Coal gangue recognition and coal flow monitoring integrated intelligent system and application thereof

Abstract

The present application relates to a kind of coal gangue recognition and coal flow monitoring integrated intelligent system and its application, belong to coal gangue recognition and coal flow monitoring technical field.System includes hydraulic support, scraper conveyor, coal gangue recognition system, coal flow monitoring system and control system, wherein, hydraulic support one end below is provided with scraper conveyor, and hydraulic support above the scraper conveyor is provided with coal gangue recognition system and coal flow monitoring system, and hydraulic support, scraper conveyor, coal gangue recognition system and coal flow monitoring system are all connected with control system.The present application improves the precision of coal gangue recognition, prevents scraper conveyor empty load or overload at the same time, and guarantees the safety and reliability of top coal process.

Description

Technical Field

[0001] This invention relates to an integrated intelligent system for coal gangue identification and coal flow monitoring and its application, belonging to the field of coal gangue identification and coal flow monitoring technology. Background Technology

[0002] Top coal caving and coal-gangue identification is one of the key technologies driving the development of intelligent control in fully mechanized top coal caving mining. Currently, the level of intelligence in top coal caving is low, making automated control of the coal caving mechanism impossible and requiring operator intervention. Methods for identifying coal-gangue based on vibration, sound, and pressure cannot determine the coal-gangue mixing ratio, and the harsh and complex environment of mines, including darkness, noise, and dust, results in low accuracy for image-based coal-gangue identification.

[0003] Coal flow monitoring of scraper conveyors is an important technical means to improve the efficiency of coal production and transportation. Excessive coal flow can easily cause wear and damage to the scraper conveyor, while insufficient coal flow can lead to energy waste. In order to achieve intelligent perception of the scraper conveyor's status and precise speed control, it is necessary to monitor the amount of coal transported in real time, thereby minimizing the risk of overloading or idling of the belt conveyor.

[0004] In the prior art, Chinese patent document CN111764902B discloses an intelligent coal release control method for fully mechanized top coal caving longwall faces. This method mainly includes: establishing a geological model coordinate system for the longwall face; obtaining top coal thickness information; establishing a three-dimensional geological model and a numerical calculation model of the top coal thickness variation; using information on the top coal in the middle of the longwall face exposed during coal cutting to perform advance correction on the three-dimensional geological model and the numerical calculation model; calculating and determining the theoretical release amount of top coal; using a coal quantity scanning device and a coal and gangue image recognition device to detect the release amount of top coal and the release of top coal and gangue; and finally determining the optimal coal release opening closing time by comparing the theoretical release amount with the actual release amount and the release of gangue. This method obtains the top coal thickness through a coal quantity scanning device, but the coal distribution is scattered, and simple scanning is unlikely to obtain complete coal quantity information. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an integrated intelligent system for coal gangue identification and coal flow monitoring, which improves the accuracy of coal gangue identification while preventing the scraper conveyor from being unloaded or overloaded, thus ensuring the safety and reliability of the top coal caving process.

[0006] The present invention also provides an application of the above-mentioned integrated intelligent system for coal gangue identification and coal flow monitoring.

[0007] The technical solution of the present invention is as follows:

[0008] An integrated intelligent system for coal gangue identification and coal flow monitoring includes a hydraulic support, a scraper conveyor, a coal gangue identification system, a coal flow monitoring system, and a control system.

[0009] A scraper conveyor is installed below one end of the hydraulic support. A coal gangue identification system and a coal flow monitoring system are installed on the hydraulic support above the scraper conveyor. The hydraulic support, scraper conveyor, coal gangue identification system and coal flow monitoring system are all connected to a control system.

[0010] According to a preferred embodiment of the present invention, the coal gangue identification system includes a coal gangue identification camera and a first rotating platform. The first rotating platform is fixed on a hydraulic support above the scraper conveyor and the coal gangue identification camera is mounted on the first rotating platform.

[0011] According to a preferred embodiment of the present invention, the coal gangue identification system further includes supplementary lighting and an abnormality alarm device, with supplementary lighting and an abnormality alarm device respectively installed on the hydraulic support below the first rotating platform.

