A method and system for monitoring underground belt coal flow

Abstract

The present invention provides a method and system for monitoring the coal flow of an underground belt. The system includes a belt conveyor mechanism, a belt conveyor drive drum, a belt conveyor drive motor, a belt conveyor frequency converter electric drive system, a power supply module, a belt electric control PLC system, a control host, an edge computer, and an explosion-proof high-definition camera. The method applied to the edge computer includes the following steps: obtaining the coal flow video captured by the explosion-proof high-definition camera in real time; using a coal flow monitoring discrimination algorithm model to analyze the image information of each target image within a unit time in the coal flow video, and determining the belt value and coal flow value of each target image; calculating and determining the coal flow load ratio according to the belt value and coal flow value of each target image, and sending it to the control host. Through the technical solution of the present invention, the problems of difficult implementation, high cost, large installation workload, and high maintenance difficulty of underground belt coal flow monitoring are solved, the energy-saving operation level of the underground belt conveyor in coal mines is improved, and the operation wear of the belt conveyor is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of underground coal flow control, and in particular, to an underground belt coal flow monitoring method and system. Background Art

[0002] Currently, the mainstream method for detecting underground belt coal flow is the mechanical metering and weighing method, that is, an explosion-proof belt scale. By means of a set of special weighing sensors, the coal flow parameters per unit time of the underground belt are detected and calculated. The following technical defects exist:

[0003] (1) It is necessary to develop a special belt coal flow weighing sensor suitable for the underground moving state. Moreover, it consists of multiple mechanical components to form a set of explosion-proof equipment combination. The equipment is large, complex, and the equipment cost is high. The explosion-proof belt scale needs to be installed under the moving belt, and the base, matching installation height, and the cooperation between two moving parts need to be considered. The installation workload is large and the installation accuracy requirement is high. It is necessary to match the speeds of two moving parts and test the coal flow weight. The debugging workload is large and the debugging cycle is long.

[0004] (2) As the moving belt is continuously worn, the test components of the belt scale generate deviations, which easily cause the accuracy of the belt scale to decrease. After running for a certain period, it has to be re-debugged. The maintenance difficulty is large, the requirements for maintenance engineers are high, and the maintenance cost is high. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art or related technologies.

[0006] Therefore, the purpose of the present invention is to provide an underground belt coal flow monitoring method and system to solve the problems of large size, complexity, high cost, difficult debugging, large maintenance workload, and high maintenance cost of the existing system equipment. The present invention designs a coal flow monitoring discrimination algorithm model to analyze the image information of each target image per unit time in the coal flow video, and can determine the coal flow load ratio. The accuracy of coal flow monitoring is high. By adjusting the belt running speed according to the coal flow load ratio, the energy-saving operation level of the belt conveyor in the coal mine can be effectively improved, and the running wear of the belt conveyor can be reduced. The underground belt coal flow monitoring system of the present invention has a low cost. The main off-the-shelf hardware systems are only explosion-proof high-definition cameras, edge computers, and control hosts, all of which are general-purpose hardware, which is convenient for large-scale use. Moreover, a set of underground belt coal flow monitoring system can control multiple transport belts at the same time, with high efficiency and strong reliability.

[0007] To achieve the above object, the technical solution of the first aspect of the present invention provides a method for monitoring underground belt coal flow, which is applied to an edge computer in an underground belt coal flow monitoring system. The underground belt coal flow monitoring system further includes: a belt conveyor mechanism and a belt conveyor drive roller that are cooperatively connected; a belt conveyor drive motor that is connected to the belt conveyor drive roller through a coupling; a belt conveyor frequency converter electric drive system that is connected to the belt conveyor drive motor through a power cable; a power supply module that is connected to the power supply module of the belt conveyor frequency converter electric drive system through a power cable; a belt conveyor electric control PLC system that is connected to the control module of the belt conveyor frequency converter electric drive system through a communication network line; a control host that is connected to the belt conveyor electric control PLC system through a communication network line; an edge computer that is respectively connected to the control host and an explosion-proof high-definition camera through communication network lines. The explosion-proof high-definition camera is installed directly above the conveyor belt in the belt conveyor mechanism through a mounting bracket. The method includes the following steps: obtaining the coal flow video captured by the explosion-proof high-definition camera in real time; using a coal flow monitoring discrimination algorithm model to analyze the image information of each target image within a unit time in the coal flow video. The image information includes the total number of pixels and the pixel value of each pixel, and determining the belt value and coal flow value of each target image; calculating and determining the coal flow load ratio according to the belt value and coal flow value of each target image, and sending it to the control host.

[0008] In this technical solution, by obtaining the coal flow video captured by the explosion-proof high-definition camera in real time, using a coal flow monitoring discrimination algorithm model to analyze the image information of each target image within a unit time in the coal flow video, determining the belt value and coal flow value of each target image, and calculating and determining the coal flow load ratio based on this, the accuracy of determining the coal flow load ratio is high and it has real-time performance, which is beneficial for the control host to adjust the belt speed of the belt conveyor according to the coal flow load ratio, so that the belt conveyor is always in the best economic operation state.

[0009] The unit time can be 1 min, 1 s, 10 s, 30 s, etc.

