal mining face coal bed.
The step of constructing a fault/wrinkle refined triangulation network in the step 2 comprises the following steps:
firstly, reading fault/fold data, coal bed seismic wave detection data, underground drilling sampling data and bottom plate high-line data, then obtaining a top plate cross line and a bottom plate cross line of the fault/fold from a bottom plate high-line map in sequence, and projecting the top plate cross line and the bottom plate cross line onto a triangular grid template;
embedding the upper disc cross-hatching and the lower disc cross-hatching of the fault/fold and the stratum as constraint conditions into a triangular mesh template, and forming a coal bed surface triangular mesh without height information and containing partial fault/fold surfaces through a constraint triangulation algorithm;
thirdly, partitioning the coal bed by taking the boundary line of the triangular net of the coal bed surface and the fault/fold line as boundaries;
fourthly, performing elevation interpolation on the vertex on each partition of the triangular net of the coal seam/wrinkled surface according to a certain rule and algorithm;
triangularization is carried out on the non-triangulated area on the fault/fold surface according to a Krigin method, then the vertex and the triangular edge on a triangular net template are embedded, the fault/fold surface triangular net is further refined, and the height interpolation is carried out on the vertex inside the fault/fold surface triangular net, so that the fault/fold refined triangular net of the fully mechanized mining face is constructed.
In the step 2, the step of constructing the roadway refinement triangulation network comprises the following steps:
firstly, reading three-dimensional point cloud data of a laser scanning roadway, and calculating barycentric coordinates and density of the point cloud data;
performing grid processing on the point cloud data by adopting a quadtree algorithm to construct a first base edge, setting a distance threshold and a search range by taking any point of the point cloud data as a starting point, and searching a closest point to construct a second base edge;
and thirdly, constructing a first triangle, judging the direction of the normal vector of the triangle according to the normal vector of the triangle and the included angle between the gravity center point and the vector of a certain vertex of the triangle, taking 90 degrees as a threshold value, and pointing to the outside if the included angle is less than 90 degrees, so that the requirement is met. Otherwise, pointing to the inside, failing to meet the requirement, and searching again;
fourthly, after the first triangle is constructed, searching a third point, forming a new triangle by the third point and the nearest side, calculating the included angle of the normal vector of the previous triangle and the new triangle, if the included angle is smaller than 90 degrees, meeting the requirement, finally selecting the best point by adopting a maximum included angle method, if the included angle is larger than 90 degrees, abandoning and continuing searching;
and fifthly, optimizing the constructed triangulation network to complete construction of the roadway fine triangulation network.
Has the advantages that: the method can adapt to the fully mechanized coal mining face with a complex coal seam structure, quickly obtain high-precision coal seam information and provide accurate coal seam data for unmanned mining of the fully mechanized coal mining face. Compared with the prior art, the method has the following advantages:
(1) the method for acquiring the modeling data is simple and the acquired measured data is accurate, and the data comprises the following steps: coal seam seismic wave detection data, roadway laser scanning data, underground drilling sampling data and coal mine well construction data (floor contour data and fault fold data).
(2) The modeling method provided by the invention can quickly and effectively establish a fine three-dimensional model of the coal bed of the fully mechanized coal mining face, can effectively ensure the accuracy and reliability of the established model, can avoid the difficult problem of coal rock identification, solves the problem of accurate coal cutting of a coal mining machine by a new method, and provides accurate coal bed data for unmanned mining of the fully mechanized coal mining face.
Drawings
FIG. 1 is a flow chart of the construction of a refined three-dimensional model of a fully mechanized coal mining face coal seam.
FIG. 2 is a three-dimensional model of a fully mechanized coal mining face coal seam refinement established by the present invention.