[0012] According to a preferred embodiment of the present invention, the coal flow monitoring system includes a second rotating platform, a coal flow monitoring camera, a third rotating platform, and a line laser. The second rotating platform is mounted on a hydraulic support above the coal gangue identification system, and the coal flow monitoring camera is mounted on the second rotating platform. The third rotating platform is mounted on a hydraulic support above the scraper conveyor, and the line laser is mounted on the third rotating platform.

[0013] According to a preferred embodiment of the present invention, the first and third rotating platforms are existing single-axis turntables. The second rotating platform includes a gimbal mounting plate, a gimbal body, a first rotating mechanism, a second rotating mechanism, and a third rotating mechanism. The gimbal body is disposed on the lower side of the gimbal mounting plate, and the third rotating mechanism is disposed on the gimbal body. Rolling supports are disposed on both sides of the third rotating mechanism. The first rotating mechanism and the second rotating mechanism are disposed in the two rolling supports respectively. The first rotating mechanism and the second rotating mechanism hold a coal flow monitoring camera.

[0014] According to a further preferred embodiment of the present invention, the first rotating mechanism includes a housing, a sway base, a bushing, a set screw, a rocker arm, a connecting rod, a crank, and a motor. The sway base is movably mounted on one side of the housing via a bearing. A set screw is fixedly mounted on the lower side of the sway base. A bushing is fitted onto the outer side of the set screw via a deep groove ball bearing. The bushing is fixed inside the housing. The bottom of the set screw is connected to the output shaft of the motor via the rocker arm, the connecting rod, and the crank. The motor is fixed inside the housing. The motor drives the sway base to rotate via the rocker arm, the connecting rod, and the crank, reducing the transmission ratio. Compared to a motor directly connected to the sway base, the adjustment accuracy is higher. The third rotating mechanism has the same structure as the first rotating mechanism. The second rotating mechanism has the same structure as the first rotating mechanism or only retains the housing, the sway base, the bushing, and the set screw, without a motor or other drive mechanism.

[0015] According to a preferred embodiment of the present invention, the control system includes a data conversion module, a controller A, an IoT module ESP8266, a host computer, a controller B, and a controller C. The coal gangue identification system and the coal flow monitoring system are both connected to the data conversion module. The data conversion module is connected to the host computer through the controller A and the IoT module ESP8266. The controller A simultaneously controls the coal gangue identification system and the coal flow monitoring system. The host computer is connected to a hydraulic support through the controller B, and the host computer is connected to a scraper conveyor through the controller C.

[0016] The application steps of the above-mentioned integrated intelligent system for coal gangue identification and coal flow monitoring are as follows:

[0017] ① The first rotating platform rotates so that the coal gangue identification camera faces the central axis of the scraper conveyor. The second and third rotating platforms rotate so that the line laser shines on the coal pile to form a complete outline and projects it into the coal flow monitoring camera, thus realizing the initialization of the integrated intelligent system for coal gangue identification and coal flow monitoring.

[0018] ②The scraper conveyor is running, and the hydraulic supports begin to discharge coal;

[0019] ③ The coal gangue identification camera and the supplementary light are turned on simultaneously every 0.1s to collect image information of the scraper conveyor and the surface of the coal flow. The coal flow monitoring camera is turned on every 0.1s to collect laser spot images of the coal pile. The time interval between the turn-on of the coal gangue identification camera and the coal flow monitoring camera is 0.05s to prevent mutual interference between the image quality of the two systems. The data conversion module converts the coal gangue image information and the laser spot image into digital signals and sends them to controller A. Controller A packages the data into JSON format and sends it to the IoT module ESP8266 via serial port. The IoT module ESP8266 pushes the entire data packet to the MQTT message queue via Wi-Fi for data extraction. The MQTT rule engine extracts all the data, packages it, and sends it to the host computer.

[0020] ④ The host computer reads the image information of the scraper conveyor and the coal flow surface in real time, calculates the gangue content, and divides the sample into three intervals: allowable, shut-off, and shut-off. When the gangue content reaches the shut-off interval, the control decision is fed back to controller B, which controls the hydraulic support to stop coal discharge. When the gangue content suddenly reaches the shut-off interval without transition, controller B controls the abnormal alarm device to be activated, stops coal discharge, and repairs the equipment.

