CN111272093B - Roadway deformation monitoring method - Google Patents
Roadway deformation monitoring method Download PDFInfo
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- CN111272093B CN111272093B CN202010203331.0A CN202010203331A CN111272093B CN 111272093 B CN111272093 B CN 111272093B CN 202010203331 A CN202010203331 A CN 202010203331A CN 111272093 B CN111272093 B CN 111272093B
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- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
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Abstract
A roadway deformation monitoring method comprises the steps of scanning a three-dimensional laser scanner fixed on the top of a roadway from left to right in a matrix mode from top to bottom, and preprocessing original point cloud data according to the quality and characteristics of data scanned for multiple times; extraction ofThe point data X, Y, Z of the first and the later fixed position roadway reference coordinate mark points are used for calculating the displacement X of the three-dimensional laser range finder in the coordinates by making a differenceo、Yo、Zo(ii) a Calibrating the coordinates of the three-dimensional laser scanner, i.e. converting the data cloud of the post-processed point data into [ X + X ]o、Y+Yo、Z+Zo]And subtracting the transformed point data from the data preprocessed for the first time to obtain the deformation amount around the roadway. The three-dimensional laser scanner is applied to automatic measurement under the coal mine for the first time, can scan the full section of the roadway, and can realize deformation data of all points of the roadway. The method has strong adaptability to environment and low cost.
Description
Technical Field
The invention relates to the field of mineral exploitation, relates to coal exploitation, and particularly relates to a roadway deformation monitoring method.
Background
Coal is a main one-time consumption energy source in China, and is concerned with the continuous development of national economy, large-scale mining and utilization of coal bring severe potential safety hazards while generating huge benefits, roadway deformation caused by surrounding rock stress change caused by mining causes increasingly serious accidents such as roof collapse, water inrush and sand inrush, gas outburst and the like, and the coal is a major potential hazard threatening mine safety.
At present, the main detection methods of roadway deformation are cross measurement, underground total station measurement and laser range finder measurement, and the measurement methods only aim at the statistics of the convergence of a certain point, cannot measure the convergence of all points, and simultaneously consume a large amount of labor. With the development of unmanned intelligence of few people in mines, the technology has obvious technical advantages in roadway monitoring.
Disclosure of Invention
In order to overcome the problems in the prior art, the invention aims to provide a roadway deformation monitoring method.
In order to achieve the purpose, the invention adopts the following technical scheme:
a roadway deformation monitoring method comprises the following steps:
1) scanning in a matrix form from top to bottom from left to right by adopting a three-dimensional laser scanner fixed at the top of the roadway to obtain scanning data;
2) preprocessing the original point cloud data according to the quality and the characteristics of the data scanned for multiple times;
3) storing the coordinates of the preprocessed point cloud data in a format of X, Y, Z; extracting the point data X, Y, Z of the first and the later fixed roadway reference coordinate mark points, and calculating the displacement X of the three-dimensional laser range finder in the coordinate point by making a differenceo、Yo、Zo(ii) a Calibrating three-dimensional laser scanner coordinates, i.e. converting point data cloud preprocessed after the first time into [ X + X ]o、Y+Yo、Z+Zo]And subtracting the transformed point data from the data preprocessed for the first time to obtain the deformation amount around the roadway.
A further improvement of the invention is that in step 1), the scan data comprises roadway coordinate point data.
The further improvement of the invention is that in the step 2), the pretreatment comprises point cloud data segmentation, point cloud data denoising and mixed point and error point removal.
The further improvement of the invention is that the specific process of point cloud data segmentation is as follows: and dividing the point cloud data according to the space, texture and geometric characteristics of the point cloud data to divide the point cloud data with similar characteristics or semantics together.
The further improvement of the invention is that the specific process of point cloud data denoising is as follows: and denoising the drift points, the isolated points and the redundant points in the point cloud data through 3D Reshaper software.
The invention further improves the method, and the specific process of removing the mixed points and the error points is as follows: and removing mixed points and error points in the point cloud data according to an iterative closest point algorithm.