[0010] In the above technical solution, preferably, the coal flow monitoring discrimination algorithm model is constructed by the following

[0011] method. Prepare the source data for coal flow video analysis, and select the underground belt coal flow video stream file recorded by the explosion-proof high-definition camera deployed in the coal mine as the source data for video analysis;

[0012] Use UnifiedTestFrame image processing software to perform image frame segmentation processing on the belt coal flow video stream file to generate frame-by-frame coal flow image files;

[0013] Define the model as the coal flow monitoring discrimination algorithm model;

[0014] Define the model algorithm as an image percentage segmentation calculation algorithm;

[0015] Define the model rules, including defining the attributes, size, calibration method, and statistical rules of the belt, and defining the attributes, size, calibration method, and statistical rules of the coal flow;

[0016] Define the calculation rule for the proportion of coal flow;

[0017] Import the coal flow image files generated by image processing into the model source file library, select and classify the coal flow image files in the library for calibration, and divide them into low coal flow load levels, medium coal flow load levels, and high coal flow load levels according to the coal flow load. The low coal flow load level includes no coal flow load on the belt, 1%-10% coal flow load, 11%-20% coal flow load, 21%-30% coal flow load. The medium coal flow load level includes 31%-40% coal flow load, 41%-50% coal flow load, 51%-60% coal flow load, 61%-70% coal flow load. The high coal flow load level includes 71%-80% coal flow load, 81%-90% coal flow load.

[0018] Preferably, the calibration method for coal flow image files includes the following steps:

[0019] Select coal flow image files with different coal flow loads on the same target field of view and the same target section of the belt for calibration. Among them, 5-10 coal flow image files with no coal flow load on the belt are calibrated, and 30-40 coal flow image files with 1%-10%, 11%-20%, 21%-30%, 31%-40%, 41%-50%, 51%-60%, 61%-70%, 71%-80%, 81%-90% coal flow loads on the belt are respectively calibrated.

[0020] First, connect the calibration points into lines and then connect the lines into frames for the section of the target section of the belt without coal flow to obtain multiple belt frames;

[0021] Then, connect the calibration points into lines and then connect the lines into frames for the section of the target section of the belt with coal flow to obtain multiple small coal flow frames;

[0022] According to the statistical rules, automatically calculate the belt value, coal flow value, and coal flow proportion value according to the image percentage segmentation calculation algorithm to calibrate the coal flow load.

[0023] Preferably, automatically calculating the belt value, coal flow value, and coal flow proportion value according to the image percentage segmentation calculation algorithm includes the following steps:

[0024] Read the width and height of the target field of view area, and calculate the total number of pixels in the target field of view area;

[0025] Scan each pixel in the target field of view, read its pixel value, and count the pixel values to form a data table of different grayscale values;

[0026] According to the different grayscale value data tables, the pixel ratio of the belt frame and the pixel ratio of the coal flow small frame are calculated respectively and recorded as the belt value and coal flow value respectively. The ratio of the coal flow value to the sum of the belt value and the coal flow value is recorded as the coal flow ratio value, and the grayscale value range of the belt frame and the coal flow small frame are identified and optimized respectively.

[0027] In this technical solution, by designing a coal flow monitoring and discrimination algorithm model and optimizing it, the belt value, coal flow value, and coal flow ratio can be accurately calculated, and the model accuracy can reach more than 90%. Moreover, the calibration design of the coal flow image file is relatively simple and comprehensive, which makes the model construction more accurate and the optimization process simpler. In addition, the belt frame is calibrated first, and then the coal flow small frame is calibrated. The calibration is relatively simple and accurate. While calculating the belt value, coal flow value, and coal flow ratio value according to the image percentage segmentation calculation algorithm, the grayscale value range of the belt frame and the coal flow small frame is identified and optimized respectively, so that the distinction between the belt frame and the coal flow small frame is more accurate, so that the belt value and the coal flow value can be accurately distinguished and determined during the actual operation, so that the determination of the coal flow load ratio is more accurate.

[0028] It should be noted that the coal flow monitoring and discrimination algorithm model can be built first and then imported into the edge

[0029] In addition, after the coal flow monitoring and discrimination algorithm model is trained, it is necessary to test and evaluate the performance of the model, import the model into the edge computer of the field test, configure and verify the association between the coal flow video and the model, start running the model, generate the coal flow load ratio, compare the coal flow load ratio with the coal flow video to determine the accuracy of the model, if the accuracy difference is large, it is necessary to adjust the statistical rule parameters, train the model again, and continuously optimize it to ensure that the model accuracy reaches the engineering application level (more than 90%).

[0030] In any of the above technical solutions, preferably, the coal flow load ratio is calculated and determined according to the belt value and coal flow value of each target image, which specifically includes the following steps: the coal flow ratio of each target image is calculated by dividing the coal flow value of each target image by the sum of the belt value and the coal flow value; the coal flow load ratio is calculated and determined by adding the coal flow ratio values of each target image in unit time and finding the average value.

[0031] In this technical solution, by calculating the coal flow occupancy ratio of each target image, the coal flow load ratio per unit time in the coal flow video is accurately determined. The accuracy of the determined coal flow load ratio is high, and the method is relatively simple, time-saving and labor-saving, with real-time performance, which is beneficial to controlling the main machine according to the coal flow load ratio to adjust the belt speed of the belt conveyor, so that the belt conveyor is always in the best economic operation state.

[0032] The technical solution of the second aspect of the present invention provides an underground belt coal flow monitoring method, which is applied to a control host in an underground belt coal flow monitoring system. The underground belt coal flow monitoring system further includes: a belt conveyor transmission mechanism and a belt conveyor driving drum which are cooperatively connected; a belt conveyor driving motor connected to the belt conveyor driving drum through a coupling; a belt conveyor frequency converter electric drive system connected to the belt conveyor driving motor through a power cable; a power supply module connected to the power supply module of the belt conveyor frequency converter electric drive system through a power cable; a belt conveyor electric control PLC system connected to the control module of the belt conveyor frequency converter electric drive system through a communication network cable; a control host connected to the belt conveyor electric control PLC system through a communication network cable; an edge computer respectively connected to the control host and an explosion-proof high-definition camera through communication network cables. The explosion-proof high-definition camera is installed directly above the conveyor belt in the belt conveyor transmission mechanism through a mounting bracket.