[0021] ⑤ The host computer reads the laser spot image of the coal pile, uses morphological processing methods to repair the breaks in the laser spot, making the laser outline form a complete connected region, and uses the geometric center method to extract the center line of the connected region. By comparing it with the reference center line of the scraper conveyor under no-load conditions, the cross-sectional area of ​​the coal pile at the current time point is obtained. According to the coal flow monitoring requirements, when the scraper conveyor is overloaded, the size of the coal discharge port of the hydraulic support and the speed of the scraper conveyor are controlled.

[0022] According to a preferred embodiment of the present invention, the specific steps for coal flow monitoring in step ⑤ are as follows:

[0023] (1) The line laser is projected from point D at an angle perpendicular to the installation plane. The intersection of the perpendicular line from the rotation point O1 of the coal flow monitoring camera to the reference plane and the hydraulic support is point O. Point A1 is the projection point on the reference plane, and the corresponding spot on the image sensor inside the coal flow monitoring camera is point A. h is the actual height of the object being measured. The line laser is projected onto the surface of the object at the same angle, and the corresponding spot on the image sensor is point B. O1C1 is the straight line where the optical axis of the coal flow monitoring camera is located. The points through which O1C1 passes through the image sensor and the lens are points C and O2, respectively. O1C1 is perpendicular to the line laser.

[0024] Let β be the angle between the hydraulic support at the line laser mounting location and the vertical plane. From geometric relationships, we know that:

[0025] O2C1=OD-OO1·cosβ-O1O2

[0026] Since ΔO2A1B1~ΔO2AB, according to the principle of triangle similarity, If the relationship is true, then:

[0027]

[0028] Therefore, the height of the target object can be calculated using the following formula:

[0029] h=A1B1·sinβ

[0030] Right now

[0031] In the formula, AB is the amount of light spot movement in camera imaging, and O2C, β, OD, OO1, O1O2 are the fixed amounts of the equipment when it is arranged according to the working conditions.

[0032] (2) Linear laser projection is used, and the projected light spot forms a linear light spot on the object to be measured. The projection height of each point on the laser spot is calculated through step (1), and the height of each point is accumulated using Riemann summation to obtain the cross-sectional area of ​​the contour projection. Since the coordinates of each pixel in the digital image are discrete, the number of pixels is determined by the camera resolution. Therefore, the discrete expression for the pixel area of ​​the coal pile cross-section is:

[0033]

[0034] In the formula, n represents the number of pixels occupied by the laser line, and M and N represent the horizontal coordinates of the pixels represented by the start and end points of the laser line, respectively.

[0035] The actual cross-sectional area of ​​the coal pile is then expressed as:

[0036]

[0037] In the formula, K is the coordinate transformation coefficient of the image measurement system.

[0038] The beneficial effects of this invention are as follows:

[0039] 1. This invention uses three rotating mechanisms to rotate the coal gangue identification camera, the coal flow monitoring camera, and the line laser to a set position to extract higher-resolution image information, while simultaneously performing coal gangue identification and coal flow monitoring during the top coal caving process.

[0040] 2. This invention proposes a three-section coal release decision method: release zone, shutdown zone, and shutdown zone, each corresponding to a different system control strategy. This method can ensure the orderly progress of the coal release process. When the system detects an abnormal gangue content, it can activate an abnormal situation alarm device.

[0041] 3. This invention utilizes the principle of laser triangulation to measure coal flow during the coal discharge process. It proposes a reasonable arrangement method for coal flow monitoring cameras and line lasers suitable for top coal discharge, a laser stripe image processing method, and a formula for calculating the cross-sectional area of ​​the coal pile.

