Coal mine shaft deformation automatic continuous detection device and method

Abstract

An automated continuous detection device for coal mine shaft deformation includes a cage, a mine shaft, an encoder, a lidar scanner, and a laser pointer. The cage is installed inside the mine shaft. A second camera and a counter are sequentially mounted on the front of the cage. The right side of the cage is connected to the left side of the encoder. The right pulley of the encoder slides against the inner wall of the mine shaft. The counter is electrically connected to the encoder. The bottom of the cage, from left to right, is connected to the tops of three gimbals (first, second, and third). The bottoms of the first and third gimbals are connected to the top of the laser pointer, and the bottom of the second gimbal is connected to the top of the lidar scanner. This design achieves simultaneous horizontal movement and rotation measurement of the cage, point cloud acquisition, and vertical distance measurement. The cage does not need to remain stationary for extended periods during the detection process, achieving automated continuous measurement and significantly improving operational efficiency.

Description

Technical Field

[0001] This invention relates to an improvement in coal mine shaft inspection technology, belonging to the field of shaft deformation detection, and particularly to an automated continuous detection device and method for coal mine shaft deformation. Background Technology

[0002] Coal mine shafts are essential passageways connecting underground resource extraction and surface production systems, and they also bear the heavy responsibility of ensuring mining safety. Due to complex geological conditions and the effects of underground coal mining, the radial and vertical forces on the shaft walls change, making them prone to deformation. This can affect the normal extraction of coal resources and pose a significant threat to mining safety. The cage hoisting system is a crucial component of vertical shaft hoisting equipment, playing a vital role in maintaining cage operation, guiding the cage, and preventing cage falls. Therefore, regular deformation monitoring of coal mine shafts and cage hoisting systems is essential.

[0003] The main methods for detecting wellbore deformation currently include: geometric measurement, sensor monitoring, and specialized instrument methods.

[0004] Geometric measurement methods utilize a plumb line lowered from the wellhead as a baseline, then measure the distance from the baseline to the well wall or guideway to detect deformation of the well wall and guideway. Taking the plumb line method as an example, two steel wires are vertically lowered from the wellhead as orientation references. Different horizontal planes are selected within the well shaft as measurement surfaces. The main measurements are the vertical distances from the steel wires to the front and sides of the guideway and to various points on the well wall. By analyzing and comparing multiple data points with standards, the vertical deformation of the guideway and well wall can be determined. However, the operation of suspending the steel wires is cumbersome and susceptible to influences from wind and water. Swinging or shifting of the steel wires can cause significant errors, making it difficult to guarantee accuracy. This method requires surveyors to ride in a cage and remain at the corresponding depth for measurement, which takes a considerable amount of time within the well shaft and is inefficient.

[0005] Sensor-based methods, by installing strain sensors (such as fiber optic sensors) on the wellbore and comparing and analyzing changes in strain data, can achieve 24 / 7 monitoring of wellbore deformation. However, taking fiber optic sensors as an example, they are easily affected by environmental factors within the well, and have disadvantages such as high installation costs, complex technical procedures, and difficulty in repairing sensors after failure.

[0006] For mine shaft inspection, specialized instrumental methods have been applied both domestically and internationally. The ISSM system used by the German company DMT employs an inertial navigation system to obtain the planar position of the cage platform and utilizes two sets of laser scanning equipment for shaft wall measurement. The entire system is expensive, and due to errors in the inertial navigation system, the error increases sharply with shaft depth. This equipment is mainly used to measure the relative deformation of the shaft wall and is less effective at measuring the overall deformation of the shaft.

[0007] In summary, the technical problem to be solved by this invention is: how to achieve automated and continuous detection of deformation in coal mine shafts.

[0008] The information disclosed in this background section is intended only to enhance the understanding of the overall background of this patent application and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0009] The purpose of this invention is to overcome the problem that coal mine shaft deformation cannot be continuously detected in the prior art, and to provide an automated continuous detection device and method for coal mine shaft deformation.