[0033] The method includes the following steps: receiving the coal flow load ratio determined in real time in the edge computer; calculating the power supply frequency output by the belt conveyor frequency converter electric drive system to the belt conveyor driving motor according to a pre-developed program for different coal flow load ratios corresponding to different belt speed parameters; converting the power supply frequency into a frequency converter adjustment parameter of the belt conveyor electric control PLC system communication protocol and outputting it to the belt conveyor electric control PLC system, so as to control the belt conveyor frequency converter electric drive system through the belt conveyor electric control PLC system and adjust the belt running speed.

[0034] In this technical solution, the control host receives the coal flow load ratio determined in real time in the edge computer, calculates the power supply frequency output by the corresponding belt conveyor frequency converter electric drive system to the belt conveyor driving motor, converts the power supply frequency into a frequency converter adjustment parameter of the belt conveyor electric control PLC system communication protocol and outputs it to the belt conveyor electric control PLC system, so that the belt conveyor frequency converter electric drive system can be controlled through the belt conveyor electric control PLC system to adjust the belt running speed, and the real-time adjustment of the belt running speed can be realized, so that the belt conveyor is always in the best economic operation state and has good operation stability.

[0035] In the above technical solution, preferably, the corresponding relationship between the coal flow load ratio and the power supply frequency output by the belt conveyor frequency converter electric drive system to the belt conveyor driving motor is:

[0036] 0 - 10% corresponds to 5Hz - 10Hz; 11% - 20% corresponds to 11Hz - 15Hz; 21% - 30% corresponds to 16Hz - 20Hz; 31% - 40% corresponds to 21Hz - 25Hz; 41% - 50% corresponds to 26Hz - 30Hz; 51% - 60% corresponds to 31Hz - 35Hz; 61% - 70% corresponds to 36Hz - 40Hz; 71% - 80% corresponds to 41Hz - 45Hz; 81% - 90% corresponds to 46Hz - 50Hz.

[0037] In this technical solution, the relationship between the coal flow load ratio and the power supply frequency is further defined, which is precise and detailed. Further, it enables the belt conveyor running speed to be accurately adjusted in real time according to the coal flow load ratio, thereby further ensuring the economy and safety of the belt conveyor operation.

[0038] The technical solution of the third aspect of the present invention also provides an underground belt coal flow monitoring system, including: a belt conveyor transmission mechanism and a belt conveyor drive drum which are cooperatively connected; a belt conveyor drive motor connected to the belt conveyor drive drum through a coupling; a belt conveyor frequency converter electric drive system connected to the belt conveyor drive motor through a power cable; a power supply module connected to the power supply module of the belt conveyor frequency converter electric drive system through a power cable; a belt conveyor electric control PLC system connected to the control module of the belt conveyor frequency converter electric drive system through a communication network cable; a control host connected to the belt conveyor electric control PLC system through a communication network cable, running the underground belt coal flow monitoring method in the technical solution of the second aspect above; an edge computer connected to the control host and the explosion-proof high-definition camera respectively through communication network cables, running the underground belt coal flow monitoring method in the technical solution of the first aspect above, and the explosion-proof high-definition camera is installed directly above the conveyor belt in the belt conveyor transmission mechanism through a mounting bracket.

[0039] In this technical solution, the underground belt coal flow monitoring system is easy to install. The main components installed on-site are explosion-proof high-definition cameras. The explosion-proof high-definition cameras only need to be installed with mounting brackets at a certain height directly above the belt conveyor. Other components such as edge computers and control hosts only need to be arranged at appropriate positions in the belt electric control chamber arranged near the belt conveyor's frequency converter electric drive system. None of the component systems need to be in direct contact with moving parts such as the belt transmission system. The underground belt coal flow monitoring system proposed by the present invention has good operating stability. Once the deployment and debugging are completed, it can be used stably all the time, and basically no further adjustment and debugging are required, with little maintenance work. The underground belt coal flow monitoring system proposed by the present invention has convenient replicability. A set of coal flow monitoring system can detect and control multiple transport belts. As long as a front-end explosion-proof high-definition camera is installed on the newly added monitored and controlled belt, the video of the newly added front-end explosion-proof high-definition camera is transmitted and configured to the edge computer through the communication network, and the monitoring and discrimination algorithm model is configured into multiple detected coal flow video channels in the edge computer, then the coal flow monitoring of multiple belts can be achieved. The underground belt coal flow monitoring system proposed by the present invention has a low cost. The main off-the-shelf hardware systems are only explosion-proof high-definition cameras, edge computers, and control hosts, all of which are general-purpose hardware and are convenient for large-scale use.

[0040] In the above technical solution, preferably, the control host is directly connected to the edge computer through a communication network cable or linked through a network link using a network switch system; the edge computer is directly connected to the explosion-proof high-definition camera through a communication network cable or linked through a network link using a network switch system; the belt electric control PLC system is directly connected to the control host through a communication network cable or linked through a network link using a network switch system, and the belt electric control PLC system is pre-developed and debugged for matching.

