Coal mine underground air speed and air volume and roadway section integrated laser detection method

Abstract

The invention discloses a coal mine underground air speed and air volume and roadway section integrated laser detection method. The method comprises the following steps that 1, a detection device is installed; step 2, constructing an inclined roadway section; 3, calculating the section area S of the inclined roadway; 4, calculating the average wind speed Vavg of the section of the inclined roadway; and step 5, calculating the air volume Q. According to the invention, measuring equipment is designed, a laser scanning sensor is arranged in the measuring equipment, 360-degree scanning of the roadway can be realized, and real sectional areas of different types of roadways can be accurately calculated in combination with spatial point cloud reconstruction and a section contour recognition algorithm; a wind speed sensor arranged on the system can be installed at any measuring point position, a built-in wind speed field compensation model and a section correction coefficient library are combined, the average wind speed under the corresponding roadway shape can be calculated through the single-point wind speed, and the measuring efficiency and universality are remarkably improved.

Description

Technical Field

[0001] The invention belongs to the technical field of wind speed and air volume detection in underground tunnels, and in particular provides an integrated laser detection method for wind speed and air volume and tunnel cross-section in coal mines. Background Art

[0002] Underground ventilation in coal mines is a key component in ensuring safe production. Accurately measuring wind speed and air volume, as crucial parameters for the ventilation system's operational status, is crucial for preventing gas accumulation, controlling the spread of harmful gases, and improving ventilation efficiency. Currently, most commonly used wind speed and air volume monitoring equipment relies on manual multi-point measurement or the deployment of fixed multiple sensors. This presents challenges such as cumbersome installation, large measurement errors, and high maintenance costs. This is particularly true in inclined tunnels, where irregular cross-sections and complex flow field distributions make it difficult to achieve rapid and accurate air volume assessment using traditional methods.

[0003] To solve the above problems, an integrated laser detection device for wind speed, wind volume and cross-section identification is proposed, which is suitable for the inclined tunnel environment in coal mines. Summary of the Invention

[0004] In order to solve the above problems, the present invention provides an integrated laser detection method for wind speed, wind volume and tunnel cross-section in coal mines.

[0005] To achieve the above object, the present invention adopts a technical solution: a method for integrating laser detection of wind speed, wind volume and roadway cross section in coal mines, which specifically includes the following steps:

[0006] Step 1: Install the detection device, fix the mounting bracket in the inclined roadway, install the measuring equipment on the mounting platform, adjust the angle of the mounting platform to make it the same as the inclination angle of the inclined roadway, and construct a coordinate system with the laser scanning head as the origin;

[0007] Step 2: Construct the inclined roadway cross section. Use measurement equipment to measure point cloud information, fit the roadway axis, and construct an orthogonal section on the roadway axis to form the inclined roadway cross section.

[0008] Step 3: Calculate the cross-sectional area S of the inclined roadway by projecting the point cloud onto an orthogonal section, identifying and removing obstacle points in the point cloud, fitting a closed contour on the inclined roadway cross-section, and calculating the area.

[0009] Step 4: Calculate the average wind speed V in the inclined tunnel section avg , use a wind speed sensor to measure the wind speed at a single point, perform correction compensation for position, cross-sectional shape, and disturbance correction based on the single point wind speed, and calculate the average wind speed;

[0010] Step 5: Calculate the air volume Q based on the cross-sectional area S of the inclined tunnel and the average wind speed V avgThe calculated air volume is Q = S × V avg .

[0011] Furthermore, in step 1, the detection device includes a measuring device, a mounting bracket, a hydraulic cylinder, and a mounting platform, the mounting bracket is fixedly installed in the inclined tunnel, the measuring device is fixedly installed on the mounting platform, the side of the measuring device is telescopically equipped with a laser scanning head, the upper surface of the measuring device is fixedly installed with a wind speed sensor, and the front surface of the measuring device is equipped with a display screen;

[0012] The lower end of the mounting bracket is fixedly mounted with a base, the upper end of the mounting bracket is fixedly mounted with a deflection side plate, a fixed shaft is fixedly mounted between the two deflection side plates, a deflection member is fixedly mounted on one side of the lower surface of the mounting platform, and the deflection member is rotatably assembled on the fixed shaft, the hydraulic cylinder is fixedly mounted on the base, the output end of the hydraulic cylinder is fixedly mounted with a support member, the other side of the lower surface of the mounting platform is fixedly mounted with a slide rail, a slider is movably assembled in the slide rail, and the support member is rotatably assembled on the lower end of the slider.