[0010] To achieve the above objectives, the technical solution of the present invention is: an automated continuous detection device for coal mine shaft deformation, the automated continuous detection device for coal mine shaft deformation includes a cage, a mine shaft, an encoder, a lidar scanner and a laser pointer;

[0011] The cage is installed inside the mine. A second camera and a counter are installed sequentially on the front of the cage. The right side of the cage is connected to the left side of the encoder. The right pulley of the encoder slides against the inner wall of the mine. The counter is electrically connected to the encoder.

[0012] The bottom of the cage is connected from left to right to the top of the first gimbal, the second gimbal, and the third gimbal. The bottom of the first gimbal and the third gimbal are connected to the top of the laser pointer, and the bottom of the second gimbal is connected to the top of the laser radar scanner.

[0013] A receiving frame is installed at the bottom of the inner wall of the mine, and a mounting plate is installed at the top of the receiving frame. A camera is installed in the middle section of the mounting plate.

[0014] The bottom of the inner wall of the receiving frame is provided with three marking points, and two laser spots are projected onto the bottom of the inner wall of the receiving frame by a laser pointer.

[0015] The first camera is fixed one meter above the center of the receiving frame, and the first camera captures the marked points and laser spots in the receiving frame.

[0016] A method for using an automated continuous detection device for deformation of coal mine shafts, the method comprising the following steps;

[0017] Assembly process: The bottom of the cage is connected to the top of the first gimbal, the second gimbal, and the third gimbal in sequence from left to right. The bottom of the first and third gimbals are connected to the top of the laser pointer. The bottom of the second gimbal is connected to the top of the lidar scanner. The second camera and the encoder are installed on the front of the cage. A receiving frame is placed at the bottom of the mine. A mounting plate is set on the top of the receiving frame. The first camera is installed in the middle of the mounting plate.

[0018] Operation process: First, the cage is raised from the bottom of the mine. During the ascent, the mine wall is scanned and point cloud data is saved until the cage reaches the mine opening. At the same time, during the ascent, the lidar scanner collects cross-sectional point cloud data of the mine, the encoder measures the vertical distance of the mine cross-section, and the laser pointer projects two laser spots on the receiving frame. Then, the second camera records video to record the vertical distance data in real time, which corresponds to the time-stamped cross-sectional point cloud data. The first camera records video to record and read the coordinates of the laser spots in real time.

[0019] Data processing technology: The acquired data is sent to the back-end terminal, which calculates the center coordinates of the point cloud of each cross section based on the acquired data. Finally, the difference between the center coordinates of the cross sections is used to detect the tilt change of the mine wall.

[0020] The encoder measures the vertical distance of the mine cross-section by installing an encoder on the cage and the mine shaft, connecting a counter, which can display the vertical movement distance of the cage in real time, and using a second camera to record video of the counter, so that the depth of the cage can be corresponding to the shooting time.

[0021] The cross-sectional point cloud refers to the set of points on the well wall obtained by a laser radar scanner scanning a circle around a predetermined depth in the mine on a horizontal plane.

[0022] The method of detecting the tilt change of the mine wall by subtracting the center coordinates between cross sections is as follows: The corresponding frame photos are processed to obtain the spot coordinates, the quadrant angle of the spot connection line, and the core coordinates of the lidar scanner. These are then subtracted from the initial coordinates and quadrant angle of the orientation reference to obtain the deformation of the cage. Based on the deformation of the cage, the cross section point cloud of that vertical distance is translated and rotated to correct the measurement error of the mine wall caused by the horizontal movement and rotation of the cage. Finally, the center coordinates of each cross section point cloud are obtained using the least squares method, and the tilt value of the mine wall is obtained by subtracting the center coordinates between cross sections.

[0023] The cross-sectional point cloud acquired by the lidar scanner includes angle information and timestamps.

[0024] The specific method for reading the laser spot coordinates is as follows: a program is written using the OpenCV library in Python to extract the center coordinates of the laser spot in the captured image, which are the planar coordinates of the orientation baseline.