Detailed Description
The invention will be further described with reference to examples in the drawings to which:
as shown in fig. 1, the method for constructing the refined three-dimensional model of the fully mechanized coal mining face coal seam comprehensively utilizes data such as coal mine well construction data, coal seam seismic wave CT detection, laser scanning roadway model, roadway exploration drilling and the like to construct the refined three-dimensional model of the fully mechanized coal mining face coal seam, and comprises the following specific steps:
(1) acquiring geological data of a fully mechanized mining face to be mined, and optimizing the geological data, wherein the geological data comprises: coal seam seismic wave detection data, roadway laser scanning data, underground drilling sampling data and coal mine well building data, wherein the coal mine well building data comprise bottom plate contour line data and fault wrinkle data;
the optimization process comprises the following steps: removing noise points by adopting a chord height difference method, carrying out smooth filtering by adopting an average filtering method, and carrying out data repair by adopting cubic spline interpolation;
(2) constructing a coal seam refined triangulation network, a fault/fold refined triangulation network and a stoping roadway refined triangulation network of the fully mechanized mining face;
the step of constructing the coal seam refined triangulation network of the fully mechanized coal mining face comprises the following steps:
firstly, reading coal seam seismic wave detection data, combining floor contour line data according to detected coal seam boundary constraint information, and realizing triangular mesh division of a coal seam top floor by using a method of combining a regular grid and an irregular triangular mesh;
introducing regular virtual drilling data to interpolate triangulation network nodes of the space of the coal seam top and bottom plate according to a space statistical analysis method and a kriging method, and repeatedly utilizing the kriging method to perform triangulation interpolation on regions which are not triangulated;
and embedding vertexes and triangular edges on the triangular net template to construct a fine triangular net of the fully mechanized coal mining face coal bed.
The step of constructing the fault/fold refined triangular net comprises the following steps:
firstly, reading fault/fold data, coal bed seismic wave detection data, underground drilling sampling data and bottom plate contour line data, then obtaining an upper disc intersection line and a lower disc intersection line of the fault/fold from a bottom plate contour line graph in sequence, and projecting the upper disc intersection line and the lower disc intersection line onto a triangular grid template;
embedding the upper disc cross-hatching and the lower disc cross-hatching of the fault/fold and the stratum as constraint conditions into a triangular mesh template, and forming a coal bed surface triangular mesh without height information and containing partial fault/fold surfaces through a constraint triangulation algorithm;
thirdly, partitioning the coal bed by taking the boundary line of the triangular net of the coal bed surface and the fault/fold line as boundaries;
fourthly, performing elevation interpolation on the vertex on each partition of the triangular net of the coal seam/wrinkled surface according to a certain rule and algorithm;
triangularization is carried out on the non-triangulated area on the fault/fold surface according to a Krigin method, then the vertex and the triangular edge on a triangular net template are embedded, the fault/fold surface triangular net is further refined, and the height interpolation is carried out on the vertex inside the fault/fold surface triangular net, so that the fault/fold refined triangular net of the fully mechanized mining face is constructed.
The step of constructing the roadway refinement triangulation network comprises the following steps:
reading three-dimensional point cloud data of the laser scanning roadway, and calculating barycentric coordinates and density of the point cloud data;
performing grid processing on the point cloud data by adopting a quadtree algorithm to construct a first base edge, setting a distance threshold and a search range by taking any point of the point cloud data as a starting point, and searching a closest point to construct a second base edge;
and thirdly, constructing a first triangle, judging the direction of the normal vector of the triangle according to the normal vector of the triangle and the included angle between the gravity center point and the vector of a certain vertex of the triangle, taking 90 degrees as a threshold value, and pointing to the outside if the included angle is less than 90 degrees, so that the requirement is met. Otherwise, pointing to the inside, failing to meet the requirement, and searching again;
fourthly, after the first triangle is constructed, searching a third point, forming a new triangle by the third point and the nearest side, calculating the included angle of the normal vector of the previous triangle and the new triangle, if the included angle is smaller than 90 degrees, meeting the requirement, finally selecting the best point by adopting a maximum included angle method, if the included angle is larger than 90 degrees, abandoning and continuing searching;
and fifthly, optimizing the constructed triangulation network to complete construction of the roadway fine triangulation network.