The invention has the further improvement that the roadway reference coordinate mark point is set through the following processes: the method comprises the steps of firstly adopting a drill rod with the inner diameter of 300-350 mm to punch holes in a coal seam bottom plate to a stable bedrock, then putting a sleeve to the upper portion of the stable bedrock, performing wall protection, vertically arranging a steel rod in the center of the drilled hole, fixing the bottom end of the steel rod on the stable bedrock, and arranging a cross mark at the other end of the steel rod to serve as a reference coordinate mark point.
The drill rod is further improved in that the inner diameter of the drill rod is 300-350 mm, and the diameter of the sleeve is 280-330 mm.
The invention is further improved in that the sleeve is filled with foam, and the top of the sleeve is provided with an iron sheet cover.
The invention is further improved in that the height of the steel rod is 30-40 mm higher than that of the sleeve.
Compared with the prior art, the invention has the following beneficial effects:
1) the convergence of all points of the roadway can be measured. The three-dimensional laser scanner is applied to automatic measurement under a coal mine well for the first time, can scan the full section of a roadway, and can achieve deformation data of all points of the roadway compared with a common method.
2) Has strong adaptability to the environment. The method adopts laser scanning, does not need a light source, has serious deformation to the roadway, can accurately measure the area where people can not reach, and has good underground measuring effect.
3) The labor cost is reduced. The method does not need manual monitoring, the three-dimensional laser scanner can automatically set self real-time measurement, the measured data can be automatically stored, and the later extraction and the uniform processing are carried out. And the data can be subjected to three-dimensional modeling, and the deformation condition of the roadway can be analyzed and monitored. The invention has great advantages in the use of few unmanned intelligent coal mine working faces.
Further, stable coordinate points are provided. Because the periphery of the roadway is deformed under the coal mining disturbance, a stable coordinate point cannot be provided.
Drawings
FIG. 1 is a schematic view of a coordinate marker point arrangement according to the present invention;
reference numerals: 1-casing, 2-steel rod, 3-anchoring agent, 4-foam, 5-cross mark, 6-iron sheet cover, 7-interface of roadway and movable bedrock, and 8-interface of movable bedrock and stable bedrock.
Detailed Description
The present invention will be described in detail with reference to the accompanying drawings.
The invention comprises the following steps:
1) setting a roadway reference coordinate mark point:
referring to fig. 1, a roadway is arranged above an interface 7 of the roadway and the movable bedrock, the movable bedrock is arranged below the interface, the movable bedrock is arranged above an interface 8 of the movable bedrock and the stable bedrock, and the stable bedrock is arranged below the interface.
Firstly, drilling a hole in a roadway bottom plate by using a drill rod with the inner diameter of 300-350 mm until the lower part of an interface 8 of movable bedrock and stable bedrock is 240-300 mm, then putting a 280-330 mm sleeve 1 to the upper part of the interface 8 of the movable bedrock and stable bedrock for wall protection by 50-100 mm, wherein the middle part of the drilled hole adopts a non-deformable steel rod 2, the length of the steel rod 2 is determined by the position of the stable bedrock under the roadway and is generally 4-12 m, the bottom of the steel rod 2 is fixed at the lower part of the interface 8 of the movable bedrock and stable bedrock by adopting an anchoring agent 3, and the other end of the drilled hole is provided with a striking cross mark 5 as a mark, namely a reference coordinate mark point; the interior of the sleeve 1 is filled with foam (polyethylene foam PE)4, and the top of the sleeve 1 is covered with an iron sheet 6 to cover the opening. Wherein the sleeve 1 and the steel rod 2 are both 50-100 mm higher than the ground, and the height of the steel rod 2 is 30-40 mm higher than that of the sleeve.
2) The three-dimensional laser scanner is fixed on the fixer to the three-dimensional laser scanner outside is provided with dust cover, makes the three-dimensional laser scanner who is fixed in the tunnel top from left to right, and matrix scanning under the from top to bottom obtains the scanning data, and the scanning data is including the tunnel coordinate point data of establishhing, and the scanning data is deposited in the hard disk of equipment in real time. And extracting data scanned for multiple times from the hard disk, and importing the extracted data into the laika Infinity management software.