[0025] The specific steps for extracting the center coordinates of the laser spot in the captured image are as follows: First, use the cv2.GaussianBlur function to filter the image and remove noisy pixels. Then, use the cvtColor function to process the image into grayscale. Next, use the threshold function to set the grayscale threshold and binarize the image. Then, use the findContours function to identify the edge of the laser spot and the center of the control point in the image. Finally, use the four-parameter coordinate transformation method and, based on the pixel coordinates of the control point center and the laser spot center, transform the pixel coordinates of the laser spot center to the independent coordinate system of the control point. This completes the extraction of the center coordinates of the laser spot in the captured image.

[0026] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0027] 1. In this invention, an automated continuous detection device and method for coal mine shaft deformation involves installing roller encoders on the cage and guide rails, connected to counters, to display the vertical movement distance of the cage in real time. A digital camera records video of the counter, allowing the cage depth to be correlated with the recording time. No manual control or recording of the cage's movement distance is required. The synchronization of all measurements is achieved by matching the time points of the video recording with the timestamps in the scanner's point cloud data, eliminating the need for the cage to stop midway. This automates and enables continuous detection. By matching the video recording time points with the scanner timestamps, the measurement of horizontal movement and rotation of the cage, point cloud acquisition, and vertical distance measurement are synchronized. The cage does not need to remain stationary for extended periods during detection, achieving automated continuous measurement and significantly improving operational efficiency. Therefore, this invention enables automated continuous measurement and improves measurement efficiency.

[0028] 2. In the automated continuous detection device and method for coal mine shaft deformation of the present invention, a laser radar scanner is installed on the connection line of two laser pointers to measure the shaft cross-section. It can achieve 360-degree horizontal rotation distance measurement to obtain the corresponding horizontal shaft wall cross-section point cloud, which is quick and convenient. After obtaining the cross-section point cloud, it is rotated and translated according to the horizontal rotation and movement values ​​of the orientation baseline. There is no need to adjust or correct the position and angle of the instrument during the measurement process, making operation more convenient. It eliminates the need for on-site adjustment of the distance measuring instrument direction, and the angle and core point coordinates of the point cloud can be corrected later, greatly saving on-site measurement time. Therefore, the present invention is easy to adjust and saves time.

[0029] 3. In the automated continuous detection device and method for coal mine shaft deformation of the present invention, the bottom of the cage is connected from left to right to the top of the first, second, and third gimbals. The bottoms of the first and third gimbals are connected to the top of the laser pointer, and the bottom of the second gimbal is connected to the top of the lidar scanner. The two laser pointers, combined with the electric gimbals, are vertically suspended at the bottom of the cage, using the vertical laser emitted by them as the baseline. A laser receiving plate is placed at the bottom of the shaft, and the laser spot coordinates are recorded and read in real time by a camera, avoiding errors caused by baseline offset. The planar coordinates of the orientation baseline are directly converted to the independent coordinate system defined on the receiving plate, eliminating the need for measurements between the surface and the shaft, thus saving time and manpower. Therefore, the present invention eliminates the need for back-and-forth communication, saving time and manpower. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of the structure of the present invention.

[0031] Figure 2 This is a top view of the structure of the laser radar scanner in this invention.

[0032] Figure 3 This is a schematic diagram of the receiving frame in this invention.

[0033] Figure 4 This is a process diagram of the present invention.

[0034] In the diagram: 1. Cage; 2. Mine shaft; 3. Camera 2; 4. Counter; 5. Encoder; 6. Gimbal 1; 7. Gimbal 2; 8. Gimbal 3; 9. LiDAR scanner; 10. Laser pointer; 11. Receiver frame; 12. Mounting plate; 13. Camera 1; 14. Laser spot; 15. Marker point. Detailed Implementation

[0035] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0036] See Figures 1 to 4 An automated continuous detection device for coal mine shaft deformation, comprising a cage 1, a mine shaft 2, an encoder 5, a lidar scanner 9, and a laser pointer 10;

[0037] The cage 1 is installed inside the mine shaft 2. A second camera 3 and a counter 4 are installed sequentially on the front of the cage 1. The right side of the cage 1 is connected to the left side of the encoder 5. The right pulley of the encoder 5 slides in cooperation with the inner wall of the mine shaft 2. The counter 4 is electrically connected to the encoder 5.