[0041] In the above technical solution, preferably, the belt conveyor frequency converter electric drive system is a standard explosion-proof frequency converter device, which is fixedly installed in the belt electric control chamber. The belt conveyor frequency converter electric drive system receives a 4mA - 20mA analog current signal sent by the belt electric control PLC system through a communication network cable, and the belt conveyor frequency converter electric drive system outputs a power supply with a corresponding frequency to the belt drive motor; the belt electric control PLC system is fixedly installed in the explosion-proof electric control cabinet in the belt electric control chamber, receives the frequency converter adjustment parameters sent by the control host through a communication network cable, and sends a corresponding 4mA - 20mA analog current signal to the belt conveyor frequency converter electric drive system; the control host is fixedly installed in the explosion-proof electric control cabinet in the belt electric control chamber; the edge computer is fixedly installed in the explosion-proof electric control cabinet in the belt electric control chamber.

[0042] In this technical solution, the circuit connections of the components of the underground belt coal flow monitoring system and the component installation positions are further defined, further ensuring safety and reliability. It can realize real-time monitoring of the underground belt coal flow, obtain accurate coal flow load ratios, and use the coal flow load ratios to adjust the belt operation in real time, ensuring the safe, energy-saving, efficient, and economic operation of the belt.

[0043] The underground belt coal flow monitoring method and system proposed by the present invention have the following beneficial technical effects:

[0044] (1) The underground belt coal flow monitoring method and system proposed by the present invention have real-time monitoring of coal flow. The explosion-proof high-definition camera monitors the coal flow in the belt conveyor transmission mechanism in real time, and the video is transmitted to the edge computer in real time. The coal flow monitoring and discrimination algorithm model in the edge computer monitors and discriminates the coal flow video in real time, and outputs the coal flow load ratio monitoring result to the control host. The control host uses the program corresponding to different belt speed parameters for different coal flow load ratios developed in advance, and the generated corresponding frequency converter output power frequency parameters are sent to the frequency converter control PLC through the communication network cable to adjust the output frequency of the frequency converter power supply, thereby adjusting the belt speed to achieve the purpose of the best economic operation of the belt conveyor, with high accuracy and strong real-time performance.

[0045] (2) The underground belt coal flow monitoring system proposed by the present invention is simple to install. The main components installed on site are explosion-proof high-definition cameras, and the explosion-proof high-definition cameras only need to be installed with mounting brackets at a certain height directly above the belt conveyor. Other edge computers and control hosts only need to be arranged at appropriate positions in the belt electric control chamber near the belt conveyor frequency converter electric drive system. All component systems do not need to be in direct contact with the moving parts such as the belt transmission system.

[0046] (3) The underground belt coal flow monitoring method and system proposed by the present invention have good operation stability. Once deployed and debugged, they can be used stably all the time, and basically no further adjustment and debugging are required, with a small maintenance workload.

[0047] (4) The underground belt coal flow monitoring method and system proposed by the present invention have convenient replicability. A set of coal flow monitoring systems can detect and control multiple conveyor belts. As long as a front-end explosion-proof high-definition camera is added to the newly added monitored and controlled conveyor belt, the video of the newly added front-end explosion-proof high-definition camera is transmitted and configured to the edge computer through the communication network, and the monitoring and discrimination algorithm model is configured to multiple coal flow video channels in the edge computer, then the coal flow monitoring of multiple conveyor belts can be realized. It has strong applicability, low cost, and can be used on a large scale.

[0048] (5) The underground belt coal flow monitoring system proposed by the present invention has a low cost. The mainly externally purchased hardware systems are only explosion-proof high-definition cameras, edge computers, and control hosts, all of which are general-purpose hardware and are convenient for large-scale use.

[0049] Additional aspects and advantages of the present invention will be given in the following description section, some will become obvious from the following description, or will be learned through the practice of the present invention. Brief Description of the Drawings

[0050] The above and / or additional aspects and advantages of the present invention will become obvious and easy to understand from the description of the embodiments in conjunction with the following drawings, where:

[0051] Figure 1 A structural schematic block diagram of an underground belt coal flow monitoring system according to an embodiment of the present invention is shown;

[0052] Figure 2 A flowchart of an underground belt coal flow monitoring method according to an embodiment of the present invention is shown;

[0053] Figure 3 A flowchart of an underground belt coal flow monitoring method according to an embodiment of the present invention is shown,

[0054] Among them, the correspondence between the reference numerals and the components in FIG. 1 is as follows:

[0055] 102 Belt conveyor mechanism, 104 Belt conveyor drive roller, 106 Belt conveyor drive motor, 108 Coupling, 110 Belt conveyor frequency converter electric drive system, 112 Power supply module, 114 Belt conveyor electric control PLC system, 116 Control host, 118 Edge computer, 120 Explosion-proof high-definition camera. Detailed Embodiments

[0056] In order to be able to more clearly understand the above objects, features and advantages of the present invention, the present invention will be further described in detail below in conjunction with the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0057] Many specific details are set forth in the following description in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0058] The following combines Figures 1 to 3 to specifically describe the underground belt coal flow monitoring method and system according to an embodiment of the present invention.

[0059] As Figure 1As shown in the figure, the underground belt coal flow monitoring system according to an embodiment of the present invention includes: a belt conveyor mechanism 102, a belt conveyor drive drum 104, a belt conveyor drive motor 106, a coupling 108, a belt conveyor frequency converter electric drive system 110, a power supply module 112, a belt electric control PLC system 114, a control host 116, an edge computer 118, and an explosion-proof high-definition camera 120.