(3) Calculating the topological relation among the constructed coal bed triangulation network, the constructed fault/fold triangulation network and the constructed tunnel triangulation network, sequentially embedding the fault/fold and the constructed tunnel triangulation network into the coal bed triangulation network by utilizing a grid index method, enabling the fault/fold triangulation network and the constructed tunnel triangulation network to become a local constraint area in the coal bed triangulation network, and optimizing and improving the fault/fold triangulation network and the constructed tunnel triangulation network by utilizing a constraint polygon embedding algorithm to realize seamless fusion among the coal bed triangulation network, the fault/fold triangulation network and the constructed tunnel triangulation network;
(4) and checking the fused refined triangulation network, reconstructing the triangulation network which does not meet the fusion precision, continuing performing smooth transition processing on the triangulation network when the fusion precision is met, and finally establishing a fully mechanized coal mining face coal seam refined three-dimensional model as shown in fig. 2.
Claims (5)
1. A method for constructing a coal seam refined three-dimensional model of a fully mechanized coal mining face is characterized by comprising the following steps: synthesize and utilize coal seam seismic wave survey data, tunnel laser scanning data, drilling sample data and colliery well construction data in the pit, construct and combine and adopt working face coal seam three-dimensional model that becomes more meticulous, concrete step includes:
(1) acquiring geological data of a fully mechanized mining face to be mined, and optimizing the geological data of the fully mechanized mining face; the geological data comprises: coal seam seismic wave detection data, roadway laser scanning data, underground drilling sampling data and coal mine well building data, wherein the coal mine well building data comprise bottom plate contour line data and fault/fold data;
(2) constructing a coal seam refined triangulation network, a fault/fold refined triangulation network and a stoping roadway refined triangulation network of the fully mechanized mining face;
(3) calculating the topological relation among the constructed coal bed triangulation network, the constructed fault/fold triangulation network and the constructed roadway triangulation network, sequentially embedding the fault/fold and the constructed roadway triangulation network into the coal bed triangulation network by utilizing a grid index method, enabling the fault/fold triangulation network and the constructed roadway triangulation network to become a local constraint area in the coal bed triangulation network, and optimizing and improving the local constraint area by adopting a constraint polygon embedding algorithm to realize seamless fusion among the coal bed refinement triangulation network, the fault/fold refinement triangulation network and the stoping roadway refinement triangulation network;
(4) and checking a refined triangulation network of the fused coal seam, fault/fold and stoping roadway, constructing the triangulation network again when the fusion precision is not met, continuing to perform smooth transition treatment on the triangulation network when the fusion precision is met, and completing construction of a refined three-dimensional model of the coal seam of the fully mechanized mining face.
2. The method for constructing the coal seam refined three-dimensional model of the fully mechanized mining face of claim 1, wherein: the optimization processing in the step (1) comprises the following steps: and removing noise points by adopting a chord height difference method, carrying out smooth filtering by adopting an average filtering method, and carrying out data repair by adopting cubic spline interpolation.
3. The method for constructing the coal seam refined three-dimensional model of the fully mechanized mining face of claim 1, wherein: the step of constructing the coal seam refinement triangulation network in the step (2) comprises the following steps:
firstly, reading coal seam seismic wave detection data, combining high-line data of a bottom plate according to detected coal seam boundary constraint information, and realizing triangular mesh division of a top bottom plate of a coal seam by using a method of combining a regular grid and an irregular triangular mesh;
introducing regular virtual drilling data to interpolate triangulation network nodes of the space of the coal seam top and bottom plate according to a space statistical analysis method and a kriging method, and repeatedly utilizing the kriging method to perform triangulation interpolation on regions which are not triangulated;
and embedding vertexes and triangular edges on the triangular net template to construct a fine triangular net of the fully mechanized coal mining face coal bed.