[0038] The bottom of the cage 1 is connected to the top of the first gimbal 6, the second gimbal 7, and the third gimbal 8 from left to right. The bottom of the first gimbal 6 and the third gimbal 8 are both connected to the top of the laser pointer 10, and the bottom of the second gimbal 7 is connected to the top of the laser radar scanner 9.

[0039] A receiving frame 11 is provided at the bottom of the inner wall of the mine 2, and an installation plate 12 is provided at the top of the receiving frame 11. A camera 13 is installed in the middle section of the installation plate 12.

[0040] Three marker points 15 are provided at the bottom of the inner wall of the receiving frame 11, and two laser spots 14 are projected by the laser pointer 10 at the bottom of the inner wall of the receiving frame 11.

[0041] The first camera 13 is fixed one meter above the center of the receiving frame 11. The first camera 13 captures the marker point 15 and the laser spot 14 in the receiving frame 11.

[0042] An automated continuous detection method for deformation of coal mine shafts, the method comprising the following steps;

[0043] Assembly process: The bottom of cage 1 is connected to the top of gimbal 6, gimbal 7, and gimbal 8 from left to right. The bottom of gimbal 6 and gimbal 8 are connected to the top of laser pointer 10. The bottom of gimbal 7 is connected to the top of laser radar scanner 9. Camera 3 and encoder 5 are installed on the front of cage 1. Receiver frame 11 is placed at the bottom of mine shaft 2. Mounting plate 12 is set on the top of receiver frame 11. Camera 13 is installed in the middle of mounting plate 12.

[0044] Operation process: First, the cage 1 is raised from the bottom of the mine shaft 2. During the ascent, the shaft wall is scanned and point cloud data is saved until the cage 1 reaches the shaft opening. At the same time, during the ascent, the lidar scanner 9 collects cross-sectional point cloud data of the mine shaft 2, the encoder 5 measures the vertical distance of the cross-section of the mine shaft 2, and the laser pointer 10 projects two laser spots 14 onto the receiving frame 11. Then, the second camera 3 records video in real time to record the vertical distance data, which corresponds to the cross-sectional point cloud data with timestamps. The first camera 13 records video in real time to record and read the coordinates of the laser spots 14.

[0045] Data processing technology: The acquired data is sent to the back-end terminal. The back-end terminal calculates the center coordinates of the point cloud of each cross section based on the acquired data. Finally, the tilt change of the well wall of mine 2 is detected by subtracting the center coordinates between cross sections.

[0046] The encoder 5 measures the vertical distance of the mine shaft 2 section by installing the encoder 5 on the cage 1 and the mine shaft 2, connecting it to the counter 4, which can display the vertical movement distance of the cage 1 in real time, and using the second camera 3 to record video of the counter 4, so that the depth of the cage 1 can be corresponding to the shooting time.

[0047] The cross-sectional point cloud refers to the set of well wall points obtained by the lidar scanner 9 scanning a circle on the horizontal plane at a preset depth in the mine 2.

[0048] The method of detecting the tilt change of the mine wall 2 by subtracting the center coordinates between cross sections is as follows: the corresponding frame photos are processed to obtain the spot coordinates, the quadrant angle of the spot connection line and the core coordinates of the lidar scanner 9. The difference between these coordinates and the initial coordinates and quadrant angle of the orientation reference is obtained to obtain the deformation of the cage passage. The cross section point cloud of the vertical distance is translated and rotated according to the deformation of the cage passage to correct the measurement error of the mine wall caused by the horizontal movement and rotation of the cage 1. Finally, the center coordinates of each cross section point cloud are obtained by the least squares method, and the tilt value of the mine wall 2 is obtained by subtracting the center coordinates between cross sections.

[0049] The cross-sectional point cloud acquired by the lidar scanner 9 includes angle information and timestamps.

