CN117232394A - Deviation detection method for coal mine tunneling roadway - Google Patents
Deviation detection method for coal mine tunneling roadway Download PDFInfo
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- 239000003245 coal Substances 0.000 title claims abstract description 23
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Abstract
The invention relates to a deviation detection method for a coal mine tunneling roadway, and belongs to the technical field of coal mine intellectualization. Comprising the following steps: a solid-state laser radar is arranged right below the tunnel roof laser director; after the tunneling machine stops at the position tunneling machine body, starting a solid-state laser radar to perform three-dimensional laser scanning to obtain an initial three-dimensional point cloud data set; screening out a three-dimensional point cloud data set of the roadway wall surface; projecting the three-dimensional point cloud data set of the roadway wall surface into two-dimensional projection point clouds on two orthogonal planes, and determining a central line equation of the roadway wall surface point clouds according to the central line equations of the two-dimensional projection point clouds; and comparing a central line equation of the roadway wall point cloud with the laser pointing direction of the laser pointing instrument to obtain the deviation size of the tunneling roadway. According to the invention, the automatic and non-contact method is adopted to detect the deviation of the tunneling roadway, so that higher detection precision can be ensured, meanwhile, the dependence on manpower can be greatly reduced, and the potential safety hazard is small.
Description
Technical Field
The invention relates to the technical field of coal mine intellectualization, in particular to a deviation detection method of a coal mine tunneling roadway.
Background
In the coal mine tunnel tunneling operation, the tunnel tunneling needs to be subjected to deviation detection at regular intervals, namely the gap between the tunnel to be excavated and an ideal tunnel is measured. In the traditional coal mine tunneling working face, the detection of tunnel tunneling deviation is often carried out by means of manual operation of underground operators, and the detection is contrary to the intelligent development of coal mines which are minimally humanized and unmanned, and certain potential safety hazards exist. The three-dimensional laser scanning technology uses laser point cloud as a carrier, and the obtained three-dimensional data can visually display geometric and spatial information, and is widely applied to automatic driving, robot positioning and geographical mapping, but due to the particularity of a coal mine tunneling scene, the existing application method is difficult to directly apply, and special design improvement is required according to the coal mine tunneling scene.
Disclosure of Invention
In order to solve the technical problems, the invention provides a deviation detection method for a coal mine tunneling roadway. The technical scheme of the invention is as follows:
a deviation detection method of a coal mine tunneling roadway comprises the following steps:
s1, the heading machine moves to an initial heading operation position, a solid-state laser radar is installed right below the position of a tunnel roof laser director, and the scanning direction of the solid-state laser radar is the same as the laser emission direction of the laser director;
s2, after the heading machine stops to support at the position of the heading machine body, starting a solid-state laser radar to perform three-dimensional laser scanning on the direction of the heading machine to obtain an initial three-dimensional point cloud data set;
s3, acquiring the initial three-dimensional point cloud data set, and screening out the three-dimensional point cloud data set of the roadway wall surface from the initial three-dimensional point cloud data set;
s4, projecting the three-dimensional point cloud data set of the roadway wall surface into two-dimensional projection point clouds on two orthogonal planes, respectively calculating the central line equations of the two-dimensional projection point clouds by a curve fitting method, and determining the central line equation of the roadway wall surface point cloud according to the central line equations of the two-dimensional projection point clouds;
and S5, comparing a central line equation of the roadway wall point cloud with the laser pointing direction of the laser pointing instrument to obtain the deviation size of the tunneling roadway.
Optionally, the step S3 includes the following steps when screening the three-dimensional point cloud data set of the roadway wall surface from the initial three-dimensional point cloud data set:
s31, a space rectangular coordinate system is established by taking the self laser emission center of the solid-state laser radar as an origin, taking the right front of the solid-state laser radar as a Y axis and taking the right upper of the solid-state laser radar as a Z axis;
s32, establishing an initial three-dimensional point cloud data set of the current heading machine body at stop time tN+ represents a positive integer set, p t Representing an initial three-dimensional point cloud dataset, p i Is p t Any point (x) i ,y i ,z i ) Is p i Coordinates in a space rectangular coordinate system, p represents p t The number of points in (a);
s33, determining two condition thresholds Rmax and Rmin, and concentrating the initial three-dimensional point cloud data to obtain a linear distance value D from a Y axis ist Points greater than Rmax and less than Rmin are removed,；
s34, uniformly downsampling the three-dimensional point cloud data set processed in the S33 to enable the number of points to be reduced to N, and obtaining the three-dimensional point cloud data set of the roadway wall surface。
Optionally, the step S4 includes the following steps when the three-dimensional point cloud data set of the roadway wall is projected on two orthogonal planes to form two-dimensional projection point clouds, and the centerline equations of the two-dimensional projection point clouds are respectively calculated by a curve fitting method:
s41, respectively projecting the three-dimensional point cloud data set of the roadway wall surface on a OYX plane and an OYZ plane of a space rectangular coordinate system by using a projection method to obtain two-dimensional point cloud sets q t OYX And q t OYZ ；
S42, extracting q t OYX And q t OYZ From q t OYX And q t OYZ Extracting an outer contour point cloud along the Y-axis direction from all the outer contour points of the model;
s43, using polynomial fitting method to obtain the final product q t OYX And q t OYZ The extracted outer contour point clouds along the Y-axis direction are respectively fitted into an equation of a OYX plane and an equation of an OYZ plane to obtain a center line equation of two-dimensional projection point clouds.