[0042] 4. The present invention has designed a second rotating platform suitable for coal flow monitoring cameras, which can achieve dual-axis rotation and, in conjunction with a line laser, better acquire laser spot images of the cross-sectional area of ​​the coal pile. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the control process of the present invention;

[0044] Figure 2 This is a schematic diagram of the hydraulic support structure of the present invention;

[0045] Figure 3 This is a schematic diagram of the installation structure of the coal gangue identification system and coal flow monitoring system of the present invention;

[0046] Figure 4 This is a front view schematic diagram of the second rotating platform structure of the present invention;

[0047] Figure 5 This is a side view of the second rotating platform structure of the present invention;

[0048] Figure 6 This is a schematic cross-sectional view of the first rotating mechanism structure of the present invention;

[0049] Figure 7 This is a top cross-sectional view of the first rotating mechanism structure of the present invention;

[0050] Figure 8 This is a cross-sectional schematic diagram of the second rotating mechanism in Embodiment 1 of the present invention;

[0051] Figure 9 This is a schematic diagram of the application process of the present invention;

[0052] Figure 10 This is a schematic diagram of the coal gangue identification process of the present invention;

[0053] Figure 11 This is a schematic diagram illustrating the principle of coal gangue identification in this invention.

[0054] Figure 12 This is a flowchart of the coal flow monitoring process of the present invention.

[0055] The components include: 1. Coal and gangue identification camera; 2. First rotating platform; 3. Supplemental lighting; 4. Abnormal alarm device; 5. Coal flow monitoring camera; 6. Second rotating platform; 7. Line laser; 8. Third rotating platform; 9. Scraper conveyor; 10. Top beam; 11. Shield beam; 12. Front connecting rod; 13. Hydraulic system; 14. Tail beam; 15. Image sensor; 16. Lens; 17. Measured object; 18. Reference plane.

[0056] 61. First rotating mechanism; 62. Second rotating mechanism; 63. Third rotating mechanism; 64. Gimbal body; 65. Roll support; 66. Gimbal mounting plate;

[0057] 611. Oscillating base; 612. Housing; 613. Bushing; 614. Set screw; 615. Rocker arm; 616. Connecting rod; 617. Crank; 618. Motor; 619. Deep groove ball bearing. Detailed Implementation

[0058] The present invention will be further described below with reference to the embodiments and accompanying drawings, but is not limited thereto.

[0059] Example 1:

[0060] like Figure 1-12 As shown, this embodiment provides an integrated intelligent system for coal gangue identification and coal flow monitoring, including a hydraulic support, a scraper conveyor, a coal gangue identification system, a coal flow monitoring system, and a control system.

[0061] A scraper conveyor 9 is installed below one end of the hydraulic support. A coal and gangue identification system and a coal flow monitoring system are installed on the hydraulic support above the scraper conveyor 9. The hydraulic support, scraper conveyor 9, coal and gangue identification system, and coal flow monitoring system are all connected to a control system. The hydraulic support is a conventionally used equipment and includes a top beam 10, a shield beam 11, a front connecting rod 12, a hydraulic system 13, and a tail beam 14.

[0062] The coal gangue identification system includes a coal gangue identification camera 1 and a first rotating platform 2. The first rotating platform 2 is fixed on the front connecting rod 12 of the hydraulic support above the scraper conveyor. The coal gangue identification camera 1 is installed on the first rotating platform 2.

[0063] The coal gangue identification system also includes supplementary lights 3 and abnormal alarm devices 4. Supplementary lights 3 and abnormal alarm devices 4 are respectively installed on the front connecting rod 12 below the first rotating platform 2.

[0064] The coal flow monitoring system includes a second rotating platform 6, a coal flow monitoring camera 5, a third rotating platform 8, and a line laser 7. The second rotating platform 6 is installed on the front connecting rod 12 above the coal gangue identification system. The coal flow monitoring camera 5 is installed on the second rotating platform 6. The third rotating platform 8 is installed on the tail beam 14 of the hydraulic support above the scraper conveyor 9. The line laser 7 is installed on the third rotating platform 8.

[0065] The first rotating platform 2 and the third rotating platform 8 are existing single-axis turntables. The second rotating platform 6 includes a gimbal mounting plate 66, a gimbal body 64, a first rotating mechanism 61, a second rotating mechanism 62, and a third rotating mechanism 63. The gimbal body 64 is located on the lower side of the gimbal mounting plate 66, and the third rotating mechanism 63 is located on the gimbal body 64. Roller supports 65 are respectively located on both sides of the third rotating mechanism 63. The first rotating mechanism 61 and the second rotating mechanism 62 are respectively located in the two roller supports 65. The first rotating mechanism 61 and the second rotating mechanism 62 hold the coal flow monitoring camera 5.