[0050] The specific method for reading the coordinates of the laser spot 14 is as follows: a program is written using the OpenCV library in Python to extract the center coordinates of the laser spot in the captured image, which are the planar coordinates of the orientation baseline.

[0051] The extraction of the center coordinates of laser spot 14 in the captured photo is as follows: First, the cv2.GaussianBlur function is used to filter the photo and remove noise pixels. Then, the cvtColor function is used to process the image into grayscale. Next, the threshold function is used to set the grayscale threshold and binarize the image. Then, the findContours function is used to identify the edge of the spot and the center of the control point in the photo. Finally, the four-parameter coordinate transformation method is used, and the pixel coordinates of the center of the spot are transformed to the independent coordinate system of the control point based on the pixel coordinates of the control point center and the center of the spot. This completes the extraction of the center coordinates of laser spot 14 in the captured photo.

[0052] The principle of this invention is explained as follows: By using the corresponding video recording time points of camera 3 and camera 13 and the scanner timestamp, the horizontal movement and rotation value measurement, point cloud acquisition, and vertical distance measurement of cage 1 are realized simultaneously. The cross-sectional points of the well shaft are collected by using a laser radar scanner to scan 360 degrees, making the operation more convenient and eliminating the need to adjust the direction of the rangefinder on site.

[0053] Example 1:

[0054] An automated continuous detection device for coal mine shaft deformation includes a cage 1, a mine shaft 2, an encoder 5, a lidar scanner 9, and a laser pointer 10. The cage 1 is installed inside the mine shaft 2. A second camera 3 and a counter 4 are sequentially mounted on the front of the cage 1. The right side of the cage 1 is connected to the left side of the encoder 5. The right-side pulley of the encoder 5 slides against the inner wall of the mine shaft 2. The counter 4 is electrically connected to the encoder 5. The bottom of the cage 1 is sequentially connected from left to right to the tops of a first gimbal 6, a second gimbal 7, and a third gimbal 8. The bottoms of the first gimbal 6 and the third gimbal 8 are both connected to the laser pointer 10. The top of the receiver is connected to the top of the receiver 11, and the bottom of the second gimbal 7 is connected to the top of the laser radar scanner 9. The distance between the two laser pointers 10 is greater than the width of the second gimbal 7 that mounts the laser radar scanner 9. To ensure that the laser point is projected into the receiver 11, the distance between the two laser pointers 10 is less than the width of the laser receiver 10. Three marker points 15 are set on the bottom of the inner wall of the receiver 11, and two laser spots 14 are projected onto the bottom of the inner wall of the receiver 11 through the laser pointers 10. The first camera 13 is fixed one meter above the center of the receiver 11, and the first camera 13 captures the marker points 15 and the laser spots 14 in the receiver 11.

[0055] A method for using the aforementioned automated continuous detection device for coal mine shaft deformation includes an assembly process: the bottom of the cage 1 is connected from left to right to the top of the first gimbal 6, the second gimbal 7, and the third gimbal 8; the bottoms of the first gimbal 6 and the third gimbal 8 are both connected to the top of the laser pointer 10; the bottom of the second gimbal 7 is connected to the top of the lidar scanner 9; and a second camera 3 and an encoder 5 are installed on the front of the cage 1; a receiving frame 11 is placed at the bottom of the mine shaft 2; a mounting plate 12 is provided on the top of the receiving frame 11; and a first camera 13 is installed in the middle section of the mounting plate 12.

[0056] Operation process: First, the cage 1 is raised from the bottom of the mine shaft 2. During the ascent, the shaft wall is scanned and point cloud data is saved until the cage 1 reaches the shaft opening. At the same time, during the ascent, the lidar scanner 9 collects cross-sectional point cloud data of the mine shaft 2, the encoder 5 measures the vertical distance of the cross-section of the mine shaft 2, and the laser pointer 10 projects two laser spots 14 onto the receiving frame 11. Then, the second camera 3 records video in real time to record the vertical distance data, which corresponds to the cross-sectional point cloud data with timestamps. The first camera 13 records video in real time to record and read the coordinates of the laser spots 14.