[0013] Furthermore, in step 2, the following steps are specifically included:

[0014] a. Use PCA technology to fit the roadway axis and measure n point cloud points p i =(x i ,y i , z i ), its covariance matrix is:

[0015]

[0016] in:

[0017] is the vector of point i;

[0018] is the mean vector;

[0019] b. Construct the tangent plane equation, a point P on the roadway axis i It can be expressed as:

[0020]

[0021] in:

[0022] Point P i The cross section at

[0023] s i is the scalar coefficient;

[0024] is the tangent plane normal vector;

[0025] c. Calculation formula for the orthogonal projection point X' from point X to the inner wall of the roadway:

[0026]

[0027] Among them, point X = (x, y, z) belongs to the tangent plane The conditions are:

[0028]

[0029] Furthermore, in step three, the identification and removal of obstacle points in the point cloud and fitting of a closed contour on the inclined roadway section specifically include the following steps:

[0030] a. Project the point cloud to a local two-dimensional section. Project the collected three-dimensional point cloud P (x, y, z) of the obstacle to a section perpendicular to the axis of the fitting laneway:

[0031] P'(u,v)=T(θ,φ)·P;

[0032] in:

[0033] P' is the distance from point P to the tangent plane The orthogonal projection point of

[0034] T(θ,φ) is the transformation matrix from the global coordinates to the plane orthogonal to the roadway axis;

[0035] Get the local section contour point cloud;

[0036] b. Identify the obstacle area and construct the point density function:

[0037]

[0038] in:

[0039] N i is the number of points within the neighborhood radius;

[0040] A r is the area of ​​the neighborhood radius;

[0041] The obstacle feature area satisfies the point density ρ m >> avg , with a typical geometric shape, its outer contour is fitted by RANSAC circle fitting or Hough circle detection:

[0042] (xa) 2 +(yb) 2 =r 2 ;

[0043] Use the fitting results to filter the point cloud and remove obstacle points;

[0044] c. Void interpolation and closed fitting: After removing the obstacle points, gaps appear in the inclined tunnel section. Interpolation and polygon fitting are used to close the contour.

[0045] Use Alpha Shape reconstruction to automatically connect missing areas into closed contours:

[0046]

[0047] in:

[0048] δ controls the thickness of the reconstructed contour;

[0049] A(δ) is the region or area associated with the parameter δ;

[0050] E(δ) is the set of edges, representing the edges generated by parameter δ;

[0051] △(p i ,p j ,p k ) is composed of three points p i 、p j 、p k The triangle formed;

[0052] d. Calculate the cross-sectional area after removing obstacles using the polygon formula:

[0053]

[0054] Furthermore, in step d, the curve integral area formula is used to calculate the cross-sectional area after removing obstacles, automatically adapting to complex cross-sections and concave-convex structures:

[0055]

[0056] in:

[0057] C is the closed curve of the cross-section contour after obstacle filtering.

[0058] Furthermore, in step 4, the position, cross-sectional shape, and disturbance correction are corrected and compensated to obtain the average wind speed V of the cross-sectional area. avg Compensation model:

[0059]

[0060] in:

[0061] V m is the measured wind speed at the measuring point;

[0062] α is the position correction coefficient, which realizes the correction of the measuring point position relative to the center of the section;

[0063] β is the cross-section shape coefficient, which is used to correct the effect of cross-section type on velocity distribution;

[0064] γ is the disturbance correction coefficient, which realizes the correction of local disturbances such as air ducts and brackets.

[0065] Furthermore, the position correction coefficient α, in a circular or approximately elliptical cross section, the wind speed changes along the radial direction approximately in a parabolic distribution:

[0066]

[0067] in:

[0068] V(r) is the wind speed at a point with radius r;

[0069] V0 is the maximum wind speed at the axis;

[0070] r is the distance from the measuring point to the center;

[0071] R is the equivalent radius of the roadway;

[0072] n is the flow index, laminar flow n = 1, turbulent flow n ≈ 1 / 7 to 1 / 9;

[0073] For a measuring point r m At , the position correction coefficient is:

[0074]

[0075] After calculating the integral, the position correction coefficient is:

[0076]

[0077] Furthermore, the cross-sectional shape coefficient β has different values ​​for different cross-sectional shapes. If the cross-sectional shape is rectangular, the cross-sectional shape coefficient β is 1.0-1.2; if the cross-sectional shape is trapezoidal, the cross-sectional shape coefficient β is 1.1-1.3; if the cross-sectional shape is arched, the cross-sectional shape coefficient β is 1.3-1.5.