[0066] The first rotating mechanism 61 includes a housing 612, a sway base 611, a bushing 613, a set screw 614, a rocker arm 615, a connecting rod 616, a crank 617, and a motor 618. The sway base 611 is movably mounted on one side of the housing 612 via bearings. A set screw 614 is fixedly mounted on the lower side of the sway base 611. A bushing 613 is fitted onto the outside of the set screw 614 via a deep groove ball bearing 619. The bushing 613 is fixed inside the housing 612. The bottom of the set screw 614 is connected to the motor output shaft via the rocker arm 615, the connecting rod 616, and the crank 617. The motor 618 is fixed inside the housing 612. The motor drives the sway base to rotate via the rocker arm, connecting rod, and crank, reducing the transmission ratio. Compared to a direct connection between the motor and the sway base, this results in higher adjustment accuracy. The third rotating mechanism has the same structure as the first rotating mechanism. The second rotating mechanism only retains the housing, sway base, bushing, and set screw, excluding the motor and other drive mechanisms. Figure 8 As shown.

[0067] The control system includes a data conversion module, controller A, an IoT module ESP8266, a host computer, controller B, and controller C. The coal gangue identification system and the coal flow monitoring system are both connected to the data conversion module. The data conversion module is connected to the host computer through controller A and the IoT module ESP8266. Controller A controls both the coal gangue identification system and the coal flow monitoring system. The host computer is connected to the hydraulic support through controller B and to the scraper conveyor through controller C. The host computer contains a coal gangue identification module and a coal flow monitoring module, which are used for coal gangue identification and coal flow monitoring, respectively.

[0068] The application steps of the above-mentioned integrated intelligent system for coal gangue identification and coal flow monitoring are as follows:

[0069] ① The first rotating platform rotates so that the coal gangue identification camera faces the central axis of the scraper conveyor. The second and third rotating platforms rotate so that the line laser shines on the coal pile to form a complete outline and projects it into the coal flow monitoring camera, thus realizing the initialization of the integrated intelligent system for coal gangue identification and coal flow monitoring.

[0070] ②The scraper conveyor is running, and the hydraulic supports begin to discharge coal;

[0071] ③ The coal gangue identification camera and the supplementary light are turned on simultaneously every 0.1s to collect image information of the scraper conveyor and the surface of the coal flow. The coal flow monitoring camera is turned on every 0.1s to collect laser spot images of the coal pile. The time interval between the turn-on of the coal gangue identification camera and the coal flow monitoring camera is 0.05s to prevent mutual interference between the image quality of the two systems. The data conversion module converts the coal gangue image information and the laser spot image into digital signals and sends them to controller A. Controller A packages the data into JSON format and sends it to the IoT module ESP8266 via serial port. The IoT module ESP8266 pushes the entire data packet to the MQTT message queue via Wi-Fi for data extraction. The MQTT rule engine extracts all the data, packages it, and sends it to the host computer.

[0072] ④ The host computer reads the image information of the scraper conveyor and the coal flow surface in real time, calculates the gangue content, and divides the sample into three intervals: allowable, shut-off, and shut-off. When the gangue content reaches the shut-off interval, the control decision is fed back to controller B, which controls the hydraulic support to stop coal discharge. When the gangue content suddenly reaches the shut-off interval without transition, controller B controls the abnormal alarm device to be activated, stops coal discharge, and repairs the equipment.

[0073] ⑤ The host computer reads the laser spot image of the coal pile, uses morphological processing methods to repair the breaks in the laser spot, making the laser outline form a complete connected region, and uses the geometric center method to extract the center line of the connected region. By comparing it with the reference center line of the scraper conveyor under no-load conditions, the cross-sectional area of ​​the coal pile at the current time point is obtained. According to the coal flow monitoring requirements, when the scraper conveyor is overloaded, the size of the coal discharge port of the hydraulic support and the speed of the scraper conveyor are controlled.