[0060] The belt conveyor mechanism 102 and the belt conveyor drive drum 104 are cooperatively connected. The belt conveyor drive motor 106 is connected to the belt conveyor drive drum 104 through the coupling 108. The belt conveyor frequency converter electric drive system 110 is connected to the belt conveyor drive motor 106 through a power cable. The power supply module 112 is connected to the power supply module of the belt conveyor frequency converter electric drive system 110 through a power cable. The belt electric control PLC system 114 is connected to the control module of the belt conveyor frequency converter electric drive system 110 through a communication network cable. An explosion-proof high-definition camera 120 is installed directly above the conveyor belt in the underground belt conveyor mechanism 102. The control host 116 is arranged to be connected to the belt electric control PLC system 114 through a communication network cable. The edge computer 118 is respectively connected to the control host 116 and the explosion-proof high-definition camera 120 through communication network cables. The coal flow monitoring and discrimination algorithm model in the edge computer 118 detects the coal flow load ratio in real time and sends it to the control host 116. The control host 116 converts it into a digital control parameter according to the program that corresponds different belt speed parameters to different coal flow load ratios developed in advance and sends it to the belt electric control PLC system 114. The belt electric control PLC system 114 generates a corresponding frequency signal of the power supply for the output of the frequency converter to the belt conveyor frequency converter electric drive system 110. The frequency converter electric drive system outputs a power supply with a corresponding frequency to the belt conveyor drive motor 106, so that the running speed of the belt can be adjusted, solving the problems of difficult implementation, high cost, large installation work volume

[0061] and high maintenance difficulty of underground belt coal flow monitoring, improving the energy-saving operation level of the underground belt conveyor in coal mines, and reducing the running wear of the belt conveyor.

[0062] The belt conveyor mechanism 102 uses a long-distance belt, which is hung on the belt conveyor drive drum 104, and the long-distance belt is used to convey the coal flow.

[0063] The installation of the underground belt coal flow monitoring system is simple. The main components installed on-site are the explosion-proof high-definition camera 120, which only needs to be installed with an installation bracket at a certain height directly above the belt conveyor. For the other components, namely the edge computer 118 and the control host 116, they only need to be arranged at appropriate positions in the belt electric control chamber near the belt conveyor frequency converter electric drive system 110. None of the component systems need to be in direct contact with the moving parts such as the belt transmission system. The underground belt coal flow monitoring system proposed by the present invention has good operation stability. Once the deployment and debugging are completed, it can be used stably all the time, and basically no further adjustment and debugging are required, with little maintenance work. The underground belt coal flow monitoring system proposed by the present invention has convenient replicability. One set of coal flow monitoring system can detect and control multiple transport belts. As long as a front-end explosion-proof high-definition camera 120 is added to the newly added monitored and controlled belt, the video of the newly added front-end explosion-proof high-definition camera 120 is transmitted and configured to the edge computer 118 through the communication network, and the monitoring and discrimination algorithm model is configured into multiple coal flow detection video channels in the edge computer 118, then the coal flow monitoring of multiple belts can be realized. The underground belt coal flow monitoring system proposed by the present invention has a low cost. The main externally purchased hardware systems are only the explosion-proof high-definition camera 120, the edge computer 118, and the control host 116, all of which are general-purpose hardware and are convenient for large-scale use.

[0064] Further, the control host 116 is directly connected to the edge computer 118 through a communication network cable or linked through a network link using a network switch system; the edge computer 118 is directly connected to the explosion-proof high-definition camera 120 through a communication network cable or linked through a network link using a network switch system; the belt electric control PLC system 114 is directly connected to the control host 116 through a communication network cable or linked through a network link using a network switch system, and the belt electric control PLC system 114 is pre-developed and debugged for matching.

[0065] Further, the belt conveyor frequency converter electric drive system 110 is a standard explosion-proof frequency converter device, fixedly installed in the belt electric control chamber. The belt conveyor frequency converter electric drive system 110 receives the 4mA - 20mA analog current signal sent by the belt electric control PLC system 114 through a communication network cable, and outputs the power supply of the corresponding frequency to the belt drive motor; the belt electric control PLC system 114 is fixedly installed in the explosion-proof electric control cabinet in the belt electric control chamber, receives the frequency converter adjustment parameters sent by the control host 116 through a communication network cable, and sends the corresponding 4mA - 20mA analog current signal to the belt conveyor frequency converter electric drive system 110; the control host 116 is fixedly installed in the explosion-proof electric control cabinet in the belt electric control chamber; the edge computer 118 is fixedly installed in the explosion-proof electric control cabinet in the belt electric control chamber.

[0066] Thus, the circuit connections of the components of the underground belt coal flow monitoring system are further defined according to the component installation positions, further ensuring safety and reliability, enabling real-time monitoring of the underground belt coal flow, obtaining accurate coal flow load ratios, and using the coal flow load ratios to adjust the belt operation in real time to ensure the safe, energy-saving, efficient, and economic operation of the belt.

[0067] As Figure 2 shown, the underground belt coal flow monitoring method according to an embodiment of the present invention is applied to an edge computer in an underground belt coal flow monitoring system, and includes the following steps:

[0068] S202, obtaining in real time the coal flow video captured by an explosion-proof high-definition camera;

[0069] S204, using a coal flow monitoring discrimination algorithm model to analyze the image information of each target image in the coal flow video per unit time, where the image information includes the total number of pixels and the pixel value of each pixel, and determining the belt value and coal flow value of each target image;

[0070] S206, calculating and determining the coal flow load ratio according to the belt value and coal flow value of each target image,

[0071] and sending it to the control host.