4. The method for constructing the coal seam refined three-dimensional model of the fully mechanized mining face of claim 1, wherein: the step of constructing a fault/wrinkle refined triangulation network in the step (2) comprises the following steps:
firstly, reading fault/fold data, coal bed seismic wave detection data, underground drilling sampling data and bottom plate high-line data, then obtaining a top plate cross line and a bottom plate cross line of the fault/fold from a bottom plate high-line map in sequence, and projecting the top plate cross line and the bottom plate cross line onto a triangular grid template;
embedding the upper disc cross-hatching and the lower disc cross-hatching of the fault/fold and the stratum as constraint conditions into a triangular mesh template, and forming a coal bed surface triangular mesh without height information and containing partial fault/fold surfaces through a constraint triangulation algorithm;
thirdly, partitioning the coal bed by taking the boundary line of the triangular net of the coal bed surface and the fault/fold line as boundaries;
fourthly, performing elevation interpolation on the vertex on each partition of the triangular net of the coal seam/wrinkled surface according to a certain rule and algorithm;
triangularization is carried out on the non-triangulated area on the fault/fold surface according to a Krigin method, then the vertex and the triangular edge on a triangular net template are embedded, the fault/fold surface triangular net is further refined, and the height interpolation is carried out on the vertex inside the fault/fold surface triangular net, so that the fault/fold refined triangular net of the fully mechanized mining face is constructed.
5. The method for constructing the coal seam refined three-dimensional model of the fully mechanized mining face according to claim 1, characterized in that: in the step (2), the step of constructing the roadway refinement triangulation network comprises the following steps:
firstly, reading three-dimensional point cloud data of a laser scanning roadway, and calculating barycentric coordinates and density of the point cloud data;
performing grid processing on the point cloud data by adopting a quadtree algorithm to construct a first base edge, setting a distance threshold and a search range by taking any point of the point cloud data as a starting point, and searching a closest point to construct a second base edge;
constructing a first triangle, judging the direction of a normal vector of the triangle according to the normal vector of the triangle and the included angle between the gravity center point and a vector at a certain vertex of the triangle, taking 90 degrees as a threshold value, if the included angle is less than 90 degrees, pointing to the outside to meet the requirement, otherwise, pointing to the inside to not meet the requirement, and searching again;
fourthly, after the first triangle is constructed, searching a third point, forming a new triangle by the third point and the nearest side, calculating the included angle of the normal vector of the previous triangle and the new triangle, if the included angle is smaller than 90 degrees, meeting the requirement, finally selecting the best point by adopting a maximum included angle method, if the included angle is larger than 90 degrees, abandoning and continuing searching;
and fifthly, optimizing the constructed triangulation network to complete construction of the roadway fine triangulation network.
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| CN111127644B (en) * | 2019-12-12 | 2021-03-02 | 北京龙软科技股份有限公司 | Method and device for drawing coal seam thickness contour line of open pit coal mine |
| CN111311747B (en) * | 2020-01-17 | 2022-02-11 | 中国水利水电科学研究院 | Multi-sensor barrier lake region integrated three-dimensional model rapid construction method |
| CN112258603B (en) * | 2020-10-30 | 2021-09-21 | 西南石油大学 | Three-axis layout drawing method for analyzing rule of three-factor composite influence and application thereof |
| CN113341422B (en) * | 2021-06-23 | 2024-05-24 | 重庆工程职业技术学院 | Tunneling support method based on position sensing system of tunneling and anchoring machine |
| CN113486817B (en) * | 2021-07-09 | 2023-09-08 | 中国矿业大学 | Coal face coal rock identification method based on laser scanning |
| CN113962008A (en) * | 2021-11-09 | 2022-01-21 | 华北科技学院(中国煤矿安全技术培训中心) | Method for generating three-dimensional mine roadway model and constructing transparent working surface |
| CN114330078B (en) * | 2022-01-12 | 2023-03-24 | 煤炭科学研究总院有限公司 | Construction method of accurate numerical simulation model of mine coal face |
| CN114997482A (en) * | 2022-05-24 | 2022-09-02 | 徐州大屯工程咨询有限公司 | Coal mine underground working face digital transparent geological technical method |
| CN116152461B (en) * | 2023-04-21 | 2023-07-18 | 北京星天地信息科技有限公司 | Geological modeling method, device, computer equipment and computer readable storage medium |
| CN117671160B (en) * | 2024-01-30 | 2024-04-23 | 北京星天地信息科技有限公司 | Multi-source data collaborative coal seam modeling method, device, equipment and storage medium |
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