[0074] The steps for identifying coal gangue are as follows:

[0075] A coal gangue identification model was built using Python and OpenCV. First, image information of the scraper conveyor and the coal flow surface was read. The images were binarized and Gaussian filtered to obtain the edge image. Then, a morphological method was used to perform a dilation-erosion closing operation on the image to fill holes caused by pixel inhomogeneity. Second, a color range for the gangue was defined, and a pixel mask of the target color was obtained by applying a set color threshold. A bitwise AND operation was performed on the foreground mask to obtain the processed image. Based on this, contour traversal and approximate estimation of the gangue were performed, and the total contour area in the image was calculated. Finally, the proportion of all gangue contour areas in the entire image was calculated to obtain the gangue content.

[0076] The specific coal gangue identification process is as follows:

[0077] Ⅰ. Use cv2.imread() to read images of the scraper conveyor and the surface of the coal flow;

[0078] II. Create a background modeler using the createBackgroundSubtractorMOG2() function in the cv2 library and apply it to the coal gangue image to obtain the foreground mask;

[0079] III. Use the threshold() and GaussianBlur() functions from the cv2 library to perform binarization and Gaussian filtering on the image, respectively.

[0080] IV. Use the morphologyEx() function to perform morphological closing operations on the binary image, set the range of gangue colors, and perform a bitwise AND operation on the processed image and the foreground mask to obtain the processed image.

[0081] V. Traverse the gangue image, detect all gangue contours in the image using the findContours() function, approximate the gangue contours using cv.approxPolyDP(), and obtain the contour area using cv.contourArea().

[0082] VI. Calculate the proportion of the outline area of ​​all gangue in the whole image to obtain the gangue area ratio, and thus estimate the gangue content.

[0083] VII. According to the relevant requirements for top coal caving, coal caving should be stopped when the gangue content reaches [x1, x2]. Therefore, a three-level coal caving decision-making method is proposed, which includes caving categories, shutdown categories, and shutdown categories.

[0084]

[0085] VIII. When the gangue content reaches [0, x1], the system continues to discharge coal; when the gangue content reaches [x1, x2], the hydraulic support stops discharging coal; when the gangue content reaches [x2, 1], the hydraulic support stops discharging coal and controls the abnormal alarm device to issue an abnormal alarm.

[0086] In step ⑤, the specific steps for coal flow monitoring are as follows:

[0087] (1) The line laser is projected from point D at an angle perpendicular to the installation plane. The point where the perpendicular line from the rotation point O1 of the coal flow monitoring camera to the reference plane 18 intersects with the hydraulic support is point O. Point A1 is the projection point on the reference plane, and the corresponding spot on the image sensor 15 inside the coal flow monitoring camera is point A. h is the actual height of the object 17 being measured. The line laser is projected onto the surface of the object at the same angle, and the corresponding spot on the image sensor 15 is point B. O1C1 is the straight line where the optical axis of the coal flow monitoring camera is located. The points where O1C1 passes through the image sensor 15 and the lens 16 are points C and O2, respectively. O1C1 is perpendicular to the line laser.

[0088] Let β be the angle between the hydraulic support at the line laser mounting location and the vertical plane. From geometric relationships, we know that:

[0089] O2C1=OD-OO1·cosβ-O1O2

[0090] Since ΔO2A1B1~ΔO2AB, according to the principle of triangle similarity, If the relationship is true, then:

[0091]

[0092] Therefore, the height of the target object can be calculated using the following formula:

[0093] h=A1B1·sinβ

[0094] Right now

[0095] In the formula, AB is the amount of light spot movement in camera imaging, and O2C, β, OD, OO1, O1O2 are the fixed amounts of the equipment when it is arranged according to the working conditions.

[0096] (2) Linear laser projection is used, and the projected light spot forms a linear light spot on the object to be measured. The projection height of each point on the laser spot is calculated through step (1), and the height of each point is accumulated using Riemann summation to obtain the cross-sectional area of ​​the contour projection. Since the coordinates of each pixel in the digital image are discrete, the number of pixels is determined by the camera resolution. Therefore, the discrete expression for the pixel area of ​​the coal pile cross-section is:

[0097]

[0098] In the formula, n represents the number of pixels occupied by the laser line, and M and N represent the horizontal coordinates of the pixels represented by the start and end points of the laser line, respectively.