[0072] In this embodiment, by obtaining in real time the coal flow video captured by an explosion-proof high-definition camera, using a coal flow monitoring discrimination algorithm model to analyze the image information of each target image in the coal flow video per unit time, determining the belt value and coal flow value of each target image, and calculating and determining the coal flow load ratio based on this, the determination of the coal flow load ratio is highly accurate and has real-time performance, which is beneficial for the control host to adjust the belt speed of the belt conveyor according to the coal flow load ratio, so that the belt conveyor is always in the best economic operation state.

[0073] The unit time can be 1 min, 1 s, 10 s, 30 s, etc.

[0074] The coal flow monitoring discrimination algorithm model is constructed by the following method:

[0075] Step 1, preparing source data for coal flow video analysis: Selecting the underground belt coal flow video stream file recorded by an explosion-proof high-definition camera deployed in a coal mine as the source data for video analysis.

[0076] Step 2, processing the source data analysis: Using UnifiedTestFrame image processing software to perform image frame segmentation processing on the coal flow video stream file to generate frame-by-frame coal flow image files.

[0077] Step 3, Create a model: Use a model training platform to create a coal flow analysis and detection model. This includes defining the model, defining the model algorithm, defining the model rules, calibrating the model image materials, training the model, etc.

[0078] Specifically, the defined model is a coal flow monitoring and discrimination algorithm model. The defined model rules are: include defining the attributes, size, calibration method, and statistical rules of the belt; defining the attributes, size, calibration method, and statistical rules of the coal flow; defining the rules for calculating the coal flow ratio.

[0079] Import the coal flow image file package generated by image processing into the model source file library, and select image files from the library for calibration. To achieve accurate model training, it is necessary to select picture materials of different coal flow load levels for calibration according to the degree of coal flow. The coal flow load is divided into low coal flow load level, medium coal flow load level, and high coal flow load level. The low coal flow load level includes no coal flow load on the belt, 1%-10% coal flow load, 11%-20% coal flow load, 21%-30% coal flow load. The medium coal flow load level includes 31%-40% coal flow load, 41%-50% coal flow load, 51%-60% coal flow load, 61%-70% coal flow load. The high coal flow load level includes 71%-80% coal flow load, 81%-90% coal flow load.

[0080] The calibration of picture materials with no coal flow load on the belt is as follows: Select picture materials from the library for calibration. First, select pictures without coal flow, and select a section of the belt in the middle of the field of view. Calibrate the belt first (note: throughout the model training stage, it is always this target field of view and target section of the belt). Connect the calibration points into lines, and then connect the lines into a frame, which is the belt frame. Then calibrate the coal flow. Since there is no coal flow, do not calibrate the coal flow frame. According to the statistical rules, the model will automatically calculate the belt value, coal flow value, and coal flow ratio value (belt value 100, coal flow value 0, coal flow ratio 0%) according to the image percentage segmentation calculation algorithm. After completing the calibration operations for the belt and coal flow, one calibration picture is completed. 5-10 such pictures without coal flow need to be calibrated.

[0081] The calibration of the picture material of the belt with 1%-10% coal flow load is as follows: Select the picture material of the coal flow load of 1%-10%, and continue to select the previously determined target field of view and the belt of the target section for calibration. For the intervals that do not exist in the belt of the target section, connect the calibration points into lines and then connect the lines into frames to form several belt frames (note that the belt dividing lines of the coal flow extension are irregular. To accurately calibrate and distinguish the belt and the coal flow, the punctuation should be accurate, careful, and with small intervals); then calibrate the coal flow. For the intervals with coal blocks in the belt of the target section, connect the calibration points into lines and then connect the lines into frames (note that the punctuation should be accurate, careful, and with small intervals) to form several small coal flow frames. According to the statistical rules, the model will automatically calculate the belt value, the coal flow value, and the coal flow occupancy ratio according to the image percentage segmentation calculation algorithm (for example, several belt frames are statistically represented as the belt value of 95, several small coal flow frames are statistically represented as the coal flow value of 5, and the coal flow occupancy ratio is 5%). Such picture materials of the coal flow need to be calibrated for 30-40 pieces.

[0082] The calibration of the picture material of the belt with 11%-20% coal flow load is as follows: Select the picture material of the coal flow load of 11%-20%, and continue to select the previously determined target field of view and the belt of the target section for calibration. Connect the calibration points into lines and then connect the lines into frames to form several belt frames (to accurately calibrate and distinguish the belt and the coal flow, the punctuation should be accurate, careful, and with small intervals); then calibrate the coal flow. For the intervals with coal blocks in the belt of the target section, connect the calibration points into lines and then connect the lines into frames (note that the punctuation should be accurate, careful, and with small intervals) to form several small coal flow frames. According to the statistical rules, the model will automatically calculate the belt value, the coal flow value, and the coal flow occupancy ratio according to the image percentage segmentation calculation algorithm (for example, several belt frames are statistically represented as the belt value of 85, several small coal flow frames are statistically represented as the coal flow value of 15, and the coal flow occupancy ratio is 15%). Such picture materials of the coal flow need to be calibrated for 30-40 pieces.

[0083] The calibration of the picture material of the belt with 21%-30% coal flow load is the same as above.