[0078] Furthermore, the disturbance correction coefficient γ is obtained by CFD simulation:

[0079] γ=1+δ;

[0080] in:

[0081] δ is the disturbance coefficient, ranging from 0.05 to 0.3.

[0082] The beneficial effects of using the present invention are:

[0083] The present invention designs a measuring device with a built-in laser scanning sensor that can realize 360° scanning of the tunnel. Combined with spatial point cloud reconstruction and cross-sectional contour recognition algorithm, it can accurately calculate the true cross-sectional area of ​​different types of tunnels, thereby providing basic data support for air volume calculation.

[0084] Compared with traditional cross-section estimation methods, the present invention has higher geometric restoration accuracy. Especially when there are obstacles such as air ducts and water pipes, the system can identify and eliminate interference areas through intelligent point cloud segmentation and shape fitting algorithms, thereby achieving automatic obstacle avoidance and cross-section restoration.

[0085] The wind speed sensor equipped in the system can be installed at any measuring point. Combined with the built-in wind speed field compensation model and section correction coefficient library, the average wind speed under the corresponding tunnel shape can be calculated from the single-point wind speed, significantly improving measurement efficiency and versatility.

[0086] The overall device of the present invention has a compact structure and high integration, and is particularly suitable for complex scenarios with limited underground space, changeable tunnels, and large wind flow disturbances. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 This is one of the three-dimensional schematic diagrams of the detection device of the present invention.

[0088] Figure 2 This is the second three-dimensional schematic diagram of the detection device of the present invention.

[0089] Figure 3 It is a schematic diagram of the tunnel axis and inclined tunnel section of the present invention.

[0090] Figure 4 Schematic diagram of the installation of the detection device of the present invention.

[0091] The reference numerals include: 1. Measuring device, 11. Laser scanning head, 12. Wind speed sensor, 13. Display screen, 2. Mounting bracket, 21. Deflection side panel, 3. Hydraulic cylinder, 31. Support member, 32. Protective housing, 4. Mounting platform, 41. Deflection member, 42. Slide rail, 43. Slider. DETAILED DESCRIPTION

[0092] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0093] A method for integrating laser detection of wind speed, wind volume, and tunnel cross-section in coal mines, comprising the following steps:

[0094] Step 1: Install the detection device, such as Figure 4 As shown, a mounting bracket 2 is fixed in the inclined tunnel, and a measuring device 1 is installed on the mounting platform 2. The angle of the mounting platform 4 is adjusted so that the angle of the mounting platform 4 is the same as the inclination angle of the inclined tunnel, and a coordinate system is constructed with the laser scanning head 11 as the origin;

[0095] like Figure 1 and Figure 2 As shown, the detection device includes a measuring device 1, a mounting bracket 2, a hydraulic cylinder 3 and a mounting platform 4. The mounting bracket 2 is fixedly installed in the inclined tunnel, and the measuring device 1 is fixedly installed on the mounting platform 4. The side of the measuring device 1 is telescopically equipped with a laser scanning head 11, the upper surface of the measuring device 1 is fixedly installed with a wind speed sensor 12, and the front surface of the measuring device 1 is equipped with a display screen 13;

[0096] A base is fixedly installed on the lower end of the mounting bracket 2, a deflection side plate 21 is fixedly installed on the upper end of the mounting bracket 2, a fixed shaft is fixedly installed between the two deflection side plates 21, a deflection member 41 is fixedly installed on one side of the lower surface of the mounting platform 4, and the deflection member 41 is rotatably assembled on the fixed shaft, the hydraulic cylinder 3 is fixedly installed on the base, and a support member 31 is fixedly installed on the output end of the hydraulic cylinder 3, a slide rail 42 is fixedly installed on the other side of the lower surface of the mounting platform 4, a slider 43 is movably assembled in the slide rail 42, and the support member 31 is rotatably assembled on the lower end of the slider 43.