[0057] Data processing technology: The acquired data is sent to the back-end terminal. The back-end terminal calculates the center coordinates of the point cloud of each cross section based on the acquired data. Finally, the tilt change of the well wall of mine 2 is detected by subtracting the center coordinates between cross sections.

[0058] Example 2:

[0059] Example 2 is basically the same as Example 1, except that:

[0060] An automated continuous detection method for coal mine shaft deformation is proposed. This method calculates the center coordinates of the point cloud for each cross-section based on the least squares principle. At the start of the detection, cameras 1 (13) and 2 (3) are simultaneously activated and record video. The timestamp of the first scan is then matched with the camera recording time, achieving time synchronization between the three systems: the lidar scanner 9, the laser pointer 10, and the encoder 5. If camera recording is interrupted, it can be detected during the detection process. If the time is not synchronized, the detection results will be incorrect. Each shaft scan is performed twice, and the results are checked. If the time is not synchronized and the check fails, re-measurement is required. After the measurement data is obtained, the cage 1 is lowered from the shaft opening again to scan the shaft wall. The data obtained during descent is used to check the data obtained during ascent.

[0061] Example 3:

[0062] Example 3 is basically the same as Example 2, except that:

[0063] An automated continuous detection device and method for coal mine shaft deformation, wherein the encoder 5 measures the vertical distance of the mine shaft 2 section specifically as follows: an encoder 5 is installed on the cage 1 and the mine shaft 2, and a counter 4 is connected to it. The vertical movement distance of the cage 1 can be displayed in real time. A second camera 3 is used to record video on the counter 4. The depth of the cage 1 can be correlated with the recording time. The depth of the cage 1 is measured by the encoder, and the data of the encoder 5 is time-correlated. That is, the cage 1 has a unique corresponding time at each depth. Each point has a timestamp, so the time of measurement at that point can be known. Corresponding to the time of the encoder 5, it can be known at which depth in the shaft the point was measured.

[0064] Example 4:

[0065] Example 4 is basically the same as Example 3, except that:

[0066] An automated continuous detection device and method for coal mine shaft deformation is disclosed. The cross-sectional point cloud refers to the set of points on the shaft wall obtained by a lidar scanner 9 scanning a circle at a preset depth on a horizontal plane. The method for detecting the tilt change of the shaft wall based on the difference between the center coordinates of the cross-sections specifically involves: processing corresponding frame images to obtain the spot coordinates, the quadrant angle of the spot connection line, and the core coordinates of the lidar scanner 9; subtracting these from the initial coordinates and quadrant angle of the orientation reference to obtain the deformation of the shaft; and then translating and rotating the cross-sectional point cloud based on the deformation of the shaft to correct the deformation. Due to the measurement errors of the mine wall caused by the horizontal movement and rotation of cage 1, the center coordinates of each cross-sectional point cloud are finally obtained by the least squares method. The inclination value of the mine wall 2 is obtained by subtracting the center coordinates between cross-sections. The cross-sectional point cloud acquired by the laser radar scanner 9 includes angle information and timestamp. Cage 1 may rotate horizontally during the ascent, which will cause the obtained cross-sectional point cloud to also rotate horizontally. In order to obtain the corresponding true position of the cross-sectional point, it is necessary to rotate the point cloud according to the horizontal rotation angle measured by the laser criterion. Each point has angle information to facilitate the rotation operation.

[0067] Example 5:

[0068] Example 5 is basically the same as Example 4, except that:

[0069] An automated continuous detection device and method for coal mine shaft deformation is disclosed. The method uses the OpenCV library in Python to write a program to extract the center coordinates of a laser spot in a captured photograph, which are the planar coordinates of the orientation baseline. First, the `cv2.GaussianBlur` function is used to filter the photograph and remove noisy pixels. Then, the `cvtColor` function is used to process the image into grayscale. Next, the `threshold` function is used to set a grayscale threshold to binarize the image. Then, the `findContours` function is used to identify the edge of the laser spot and the center of the control point in the photograph. Finally, a four-parameter coordinate transformation method is used, and based on the pixel coordinates of the control point center and the laser spot center, the pixel coordinates of the laser spot center are transformed to the independent coordinate system of the control point, thus completing the extraction of the center coordinates of the laser spot 14 in the captured photograph.