3) And performing necessary preprocessing on the original point cloud data according to the quality and the characteristics of the data scanned for multiple times, wherein the preprocessing comprises point cloud data segmentation, point cloud data denoising, mixed point removal and error point removal.
Point cloud data segmentation: and dividing the point cloud data according to the space, texture and geometric characteristics of the point cloud data to divide the point cloud data with similar characteristics or semantics together. In subsequent modeling scene understanding or reverse work, the method carries out various processes such as point cloud filtering, feature extraction, three-dimensional surface reconstruction and the like related to point cloud data of the same type.
Denoising point cloud data: denoising the drift points, the isolated points and the redundant points in the point cloud data by post-processing software (3D Reshaper) in a man-machine interaction mode.
Removing mixed points and error points: and removing mixed points and error points in the point cloud data according to a cloud data characteristic correlation algorithm (an iterative closest point algorithm (ICP) and a modified algorithm thereof).
4) And storing the preprocessed point cloud data coordinates into X, Y, Z. Extracting point data X, Y, Z of the reference coordinate mark points of the roadway for multiple times before and after the extraction, and calculating the displacement X of the three-dimensional laser range finder in the coordinate point by subtracting the point data of the reference coordinate mark points of the roadway for the first time and the second timeo、Yo、Zo. Calibrating the coordinates of the three-dimensional laser scanner, namely converting the data cloud of the first and later preprocessed point into [ X + X ]o、Y+Yo、Z+Zo]. And (4) subtracting the transformed point data from the data preprocessed for the first time to obtain the deformation amount around the roadway. For example, the point data X, Y, Z of the roadway reference coordinate mark point with fixed positions after the first time and the third time is extracted, and the displacement X of the three-dimensional laser range finder in the coordinate point is calculated by making a differenceo、Yo、Zo(ii) a Calibrating the three-dimensional laser scanner coordinates, i.e. converting the data cloud of the point preprocessed after the third time into [ X + X ]o、Y+Yo、Z+Zo]And subtracting the transformed point data from the data preprocessed for the first time to obtain the deformation amount around the roadway. The third time may be replaced with any one time after the first time.
Wherein X represents the X-direction coordinate from the scanner to the reference coordinate mark point, Y represents the Y-direction coordinate from the scanner to the reference coordinate mark point, Z represents the Z-direction coordinate from the scanner to the reference coordinate mark point, XoIndicating the amount of change, Y, in the X direction from the scanner to the reference coordinate mark pointoIndicating the amount of change, Z, in the Y direction from the scanner to the reference coordinate mark pointoAnd the Z-direction variation of the scanner to the reference coordinate marking point is represented.
And the calibrated cloud data and the first-time measurement cloud data can be subjected to three-dimensional modeling, and the deformation condition of the roadway is analyzed and monitored.
The invention improves the measuring range, can carry out three-dimensional scanning measurement on any part of the roadway, reduces the labor cost, enables the measurement to be simple and quick, has great advantages on the working face of few people and unmanned intelligent coal mines, and overcomes the problem of incomplete measuring range caused by only measuring one point in the prior art.