[0097] The mounting bracket 2 is installed in the inclined tunnel through the base, and then the measuring device 1 is installed and supported on the mounting platform 4. An inclination sensor is installed inside the mounting bracket 2 for measuring the inclination angle of the mounting bracket 2 when it is installed in the inclined tunnel. A processor and an oil tank are also installed inside the mounting bracket 2. After receiving the inclination angle signal, the processor controls the hydraulic pump on the oil tank, and then controls the operation of the hydraulic cylinder 3 to adjust the angle of the mounting platform 4, and then adjust the angle of the measuring device 1 and the laser scanning head 11, so that the laser scanning head 11 can scan the end face of the tunnel more smoothly.

[0098] The laser scanning head 11 is retractable and can be controlled by the built-in program of the measuring device 1 or remote operation. Before measuring the point cloud information, the laser scanning head 11 needs to be extended to the outside of the mounting platform 4 so that the point cloud information can be accurately obtained, and the tunnel axis can be accurately fitted to obtain the inclined tunnel section.

[0099] The wind speed sensor 12 is used to measure wind speed information at its location.

[0100] The tunnel profile, cross-sectional area, wind speed information obtained by the laser scanning head 11 and the wind speed sensor 12 , as well as the wind volume information obtained by calculation can all be displayed on the display screen 13 .

[0101] In addition, regarding the installation position of the mounting bracket 2, it can also be set on the top surface of the tunnel according to the actual situation in the tunnel.

[0102] Step 2: Constructing an inclined roadway cross section. Use the measuring device 1 to measure the point cloud information, fit the roadway axis, and construct an orthogonal section on the roadway axis to form an inclined roadway cross section. This includes the following steps:

[0103] a. Use PCA technology to fit the roadway axis and measure n point cloud points p i =(x i ,y i , z i ), its covariance matrix is:

[0104]

[0105] in:

[0106] is the vector of point i;

[0107] is the mean vector;

[0108] T is the transpose symbol, is the transposed term;

[0109] The roadway axis can be found according to the above formula;

[0110] b. Construct the tangent plane equation, a point P on the roadway axis i It can be expressed as:

[0111]

[0112] in:

[0113] Point P i section, section That is the plane where the inclined roadway section is located;

[0114] is the starting point coordinate vector, i.e., the reference origin, which in this embodiment is the position of the laser scanning head 11;

[0115] s i is a scalar coefficient, indicating that Along direction the "distance" scale of movement;

[0116] is the tangent plane normal vector;

[0117] c. Calculation formula for the orthogonal projection point X' from point X to the inner wall of the roadway:

[0118]

[0119] Among them, point X = (x, y, z) belongs to the tangent plane The conditions are:

[0120]

[0121] Multiple orthogonal projection points X' form the cross-sectional profile, and then the inclined tunnel cross-section is obtained.

[0122] like Figure 3 As shown in the figure, the solid line part is a schematic diagram of the inclined tunnel, the dotted straight line represents the tunnel axis, and the circular dotted line represents the cross-sectional contour, thereby obtaining the cross-sectional view of the inclined tunnel.

[0123] Step 3: Calculate the cross-sectional area S of the inclined tunnel. Project the point cloud onto the orthogonal section, identify and remove obstacle points in the point cloud, fit a closed contour to the inclined tunnel cross-section, and calculate the area. This includes the following steps:

[0124] The original point cloud contains information about the tunnel structure and obstacles, including air ducts, water pipes, cables, etc. During the cross-section recognition process, the obstacle point cloud needs to be removed, and only the inner wall contour of the tunnel is retained. This part can be used as a preprocessing step in the LiDAR cross-section extraction algorithm to improve the accuracy of cross-section recognition.

[0125] a. Project the point cloud to a local two-dimensional section. Project the collected three-dimensional point cloud P (x, y, z) of the obstacle to a section perpendicular to the axis of the fitting laneway:

[0126] P'(u,v)=T(θ,φ)·P;

[0127] in:

[0128] P' is the distance from point P to the tangent plane The orthogonal projection point of

[0129] T(θ,φ) is the transformation matrix from the global coordinates to the plane orthogonal to the roadway axis;

[0130] Obtain the local cross-sectional contour point cloud of the obstacle;

[0131] b. Identify the obstacle area and construct the point density function:

[0132]

[0133] in:

[0134] N i is the number of points within the neighborhood radius;

[0135] A r is the area of ​​the neighborhood radius;