Optionally, the step S4 is configured to combine the centerline equations of the two-dimensional projection point clouds into a three-dimensional equation according to the common variable of the equation of the OYX plane and the equation of the OYZ plane when determining the centerline equation of the roadway wall point cloud according to the centerline equations of the two-dimensional projection point clouds, so as to obtain the centerline equation of the roadway wall point cloud.
Optionally, the step S42 is to extract a two-dimensional point cloud set q t OYX And q t OYZ Comprises the following steps:
extracting two-dimensional point cloud set q by two-dimensional point set concave-convex algorithm t OYX And q t OYZ Is defined by the outer contour points of the outer contour of the outer.
All the above optional technical solutions can be arbitrarily combined, and the detailed description of the structures after one-to-one combination is omitted.
By means of the scheme, the beneficial effects of the invention are as follows:
the method is characterized in that an initial three-dimensional point cloud data set of an operation area of the heading machine is acquired through a solid-state laser radar, a three-dimensional point cloud data set of a roadway wall surface is extracted through a point cloud processing method, after a central line equation of the roadway wall surface point cloud is extracted through a two-dimensional projection and curve fitting method, the central line equation of the roadway wall surface point cloud is compared with the laser pointing direction of a laser pointing instrument to obtain the deviation size of a heading roadway, and the method for detecting the deviation of the heading roadway of the coal mine based on the solid-state laser radar is provided.
The foregoing description is only an overview of the present invention, and is intended to provide a better understanding of the present invention, as it is embodied in the following description, with reference to the preferred embodiments of the present invention and the accompanying drawings.
Drawings
Fig. 1 is a flow chart of the present invention.
FIG. 2 is a schematic diagram of the positional relationship of the body of the heading machine, the laser director and the solid-state lidar of the present invention.
Detailed Description
The following describes in further detail the embodiments of the present invention with reference to the drawings and examples. The following examples are illustrative of the invention and are not intended to limit the scope of the invention.
As shown in fig. 1, the method for detecting the deviation of the coal mine tunneling roadway provided by the invention comprises the following steps:
s1, the heading machine moves to an initial heading operation position, a solid-state laser radar is installed right below the position of a tunnel roof laser director, and the scanning direction of the solid-state laser radar is the same as the laser emission direction of the laser director.
The mechanical rotary laser radar has relatively poor reliability and high cost because the mechanical abrasion is inevitably caused by the internal rotary mechanical structure. Although the solid-state laser radar has angle limitation on the visual field, the solid-state laser radar can collect more three-dimensional point cloud characteristic information due to higher resolution in the horizontal direction and the vertical direction, and has certain research value. Therefore, the embodiment of the invention selects the solid-state laser radar to perform laser scanning.
As shown in fig. 2, the position relationship of the heading machine body 1, the laser direction indicator 2 and the solid-state laser radar 3 in the present invention is schematically shown, and the solid-state laser radar is installed right under the position of the laser direction indicator. The scanning direction of the solid-state laser radar 3 is the working area of the heading machine, so that special design improvement is carried out according to the tunneling scene of the coal mine.
And S2, after the heading machine stops to support at the position where the heading machine is located, starting a solid-state laser radar to perform three-dimensional laser scanning on the direction where the heading machine is located, and obtaining an initial three-dimensional point cloud data set.
The scanning frequency of the solid-state laser radar is 10Hz, and the three-dimensional laser scanning is carried out on the area in the direction of the heading machine, so that a series of three-dimensional point cloud data are obtained, and an initial three-dimensional point cloud data set is obtained. And meanwhile, the initial three-dimensional point cloud data set is transmitted into a server of a centralized control center at the tail part of the tunneling roadway for further processing. The following steps are performed by the server.
S3, acquiring the initial three-dimensional point cloud data set, and screening out the three-dimensional point cloud data set of the roadway wall surface from the initial three-dimensional point cloud data set.