[0099] The actual cross-sectional area of ​​the coal pile is then expressed as:

[0100]

[0101] In the formula, K is the coordinate transformation coefficient of the image measurement system.

[0102] It is worth noting that in practical applications, it is necessary to extract the laser spot image of the scraper conveyor under no-load conditions to determine the effective area range of the laser stripes in the image.

[0103] The coal flow monitoring module reads the laser spot image of the coal pile using the Image.open() function, calculates the coordinates of the upper left and lower right corners of the area to be cut, uses the Image.crop() function to cut the image, and employs a morphological processing algorithm to repair the laser spot breaks, forming a complete outline. The geometric center method is used to obtain the center line of the laser stripe, with the x-coordinate as the position and the y-coordinate as follows:

[0104]

[0105] In the formula, y max Let y be the ordinate of the upper boundary point of the laser stripe. min The vertical coordinate of the lower boundary point of the laser stripe is used. The discontinuity of the laser spot is repaired by connecting adjacent center lines end to end to form a complete center line. The center line of the laser spot image extracted every 0.1s under the coal transportation state is compared with the reference center line under the no-load state of the scraper conveyor to obtain the relative deformation amount AB of the laser spot of each pixel. Then, the cross-sectional area of ​​the coal pile is calculated according to the expression of the actual cross-sectional area of ​​the coal pile obtained above.

[0106] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made under the concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. An integrated intelligent system for coal gangue identification and coal flow monitoring, characterized in that, This includes hydraulic supports, scraper conveyors, coal and gangue identification systems, coal flow monitoring systems, and control systems. A scraper conveyor is installed below one end of the hydraulic support. A coal gangue identification system and a coal flow monitoring system are installed on the hydraulic support above the scraper conveyor. The hydraulic support, scraper conveyor, coal gangue identification system and coal flow monitoring system are all connected to a control system. The coal gangue identification system includes a coal gangue identification camera and a first rotating platform. The first rotating platform is fixed on a hydraulic support above the side of the scraper conveyor, and the coal gangue identification camera is installed on the first rotating platform. The coal flow monitoring system includes a second rotating platform, a coal flow monitoring camera, a third rotating platform, and a line laser. The second rotating platform is installed on the hydraulic support above the coal gangue identification system, and the coal flow monitoring camera is installed on the second rotating platform. The third rotating platform is installed on the hydraulic support above the scraper conveyor, and the line laser is installed on the third rotating platform. In use, the first rotating platform rotates so that the coal gangue identification camera is facing the central axis of the scraper conveyor. The second and third rotating platforms rotate so that the line laser shines on the coal pile to form a complete outline, which is then projected into the coal flow monitoring camera.

2. The integrated intelligent system for coal gangue identification and coal flow monitoring as described in claim 1, characterized in that, The coal gangue identification system also includes supplementary lighting and anomaly alarm devices. Supplementary lighting and anomaly alarm devices are respectively installed on the hydraulic supports under the first rotating platform.

3. The integrated intelligent system for coal gangue identification and coal flow monitoring as described in claim 2, characterized in that, The first and third rotating platforms are single-axis turntables. The second rotating platform includes a gimbal mounting plate, a gimbal body, a first rotating mechanism, a second rotating mechanism, and a third rotating mechanism. The gimbal body is located on the underside of the gimbal mounting plate, and the third rotating mechanism is located on the gimbal body. Roller supports are located on both sides of the third rotating mechanism. The first rotating mechanism and the second rotating mechanism are located in the two roller supports respectively. The first rotating mechanism and the second rotating mechanism hold a coal flow monitoring camera.

4. The integrated intelligent system for coal gangue identification and coal flow monitoring as described in claim 3, characterized in that, The first rotating mechanism includes a housing, a swaying base, a bushing, a set screw, a rocker arm, a connecting rod, a crank, and a motor. The swaying base is movably mounted on one side of the housing via a bearing. A set screw is fixedly mounted on the lower side of the swaying base. A bushing is fitted on the outside of the set screw via a deep groove ball bearing. The bushing is fixed inside the housing. The bottom of the set screw is connected to the motor output shaft via the rocker arm, connecting rod, and crank. The motor is fixed inside the housing. The third rotating mechanism has the same structure as the first rotating mechanism.