Claims (4)
1. A roadway deformation monitoring method is characterized by comprising the following steps:
1) scanning in a matrix form from top to bottom from left to right by adopting a three-dimensional laser scanner fixed at the top of the roadway to obtain scanning data;
2) preprocessing the original point cloud data according to the quality and the characteristics of the scanning data of multiple scanning;
3) storing the coordinates of the preprocessed point cloud data in a format of X, Y, Z; extracting X, Y, Z point cloud data coordinates of the first and later fixed tunnel reference coordinate mark points, and calculating the displacement X of the three-dimensional laser range finder in the coordinate points by making differenceo、Yo、Zo(ii) a The three-dimensional laser scanner coordinates are calibrated by the three-dimensional laser scanner fixed on the fixer, namely, the cloud conversion is carried out on the point cloud data preprocessed after the first time, and the point cloud data is converted into [ X + X ]o、Y+Yo、Z+Zo]The transformed point cloud data and the point cloud data preprocessed for the first time are subjected to subtraction to obtain deformation around the roadway; wherein, the roadway reference coordinate markThe points are set by the following procedure: firstly, drilling a hole in a coal seam bottom plate to a stable bedrock by adopting a drill rod with the inner diameter of 300-350 mm, then, putting a sleeve (1) to the upper part of the stable bedrock, performing wall protection, vertically arranging a steel rod (2) at the center of the drilled hole, fixing the bottom end of the steel rod (2) on the stable bedrock by adopting an anchoring agent 3, and arranging a cross mark (5) at the other end of the steel rod (2) to be used as a reference coordinate mark point;
the scanning data comprises roadway coordinate point cloud data;
polyethylene foam plastic is filled in the sleeve (1), and an iron sheet cover (6) is arranged at the top of the sleeve (1);
the diameter of the sleeve (1) is 280-330 mm, the sleeve (1) and the steel rod (2) are both 50-100 mm higher than the ground, and the height of the steel rod (2) is 30-40 mm higher than that of the sleeve (1);
the preprocessing comprises point cloud data segmentation, point cloud data denoising, and mixed point and error point removal.
2. The roadway deformation monitoring method according to claim 1, wherein the specific process of point cloud data segmentation is as follows: and dividing the point cloud data according to the space, texture and geometric characteristics of the point cloud data to divide the point cloud data with similar characteristics or semantics together.
3. The roadway deformation monitoring method according to claim 1, wherein the specific process of point cloud data denoising is as follows: and denoising the drift points, the isolated points and the redundant points in the point cloud data through 3D Reshaper software.
4. The roadway deformation monitoring method according to claim 1, wherein the concrete process of removing the mixed points and the error points is as follows: and removing mixed points and error points in the point cloud data according to an iterative closest point algorithm.
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| CN112282847B (en) * | 2020-09-17 | 2023-03-31 | 中煤(天津)地下工程智能研究院有限公司 | Deformation monitoring method for underground coal mine roadway |
| CN112378475B (en) * | 2020-11-17 | 2022-11-01 | 哈尔滨工业大学 | Large length-diameter ratio vertical tank volume continuous laser scanning internal measurement device and measurement method |
| CN114155245B (en) * | 2022-02-10 | 2022-05-03 | 中煤科工开采研究院有限公司 | Surrounding rock deformation monitoring method and device based on three-dimensional point cloud under coal mine |
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| CN106813589B (en) * | 2015-11-30 | 2019-09-10 | 中国石油化工股份有限公司 | With External floating roof tank real-time deformation monitoring method |
| CN106401651B (en) * | 2016-11-07 | 2018-04-13 | 中国矿业大学 | A kind of full lane overall process tunneling boring areal deformation monitoring device and method |
| CN206321207U (en) * | 2016-11-22 | 2017-07-11 | 山东科技大学 | Lane surface displacement measurement apparatus |
| CN109141383A (en) * | 2017-11-13 | 2019-01-04 | 上海华测导航技术股份有限公司 | Application method of the three-dimensional laser scanner in subway tunnel detection |
| CN108801170B (en) * | 2018-06-29 | 2021-10-15 | 深圳市市政设计研究院有限公司 | Tunnel deformation monitoring system |
| CN108917712A (en) * | 2018-07-10 | 2018-11-30 | 湖南城市学院 | A kind of Tunnel automation monitoring system and method based on three-dimensional laser scanning technique |
| CN109115119B (en) * | 2018-11-01 | 2020-10-02 | 山东科技大学 | Coal mine roadway deformation monitoring device and using method thereof |
| CN109373923A (en) * | 2018-11-30 | 2019-02-22 | 中国矿业大学(北京) | A kind of monitoring system and method for mining tunnel surrouding rock deformation |
| CN209727052U (en) * | 2019-04-24 | 2019-12-03 | 青岛海诚自动化设备有限公司 | A kind of roadway deformation dynamic monitoring system based on laser ranging technique |
| CN110736434B (en) * | 2019-10-28 | 2021-04-13 | 中国矿业大学 | Online monitoring system and monitoring method for coal mine tunnel surface displacement |
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