Specifically, the step S3 includes the following steps when screening the three-dimensional point cloud data set of the roadway wall surface from the initial three-dimensional point cloud data set:
s31, a space rectangular coordinate system is established by taking the self laser emission center of the solid-state laser radar as an origin, taking the right front of the solid-state laser radar as a Y axis and taking the right upper of the solid-state laser radar as a Z axis. At this time, the laser emitted from the laser pointing device is a ray parallel to the Y axis in the coordinate system.
S32, establishing an initial three-dimensional point cloud data set of the current heading machine body at stop time tN+ represents a positive integer set, p t Representing an initial three-dimensional point cloud dataset, p i Is p t Any point (x) i ,y i ,z i ) Is p i Coordinates in a space rectangular coordinate system, p represents p t The number of points in (a).
S33, determining two condition thresholds Rmax and Rmin, and concentrating the initial three-dimensional point cloud data to obtain a linear distance value D from a Y axis ist Points greater than Rmax and less than Rmin are removed,。
rmax and Rmin are empirical values and are determined by means of the requirement of the actual coal mine roadway cutting section size.
S34, uniformly downsampling the three-dimensional point cloud data set processed in the S33 to enable the number of points to be reduced to N, and obtaining the three-dimensional point cloud data set of the roadway wall surface。
S4, projecting the three-dimensional point cloud data set of the roadway wall surface into two-dimensional projection point clouds on two orthogonal planes, respectively calculating the central line equations of the two-dimensional projection point clouds through a curve fitting method, and determining the central line equation of the roadway wall surface point cloud according to the central line equations of the two-dimensional projection point clouds.
Specifically, the step S4 includes the following steps when the three-dimensional point cloud data set of the roadway wall is projected on two orthogonal planes to form two-dimensional projection point clouds, and the centerline equations of the two-dimensional projection point clouds are respectively calculated by a curve fitting method:
s41, respectively projecting the three-dimensional point cloud data set of the roadway wall surface on a OYX plane and an OYZ plane of a space rectangular coordinate system by using a projection method to obtain two-dimensional point cloud sets q t OYX And q t OYZ 。
S42, extracting q t OYX And q t OYZ From q t OYX And q t OYZ Extracting an outer contour point cloud along the Y-axis direction from all the outer contour points of the model.
S43, using polynomial fitting method to obtain the final product q t OYX And q t OYZ The extracted outer contour point clouds along the Y-axis direction are respectively fitted into an equation of a OYX plane (a relation between Y and x) and an equation of an OYZ plane (a relation between Y and z), so as to obtain a center line equation of the two-dimensional projection point clouds.
Based on the above, the S4, when determining the centerline equation of the roadway wall point cloud according to the centerline equations of the two-dimensional projection point clouds, merges the centerline equations of the two-dimensional projection point clouds into a three-dimensional equation according to the common variable y of the equation of the OYX plane and the equation of the OYZ plane, so as to obtain the centerline equation of the roadway wall point cloud.
Specifically, the equation according to the OYX plane and the equation of the OYZ plane are the relationship of y and x, x=f (y), and the relationship of y and z, z=g (y), respectively, and a parameter equation for y is changed by taking y as an argument. And combining the two equations to obtain a three-dimensional equation, wherein the equation is a central line equation of the roadway wall point cloud.
In a specific embodiment, the step S42 is performed to extract a two-dimensional point cloud set q t OYX And q t OYZ When all outline points of (a) are obtained, extracting a two-dimensional point cloud set q by a two-dimensional point set concave-convex algorithm t OYX And q t OYZ Is defined by the outer contour points of the outer contour of the outer.
And S5, comparing a central line equation of the roadway wall point cloud with the laser pointing direction of the laser pointing instrument to obtain the deviation size of the tunneling roadway.
In specific implementation, the deviation size of the tunneling roadway is fed back to a driver of the tunneling machine and used for assisting in calibrating the tunneling operation direction after the tunneling operation direction is calibrated.
In summary, the embodiment of the invention collects an initial three-dimensional point cloud data set of an operation area of a heading machine through a solid-state laser radar, extracts a three-dimensional point cloud data set of a roadway wall surface through a point cloud processing method, extracts a central line equation of the roadway wall surface point cloud through a two-dimensional projection and curve fitting method, compares the central line equation of the roadway wall surface point cloud with the laser pointing direction of a laser pointing instrument to obtain the deviation dimension of a heading roadway, and provides an automatic and non-contact method for detecting the deviation of the coal mine heading roadway based on the solid-state laser radar.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, and it should be noted that it is possible for those skilled in the art to make several improvements and modifications without departing from the technical principle of the present invention, and these improvements and modifications should also be regarded as the protection scope of the present invention.