5. The integrated intelligent system for coal gangue identification and coal flow monitoring as described in claim 4, characterized in that, The control system includes a data conversion module, controller A, an IoT module ESP8266, a host computer, controller B, and controller C. The coal gangue identification system and the coal flow monitoring system are both connected to the data conversion module. The data conversion module is connected to the host computer through controller A and the IoT module ESP8266. Controller A controls both the coal gangue identification system and the coal flow monitoring system. The host computer is connected to the hydraulic support through controller B and to the scraper conveyor through controller C.

6. The application of the integrated intelligent system for coal gangue identification and coal flow monitoring as described in claim 5, characterized in that, The steps are as follows: ① The first rotating platform rotates so that the coal gangue identification camera faces the central axis of the scraper conveyor. The second and third rotating platforms rotate so that the line laser shines on the coal pile to form a complete outline and projects it into the coal flow monitoring camera, thus realizing the initialization of the integrated intelligent system for coal gangue identification and coal flow monitoring. ②The scraper conveyor starts operating, and the hydraulic supports begin discharging coal; ③ The coal gangue identification camera and the supplementary light are turned on simultaneously every 0.1s to collect image information of the scraper conveyor and the surface of the coal flow. The coal flow monitoring camera is turned on every 0.1s to collect laser spot images of the coal pile. The time interval between the turn-on of the coal gangue identification camera and the coal flow monitoring camera is 0.05s. The data conversion module converts the coal gangue image information and the laser spot image into digital signals and sends them to controller A. Controller A sends the entire data packet to the host computer through the IoT module ESP8266. ④ The host computer reads the image information of the scraper conveyor and the coal flow surface in real time, calculates the gangue content, and divides it into three intervals: dischargeable, shut-off, and shut-off. When the gangue content reaches the shut-off interval, the control decision is fed back to controller B, which controls the hydraulic support to stop discharging coal. When the gangue content suddenly reaches the shut-off interval without transition, controller B controls the abnormal alarm device to be activated, stops discharging coal, and repairs the equipment. ⑤ The host computer reads the laser spot image of the coal pile, obtains the cross-sectional area of ​​the coal pile at the current time point, and controls the size of the coal discharge port of the hydraulic support and the speed of the scraper conveyor when the scraper conveyor is overloaded, according to the coal flow monitoring requirements.

7. The application of the integrated intelligent system for coal gangue identification and coal flow monitoring as described in claim 6, characterized in that, In step ⑤, the specific steps for coal flow monitoring are as follows: (1) The line laser is projected from point D at an angle perpendicular to the installation plane. The intersection of the perpendicular line from the rotation point O1 of the coal flow monitoring camera to the reference plane and the hydraulic support is point O. Point A1 is the projection point on the reference plane. The corresponding spot on the image sensor inside the coal flow monitoring camera is point A. h is the actual height of the object being measured. The line laser is projected onto the surface of the object at the same angle at point B1. The corresponding spot on the image sensor is point B. O1C1 is the straight line where the optical axis of the coal flow monitoring camera is located. The points where O1C1 passes through the image sensor and the lens are points C and O2, respectively. O1C1 is perpendicular to the line laser. Let β be the angle between the hydraulic support at the line laser mounting location and the vertical plane. From geometric relationships, we know that: ； because According to the principle of similar triangles, If the relationship is true, then: ； Therefore, the height of the target object can be calculated using the following formula: ； Right now ; In the formula, AB represents the amount of light spot movement in the camera image. , OD, OO1, O1O2 are fixed quantities when the equipment is arranged according to the working conditions; (2) Using line beam laser projection, the projected light spot forms a linear light spot on the object to be measured. By calculating the projection height of each point on the laser spot in step (1), the discrete expression of the pixel area of ​​the coal pile cross section is obtained as follows: ； In the formula, n represents the number of pixels occupied by the laser line, and M and N represent the horizontal coordinates of the pixels represented by the start and end points of the laser line, respectively. The actual cross-sectional area of ​​the coal pile is then expressed as: ； In the formula, K is the coordinate transformation coefficient of the image measurement system.

Images