[0070] In the grayscale processed image, the grayscale of laser spot 14 differs from that of the background of the receiving plate. Binarization sets a threshold based on this grayscale difference, making the grayscale of laser spot 14 0, while the grayscale of the area outside laser spot 14 becomes 225. This means that laser spot 14 appears white, while other objects appear black, facilitating the subsequent identification and extraction of the laser spot outline and simplifying data processing. Before coordinate transformation, the coordinates of the center of laser spot 14 are pixel coordinates, indicating the row and column position of the center pixel within the entire image. In contrast, the independent coordinate system of the control points is in meters. The transformation from pixel coordinates to independent coordinates converts the coordinates of laser spot 14 from those expressed in pixel rows and columns to those in meters, giving the subsequent calculations a meaningful distance.

[0071] The cage 1 is raised from the bottom of the mine shaft 2. During the ascent, the shaft wall is scanned and point cloud data is saved until the cage 1 reaches the shaft opening. After measuring the data, the cage 1 is lowered from the shaft opening again to scan the shaft wall. The data obtained during the descent is used to verify the data during the ascent. There is no need for manual control or recording of the cage's running distance. By matching the time point of the video recorded by the camera with the timestamp information in the scanner's point cloud data, all measurement work is synchronized. The cage 1 does not need to stop midway, thus realizing the automation and continuity of the entire detection process.

[0072] The above description is only a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. Any equivalent modifications or changes made by those skilled in the art based on the content disclosed in the present invention should be included within the scope of protection set forth in the claims.

Claims

1. An automated continuous detection device for deformation of coal mine shafts, characterized in that: The coal mine shaft deformation automatic continuous detection device includes a cage (1), a mine shaft (2), an encoder (5), a laser radar scanner (9) and a laser pointing instrument (10); The cage (1) is arranged in the mine shaft (2), the front of the cage (1) is sequentially provided with a second camera (3) and a counter (4), the right side of the cage (1) is connected with the left side of the encoder (5), the right side pulley of the encoder (5) is in sliding fit with the inner wall of the mine shaft (2), and the counter (4) is electrically connected with the encoder (5); The bottom of the cage (1) is sequentially connected with the top of a first gimbal (6), a second gimbal (7) and a third gimbal (8) from left to right, the bottom of the first gimbal (6) and the third gimbal (8) are both connected with the top of the laser pointing instrument (10), and the bottom of the second gimbal (7) is connected with the top of the laser radar scanner (9); The inner wall bottom of the mine shaft (2) is provided with a receiving frame (11), the top of the receiving frame (11) is provided with a mounting plate (12), and the middle section of the mounting plate (12) is provided with a first camera (13); The use method of the coal mine shaft deformation automatic continuous detection device is as follows, and the method comprises the following steps: Assembly process: the bottom of the cage (1) is sequentially connected with the top of the first gimbal (6), the second gimbal (7) and the third gimbal (8) from left to right, the bottom of the first gimbal (6) and the third gimbal (8) are both connected with the top of the laser pointing instrument (10), the bottom of the second gimbal (7) is connected with the top of the laser radar scanner (9), a second camera (3) is arranged on the front of the cage (1), and an encoder (5) is arranged; the receiving frame (11) is arranged at the bottom of the mine shaft (2), the top of the receiving frame (11) is provided with a mounting plate (12), and the middle section of the mounting plate (12) is provided with a first camera (13); Running process: first, the cage (1) is lifted from the bottom of the mine shaft (2), the shaft wall is scanned in the lifting process, and point cloud data is saved, until the cage (1) reaches the wellhead; at the same time, in the process of lifting, the laser radar scanner (9) collects the section point cloud of the mine shaft (2), the encoder (5) measures the section vertical distance of the mine shaft (2), and the laser pointing instrument (10) projects two laser spots (14) on the receiving frame (11); then, the second camera (3) records the video to record the vertical distance data in real time, which corresponds to the section point cloud data with a time stamp, and the first camera (13) records the video to record and read the coordinates of the laser spot (14) in real time; The inner wall bottom of the receiving frame (11) is provided with three mark points (15), and the inner wall bottom of the receiving frame (11) is projected with two laser spots (14) by the laser pointing instrument (10); The first camera (13) is fixed one meter above the center of the receiving frame (11), and the first camera (13) shoots the mark points (15) and the laser spots (14) in the receiving frame (11); Data processing process: the obtained data is sent to a background terminal, the background terminal calculates the center coordinates of each section point cloud according to the obtained data, and finally detects the inclination change of the shaft wall of the mine shaft (2) by the difference between the center coordinates of the sections. The encoder (5) is installed on the cage (1) and the mine (2), and the counter (4) is connected, so that the vertical movement distance of the cage (1) can be displayed in real time, and the second camera (3) is used to record the counter (4), so that the depth of the cage (1) can be corresponded through the shooting time; According to the least square principle, the center coordinates of each cross section point cloud are fitted and calculated; at the beginning of detection, the first camera (13) and the second camera (3) are started at the same time to record, and then the first scanning time stamp is corresponded with the camera recording time, so that the time synchronization of the three systems composed of the laser radar scanner (9), the laser pointing instrument (10) and the encoder (5) is realized; if the camera recording is interrupted, then the time is found to be out of synchronization during the detection process, so that the detection result will be incorrect; the detection and scanning of the shaft are carried out twice each time, and the results of the two times are checked; if the time is out of synchronization, the checking fails, and the measurement needs to be re-measured; after the measurement data, the cage (1) is lowered from the shaft mouth again to scan the shaft wall, and the data obtained by lowering is used to check the data obtained by rising.