[0136] The obstacle feature area satisfies the point density ρ m >>ρ avg , with a typical geometric shape, its outer contour is fitted by RANSAC circle fitting or Hough circle detection:

[0137] (xa) 2 +(yb) 2 =r 2 ;

[0138] in:

[0139] ρ m is the local point density of the mth point, which means the number of points within a certain area (such as radius r) centered at the mth point;

[0140] ρ avg It is the global or regional average point density, the average point density of all points or within a specified range, used to compare outliers;

[0141] Point density judgment formula ρ i >>ρ avg , commonly used for obstacle identification or anomaly detection in point cloud data analysis;

[0142] Use the fitting results to filter the point cloud and remove obstacle points;

[0143] c. Void interpolation and closed fitting: After removing the obstacle points, gaps appear in the inclined tunnel section. Interpolation and polygon fitting are used to close the contour.

[0144] Use Alpha Shape reconstruction to automatically connect missing areas into closed contours:

[0145]

[0146] in:

[0147] δ controls the thickness of the reconstructed contour;

[0148] A(δ) is the region or area associated with the parameter δ, which can be a region formed in a δ-shape or a δ-complex structure;

[0149] E(δ) is the set of edges, representing the edges generated by parameter δ;

[0150] (p i ,p j ) represents the point p i To point p j A directed edge of ;

[0151] (p i ,pj )∈E(δ) represents the edge (p i ,p j ) belongs to the edge set E(δ);

[0152] △(p i ,p j ,p k ) is composed of three points p i 、p j 、p k The triangle formed by p i 、p j 、p k is a point in a set of points, usually a data point in a plane or space;

[0153] It represents the fitting of the remaining useful contour after removing the local cross-section contour point cloud of the above obstacles;

[0154] d. Calculate the cross-sectional area after removing obstacles using the polygon formula:

[0155]

[0156] In addition, the curve integral area formula can be used to calculate the cross-sectional area after removing obstacles, automatically adapting to complex cross-sections and concave and convex structures:

[0157]

[0158] in:

[0159] C is the closed curve of the cross-section contour after obstacle filtering;

[0160] This formula automatically adapts to complex cross-sections and concave structures.

[0161] Step 4: Calculate the average wind speed V in the inclined tunnel section avg , using wind speed sensor 12 to measure single-point wind speed, and making correction compensation for position, cross-sectional shape, and disturbance correction according to the single-point wind speed, and calculating the average wind speed;

[0162] The wind speed measurement point is set at any position in the tunnel (not the tunnel center or the area with the highest velocity), so its value cannot directly represent the average wind speed of the section. To calculate the average score based on the wind speed at any position, the following should be considered:

[0163] 1. Tunnel cross-sectional shape, including arch, trapezoid, rectangle, etc.;

[0164] 2. Velocity distribution, i.e. the difference between the boundary layer and the center;

[0165] 3. Flow state, i.e., laminar or turbulent;

[0166] 4. System error caused by measuring point position offset;

[0167] 5. Asymmetric flow field caused by local disturbances (ducts, brackets, etc.);

[0168] In view of the above content, it is necessary to correct and compensate the position, cross-section shape, and disturbance correction to obtain the average wind speed V of the calculated cross-section. avg Compensation model:

[0169]

[0170] Where: V m is the measured wind speed at the measuring point;

[0171] α is the position correction coefficient, which realizes the correction of the measuring point position relative to the center of the section;

[0172] β is the cross-section shape coefficient, which is used to correct the effect of cross-section type on velocity distribution;

[0173] γ is the disturbance correction coefficient, which realizes the correction of local disturbances such as air ducts and brackets;

[0174] Position correction coefficient α, in a circular or approximately elliptical section, the wind speed changes along the radius direction approximately in a parabolic distribution:

[0175]

[0176] in:

[0177] V(r) is the wind speed at a point with radius r;

[0178] V0 is the maximum wind speed at the axis;

[0179] r is the distance from the measuring point to the center;

[0180] R is the equivalent radius of the roadway;

[0181] n is the flow index, laminar flow n = 1, turbulent flow n ≈ 1 / 7 to 1 / 9;

[0182] For a measuring point r m At , the position correction coefficient is:

[0183]

[0184] r m is the radius of a certain point, that is, the local radius;

[0185] After calculating the integral, the position correction coefficient is:

[0186]

[0187] From the formula, we can see that the closer the measuring point is to the edge, the smaller the wind speed is and the larger the correction coefficient is.