[0084] The calibration of the picture material of the belt with 31-40% coal flow load is as follows: Select the picture material of the coal flow load of 31-40%, and continue to select the previously determined target field of view and the belt of the target section for calibration. Connect the calibration points into lines and then connect the lines into frames to form several belt frames (to accurately calibrate and distinguish the belt and the coal flow, the punctuation should be accurate, careful, and with small intervals); then calibrate the coal flow. For the intervals with coal blocks in the belt of the target section, connect the calibration points into lines and then connect the lines into frames (note that the punctuation should be accurate, careful, and with small intervals) to form several small coal flow frames. According to the statistical rules, the model will automatically calculate the belt value, the coal flow value, and the coal flow occupancy ratio according to the image percentage segmentation calculation algorithm (for example, several belt frames are statistically represented as the belt value of 65, several small coal flow frames are statistically represented as the coal flow value of 35, and the coal flow occupancy ratio is 35%). Such picture materials of the coal flow need to be calibrated for 30-40 pieces.

[0085] The calibration of the picture materials of the belt with 41 - 50% coal flow load is as follows: Select the picture materials of the 41 - 50% coal flow load, and continue to select the previously determined target field of view and the belt in the target section for calibration. Connect the calibration points into lines, and then connect the lines into frames to form several belt frames (to accurately calibrate and distinguish the belt and the coal flow, the punctuation should be accurate, careful, and with small intervals); then calibrate the coal flow. For the intervals with coal lumps in the belt of the target section, connect the calibration points into lines, and then connect the lines into frames (note that the punctuation should be accurate, careful, and with small intervals) to form several small coal flow frames. According to the statistical rules, the model will automatically calculate the belt value, the coal flow value, and the coal flow occupancy ratio according to the image percentage segmentation calculation algorithm (for example, several belt frames are statistically represented as a belt value of 55, several small coal flow frames are statistically represented as a coal flow value of 45, and the coal flow occupancy ratio is 45%). Such picture materials for measuring the coal flow need to be calibrated 30 - 40 pieces.

[0086] The calibration of the picture materials of the belt with 51% - 60% coal flow load and the picture materials of the belt with 61% - 70% coal flow load is the same as above.

[0087] The calibration of the picture materials of the belt with 71 - 80% coal flow load is as follows: Select the picture materials of the 71 - 80% coal flow load, and continue to select the previously determined target field of view and the belt in the target section for calibration. Connect the calibration points into lines, and then connect the lines into frames to form several belt frames (to accurately calibrate and distinguish the belt and the coal flow, the punctuation should be accurate, careful, and with small intervals); then calibrate the coal flow. For the intervals with coal lumps in the belt of the target section, connect the calibration points into lines, and then connect the lines into frames (note that the punctuation should be accurate, careful, and with small intervals) to form several small coal flow frames. According to the statistical rules, the model will automatically calculate the belt value, the coal flow value, and the coal flow occupancy ratio according to the image percentage segmentation calculation algorithm (for example, several belt frames are statistically represented as a belt value of 25, several small coal flow frames are statistically represented as a coal flow value of 75, and the coal flow occupancy ratio is 75%). Such picture materials for measuring the coal flow need to be calibrated 30 - 40 pieces.

[0088] The calibration of the picture materials of the belt with 81 - 90% coal flow load is as follows: Select the picture materials of the 81 - 90% coal flow load, and continue to select the previously determined target field of view and the belt in the target section for calibration. Connect the calibration points into lines, and then connect the lines into frames to form several belt frames (to accurately calibrate and distinguish the belt and the coal flow, the punctuation should be accurate, careful, and with small intervals); then calibrate the coal flow. For the intervals with coal lumps in the belt of the target section, connect the calibration points into lines, and then connect the lines into frames (note that the punctuation should be accurate, careful, and with small intervals) to form several small coal flow frames. According to the statistical rules, the model will automatically calculate the belt value, the coal flow value, and the coal flow occupancy ratio according to the image percentage segmentation calculation algorithm (for example, several belt frames are statistically represented as a belt value of 15, several small coal flow frames are statistically represented as a coal flow value of 85, and the coal flow occupancy ratio is 85%). Such picture materials for measuring the coal flow need to be calibrated 30 - 40 pieces.

[0089] The calibration of picture materials for the coal flow load of 21%-30% and 51%-60% on the belt is as follows: Select picture materials of different coal flow load levels in different sections. The method for picture material calibration refers to the above-mentioned calibration of picture materials for the coal flow load of 11%-20% on the belt. Calibrate 30-40 picture materials for the belt load level in each section.

[0090] The image percentage segmentation calculation algorithm mainly involves the gray value and pixel value of the image. The main contents include: reading the image, obtaining the image size, calculating the total number of pixels, reading the pixel value, calculating the statistical pixel value, calculating the gray percentage, and displaying the result. Specifically, read the image file; obtain the width and height of the selected field of view area in the image file; calculate the total number of pixels in the selected field of view area of the read image file, where the total number of pixels = image width × image height; scan each pixel in the selected field of view area of the image file and read its pixel value. The pixel value is usually an integer between 0-255, representing the gray value of the pixel, with white being 255 and black being 0; statistically analyze the pixel values to form a data table of different gray values; calculate the percentage of each gray level according to the different gray value data. For example, the pixels with a gray value of 80-120 (coal flow) account for 25%, and the pixels with a gray value of 150-200 (special belt) account for 75%; display and output the calculated gray percentage, that is, output the belt value and the coal flow value, and calculate the coal flow occupancy ratio from the ratio of the coal flow value to the sum of the belt value and the coal flow value. At the same time, respectively optimize the recognition of the gray value range of the belt frame and the small coal flow frame, and optimize the statistical rules to make the calculation of the belt value and the coal flow value more accurate.