Claims (5)
1. The deviation detection method for the coal mine tunneling roadway is characterized by comprising the following steps of:
s1, the heading machine moves to an initial heading operation position, a solid-state laser radar is installed right below the position of a tunnel roof laser director, and the scanning direction of the solid-state laser radar is the same as the laser emission direction of the laser director;
s2, after the heading machine stops to support at the position of the heading machine body, starting a solid-state laser radar to perform three-dimensional laser scanning on the direction of the heading machine to obtain an initial three-dimensional point cloud data set;
s3, acquiring the initial three-dimensional point cloud data set, and screening out the three-dimensional point cloud data set of the roadway wall surface from the initial three-dimensional point cloud data set;
s4, projecting the three-dimensional point cloud data set of the roadway wall surface into two-dimensional projection point clouds on two orthogonal planes, respectively calculating the central line equations of the two-dimensional projection point clouds by a curve fitting method, and determining the central line equation of the roadway wall surface point cloud according to the central line equations of the two-dimensional projection point clouds;
and S5, comparing a central line equation of the roadway wall point cloud with the laser pointing direction of the laser pointing instrument to obtain the deviation size of the tunneling roadway.
2. The method for detecting the deviation of a coal mine tunneling roadway according to claim 1, wherein S3, when screening out the three-dimensional point cloud data set of the roadway wall surface from the initial three-dimensional point cloud data set, comprises the following steps:
s31, a space rectangular coordinate system is established by taking the self laser emission center of the solid-state laser radar as an origin, taking the right front of the solid-state laser radar as a Y axis and taking the right upper of the solid-state laser radar as a Z axis;
s32, establishing an initial three-dimensional point cloud data set of the current heading machine body at stop time tN+ represents a positive integer set, p t Representing an initial three-dimensional point cloud dataset, p i Is p t Any point (x) i ,y i ,z i ) Is p i Coordinates in a space rectangular coordinate system, p represents p t The number of points in (a);
s33, determining two condition thresholds Rmax and Rmin, and concentrating the initial three-dimensional point cloud data to obtain a linear distance value D from a Y axis ist Points greater than Rmax and less than Rmin are removed,；
s34, uniformly downsampling the three-dimensional point cloud data set processed in the S33 to enable the number of points to be reduced to N, and obtaining the three-dimensional point cloud data set of the roadway wall surface。
3. The method for detecting the deviation of the tunneling roadway of the coal mine according to claim 2, wherein the step S4 is characterized in that when the three-dimensional point cloud data set of the roadway wall surface is projected to two-dimensional projection point clouds on two orthogonal planes, and the centerline equations of the two-dimensional projection point clouds are respectively calculated by a curve fitting method, the method comprises the following steps:
s41, respectively projecting the three-dimensional point cloud data set of the roadway wall surface on a OYX plane and an OYZ plane of a space rectangular coordinate system by using a projection method to obtain two-dimensional point cloud sets q t OYX And q t OYZ ；
S42, extracting q t OYX And q t OYZ From q t OYX And q t OYZ Extracting an outer contour point cloud along the Y-axis direction from all the outer contour points of the model;
s43, using polynomial fitting method to obtain the final product q t OYX And q t OYZ The extracted outer contour point clouds along the Y-axis direction are respectively fitted into an equation of a OYX plane and an equation of an OYZ plane to obtain a center line equation of two-dimensional projection point clouds.
4. The method for detecting the deviation of the tunneling roadway in the coal mine according to claim 3, wherein the step S4 is characterized in that when the centerline equation of the roadway wall point cloud is determined according to the centerline equations of the two-dimensional projection point clouds, the centerline equations of the two-dimensional projection point clouds are combined into a three-dimensional equation according to the common variable of the equation of the OYX plane and the equation of the OYZ plane, so as to obtain the centerline equation of the roadway wall point cloud.
5. A method of detecting a deviation in a coal mine tunnelling roadway as claimed in claim 3, wherein S42 is a method of extracting a two-dimensional point cloud set q t OYX And q t OYZ Comprises the following steps:
extracting two-dimensional point cloud set q by two-dimensional point set concave-convex algorithm t OYX And q t OYZ Is defined by the outer contour points of the outer contour of the outer.
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Citations (5)
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| CN116630399A (en) * | 2023-02-08 | 2023-08-22 | 北京大学 | Automatic roadway point cloud center line extraction method |
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| CN101629807A (en) * | 2009-08-20 | 2010-01-20 | 中国矿业大学(北京) | Position and attitude parameter measurement system of machine body of boring machine and method thereof |
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| CN116630399A (en) * | 2023-02-08 | 2023-08-22 | 北京大学 | Automatic roadway point cloud center line extraction method |
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