[0188] The cross-sectional shape coefficient β, as shown in Table 1, has different values ​​for different cross-sectional shapes. If the cross-sectional shape is rectangular, the cross-sectional shape coefficient β is 1.0 to 1.2; if the cross-sectional shape is trapezoidal, the cross-sectional shape coefficient β is 1.1 to 1.3; if the cross-sectional shape is arched, the cross-sectional shape coefficient β is 1.3 to 1.5;

[0189] Table 1: Shape coefficient table

[0190] Cross-sectional shape Typical correction coefficient β\betaβ Features rectangle 1.0～1.2 The speed distribution is relatively uniform Trapezoid 1.1～1.3 The lower speed is higher than the top speed arched 1.3～1.5 The wind speed in the center is significantly higher than that on both sides

[0191] The disturbance correction coefficient γ is obtained by CFD simulation or actual experience when there are obstacles (such as air ducts and cable ducts) near the measuring point, which will cause local flow velocity changes.

[0192] γ=1+δ;

[0193] Where: δ is the disturbance coefficient, ranging from 0.05 to 0.3.

[0194] Step 5: Calculate the air volume Q based on the cross-sectional area S of the inclined tunnel and the average wind speed V avg The calculated air volume is Q = S × V avg .

[0195] The above content is only a preferred embodiment of the present invention. For ordinary technicians in this field, according to the concept of the present invention, many changes can be made in the specific implementation method and application scope. As long as these changes do not deviate from the concept of the present invention, they all fall within the scope of protection of the present invention.

Claims

1. A method for integrated laser detection of wind speed, wind volume and tunnel cross section in coal mines, characterized in that: The specific steps include: Step 1: Install the detection device, fix the mounting bracket in the inclined roadway, install the measuring equipment on the mounting platform, adjust the angle of the mounting platform to make it the same as the inclination angle of the inclined roadway, and construct a coordinate system with the laser scanning head as the origin; Step 2: Construct the inclined roadway cross section. Use measurement equipment to measure point cloud information, fit the roadway axis, and construct an orthogonal section on the roadway axis to form the inclined roadway cross section. Step 3: Calculate the cross-sectional area S of the inclined roadway by projecting the point cloud onto an orthogonal section, identifying and removing obstacle points in the point cloud, fitting a closed contour on the inclined roadway cross-section, and calculating the area. Step 4: Calculate the average wind speed V in the inclined tunnel section avg , use a wind speed sensor to measure the wind speed at a single point, perform correction compensation for position, cross-sectional shape, and disturbance correction based on the single point wind speed, and calculate the average wind speed; Step 5: Calculate the air volume Q based on the cross-sectional area S of the inclined tunnel and the average wind speed V avg The calculated air volume is Q = S × V avg .

2. The integrated laser detection method for wind speed, wind volume, and tunnel cross-section in a coal mine according to claim 1, characterized in that: In step 1, the detection device includes a measuring device, a mounting bracket, a hydraulic cylinder, and a mounting platform. The mounting bracket is fixedly installed in the inclined tunnel, the measuring device is fixedly installed on the mounting platform, the side of the measuring device is telescopically equipped with a laser scanning head, the upper surface of the measuring device is fixedly installed with a wind speed sensor, and the front surface of the measuring device is equipped with a display screen; The lower end of the mounting bracket is fixedly mounted with a base, the upper end of the mounting bracket is fixedly mounted with a deflection side plate, a fixed shaft is fixedly mounted between the two deflection side plates, a deflection member is fixedly mounted on one side of the lower surface of the mounting platform, and the deflection member is rotatably assembled on the fixed shaft, the hydraulic cylinder is fixedly mounted on the base, the output end of the hydraulic cylinder is fixedly mounted with a support member, the other side of the lower surface of the mounting platform is fixedly mounted with a slide rail, a slider is movably assembled in the slide rail, and the support member is rotatably assembled on the lower end of the slider.