2. The coal mine shaft deformation automatic continuous detection device according to claim 1, characterized in that: The cross section point cloud refers to that the laser radar scanner (9) scans a circle on the horizontal plane at a preset depth of the mine (2), and the point set of the shaft wall of the circle is obtained as the cross section point cloud.

3. The coal mine shaft deformation automatic continuous detection device according to claim 2, characterized in that: The difference between the center coordinates of the cross sections is used to detect the inclination change of the shaft wall of the mine (2), specifically: the spot coordinates, the quadrant angle of the spot connecting line and the core coordinates of the laser radar scanner (9) are obtained by processing the corresponding frame photos, the difference between the initial coordinates and the quadrant angle of the directional reference and the core coordinates of the directional reference is obtained, the deformation of the cage is obtained, and the cross section point cloud of the vertical distance is translated and rotated according to the deformation of the cage, so as to correct the error of the measurement of the shaft wall caused by the horizontal movement and rotation of the cage (1), and finally the center coordinates of each cross section point cloud are obtained by the least square method, and the inclination value of the shaft wall of the mine (2) is obtained by the difference between the center coordinates of the cross sections.

4. The coal mine shaft deformation automatic continuous detection device according to claim 2, characterized in that: The cross section point cloud obtained by the laser radar scanner (9) includes angle information and time stamp.

5. The coal mine shaft deformation automatic continuous detection device according to claim 1, characterized in that: The reading of the laser spot (14) coordinates specifically refers to that the program using the opencv library of python language is used to extract the center coordinates of the laser spot (14) in the photographed photo, that is, the plane coordinates of the directional reference line.

6. The coal mine shaft deformation automatic continuous detection device according to claim 5, characterized in that: The extraction of the center coordinates of the laser spot (14) in the photographed photo specifically refers to that the cv2.GaussianBlur function is used to filter the photo to remove noise pixels, the cv2.threshold function is used to set the gray threshold to binarize the image, and then the findContours function is used to identify the spot edge and control point center in the photo, finally, the four-parameter coordinate transformation method is used, and the pixel coordinates of the spot center are converted to the independent coordinate system of the control point center, that is, the extraction of the center coordinates of the laser spot (14) in the photographed photo is completed.

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