3. The integrated laser detection method for wind speed, wind volume, and tunnel cross-section in coal mines according to claim 1, characterized in that: In step 2, the following steps are specifically included: a. Use PCA technology to fit the roadway axis and measure n point cloud points p i =(x i ,y i , z i ), its covariance matrix is: in: is the vector of point i; is the mean vector; b. Construct the tangent plane equation, a point P on the roadway axis i It can be expressed as: in: Point P i The cross section at s i is the scalar coefficient; is the tangent plane normal vector; c. Calculation formula for the orthogonal projection point X' from point X to the inner wall of the roadway: Among them, point X = (x, y, z) belongs to the tangent plane The conditions are:

4. The integrated laser detection method for wind speed, wind volume, and tunnel cross-section in coal mines according to claim 1, characterized in that: In step three, the obstacle points in the point cloud are identified and removed, and a closed contour is fitted on the inclined roadway section, specifically including the following steps: a. Project the point cloud to a local two-dimensional section. Project the collected three-dimensional point cloud P (x, y, z) of the obstacle to a section perpendicular to the axis of the fitting tunnel: P'(u,v)=T(θ,φ)·P; in: P' is the distance from point P to the tangent plane The orthogonal projection point of T(θ,φ) is the transformation matrix from the global coordinates to the plane orthogonal to the roadway axis; Get the local section contour point cloud; b. Identify the obstacle area and construct the point density function: in: N i is the number of points within the neighborhood radius; A r is the area of ​​the neighborhood radius; The obstacle feature area satisfies the point density ρ m >>ρ avg , with a typical geometric shape, its outer contour is fitted by RANSAC circle fitting or Hough circle detection: (x-a) 2 +(y-b) 2 =r 2 ; Use the fitting results to filter the point cloud and remove obstacle points; c. Void interpolation and closed fitting: After removing the obstacle points, gaps appear in the inclined tunnel section. Interpolation and polygon fitting are used to close the contour. Use Alpha Shape reconstruction to automatically connect missing areas into closed contours: in: δ controls the thickness of the reconstructed contour; A(δ) is the region or area associated with the parameter δ; E(δ) is the set of edges, representing the edges generated by parameter δ; △(p i ,p j ,p k ) is composed of three points p i 、p j 、p k The triangle formed; d. Calculate the cross-sectional area after removing obstacles using the polygon formula:

5. The integrated laser detection method for wind speed, wind volume, and tunnel cross-section in coal mines according to claim 4, characterized in that: In step d, the curve integral area formula is used to calculate the cross-sectional area after removing obstacles, automatically adapting to complex cross-sections and concave and convex structures: in: C is the closed curve of the cross-section contour after obstacle filtering.

6. The integrated laser detection method for wind speed, wind volume, and tunnel cross-section in coal mines according to claim 1, characterized in that: In step 4, the position, cross-sectional shape, and disturbance correction are corrected and compensated to obtain the average wind speed V of the calculated cross-sectional area. avg Compensation model: in: V m is the measured wind speed at the measuring point; α is the position correction coefficient, which realizes the correction of the measuring point position relative to the center of the section; β is the cross-section shape coefficient, which is used to correct the effect of cross-section type on velocity distribution; γ is the disturbance correction coefficient, which realizes the correction of local disturbances such as air ducts and brackets.

7. The integrated laser detection method for wind speed, wind volume, and tunnel cross-section in coal mines according to claim 6, characterized in that: The position correction coefficient α, in a circular or approximately elliptical cross section, the wind speed changes along the radius direction approximately in a parabolic distribution: in: V(r) is the wind speed at a point with radius r; V0 is the maximum wind speed at the axis; r is the distance from the measuring point to the center; R is the equivalent radius of the roadway; n is the flow index, laminar flow n = 1, turbulent flow n ≈ 1 / 7 to 1 / 9; For a measuring point r m At , the position correction coefficient is: After calculating the integral, the position correction coefficient is:

8. The integrated laser detection method for wind speed, wind volume, and tunnel cross-section in coal mines according to claim 6, characterized in that: The cross-sectional shape coefficient β has different values ​​for different cross-sectional shapes. If the cross-sectional shape is rectangular, the cross-sectional shape coefficient β is 1.0-1.2; if the cross-sectional shape is trapezoidal, the cross-sectional shape coefficient β is 1.1-1.3; if the cross-sectional shape is arched, the cross-sectional shape coefficient β is 1.3-1.

5.

9. The integrated laser detection method for wind speed, wind volume, and tunnel cross-section in coal mines according to claim 6, characterized in that: The disturbance correction coefficient γ is obtained by CFD simulation: γ=1+δ; in: δ is the disturbance coefficient, ranging from 0.05 to 0.3.

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