[0091] Step 4, test and optimize the model: After training the coal flow monitoring and discrimination algorithm model, it is necessary to conduct tests and evaluations to verify the performance of the model. Import the result model into the on-site test edge computing server, configure and verify the association between the coal flow video and the result model, start running the result model, and generate the coal flow occupancy ratio result. Compare the coal flow occupancy ratio result with the coal flow video to determine the accuracy of the discrimination model. If the accuracy difference is large, it is necessary to adjust the statistical rule parameters, retrain the model, and continuously optimize it until the model accuracy reaches the engineering application level (above 90%).

[0092] Step 5, deploy the model: After continuously optimizing the coal flow monitoring and discrimination algorithm model and reaching the engineering application level in terms of accuracy, it can be deployed to the actual engineering underground belt coal flow monitoring system for application.

[0093] By designing and optimizing the coal flow monitoring and discrimination algorithm model, the belt value, coal flow value, and coal flow occupancy ratio can be accurately calculated. The accuracy of the model can reach over 90%. The time-consuming for testing and optimizing the model is short and relatively simple. Moreover, the calibration design of the coal flow image file is relatively simple and comprehensive, making the model construction more accurate and the optimization process simpler. Additionally, the belt frame calibration is carried out first, and then the small coal flow frame calibration is performed. The calibration is relatively simple and accurate. When calculating the belt value, coal flow value, and coal flow occupancy ratio according to the image percentage segmentation calculation algorithm, the gray value ranges of the belt frame and the small coal flow frame are respectively identified and optimized, making the distinction between the belt frame and the small coal flow frame more accurate. Thus, during the actual operation process, the belt value and the coal flow value can be accurately distinguished and determined, making the determination of the coal flow load ratio more accurate.

[0094] Step S206, calculate and determine the coal flow load ratio according to the belt value and coal flow value of each target image, specifically including:

[0095] Divide the coal flow value of each target image by the sum of the coal flow value and the belt value to calculate the coal flow occupancy ratio of each target image; add up the coal flow occupancy ratios of each target image within a unit time and then calculate the average value to calculate and determine the coal flow load ratio.

[0096] Thus, by calculating the coal flow occupancy ratio of each target image, the coal flow load ratio within a unit time in the coal flow video can be accurately determined. The accuracy of the determined coal flow load ratio is high, and the method is relatively simple, time-saving and labor-saving, with real-time performance, which is beneficial to controlling the host according to the coal flow load ratio and adjusting the belt speed of the belt conveyor, so that the belt conveyor is always in the best economic operation state.

[0097] Such as Figure 3 As shown, a downhole belt coal flow monitoring method according to an embodiment of the present invention is applied to a control host in a downhole belt coal flow monitoring system, and includes the following steps:

[0098] S302, receive the coal flow load ratio determined in real time in the edge computer;

[0099] S304, calculate the power supply frequency output by the belt conveyor inverter electric drive system to the belt conveyor drive motor according to the program that pre-developed different belt speed parameters corresponding to different coal flow load ratios;

[0100] S306, convert the power supply frequency into the inverter adjustment parameters of the belt conveyor electric control PLC system communication protocol and output them to the belt conveyor electric control PLC system, so as to control the belt conveyor inverter electric drive system through the belt conveyor electric control PLC system and adjust the belt running speed.

[0101] Thus, real-time adjustment of the belt running speed can be achieved, enabling the belt conveyor to always operate under the best economic conditions, with good running stability, high real-time performance, and high accuracy.

[0102] Furthermore, the corresponding relationship between the coal flow load ratio and the power supply frequency output by the belt conveyor frequency converter electric drive system to the belt conveyor drive motor is as follows: 0 - 10% corresponds to 5Hz - 10Hz; 11% - 20% corresponds to 11Hz - 15Hz; 21% - 30% corresponds to 16Hz - 20Hz; 31% - 40% corresponds to 21Hz - 25Hz; 41% - 50% corresponds to 26Hz - 30Hz; 51% - 60% corresponds to 31Hz - 35Hz; 61% - 70% corresponds to 36Hz - 40Hz; 71% - 80% corresponds to 41Hz - 45Hz; 81% - 90% corresponds to 46Hz - 50Hz.

[0103] Low coal flow load levels (0 - 10%, 11% - 20%, 21% - 30%, 31% - 40%), medium coal flow load levels (41% - 50%, 51% - 60%, 61% - 70%), high coal flow load levels (71% - 80%, 81% - 90%).

[0104] The relationship between the coal flow load ratio and the power supply frequency is further defined, with precise correspondence. This further enables the real-time and precise adjustment of the belt conveyor running speed according to the coal flow load ratio, thereby further ensuring the economic operation and safety of the belt conveyor.

[0105] The steps in the method of the present invention can be adjusted, combined, and deleted according to actual needs.

[0106] The units in the device of the present invention can be combined, divided, and deleted according to actual needs.

[0107] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by a program instructing relevant hardware. This program can be stored in a computer-readable storage medium, which includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), or other optical disc memories, magnetic disc memories, tape memories, or any other computer-readable medium capable of carrying or storing data.

[0108] In the present invention, the terms "first", "second", and "third" are used only for descriptive purposes and should not be construed as indicating or implying relative importance; the term "plural" refers to two or more, unless otherwise clearly defined. Terms such as "installed", "connected", "joined", and "fixed" should be understood in a broad sense. For example, "connected" can be a fixed connection, a detachable connection, or an integral connection; "joined" can be a direct connection or an indirect connection through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0109] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as "upper", "lower", "left", "right", "front", and "rear" is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or unit referred to must have a specific direction, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention.

[0110] In the description of this specification, the descriptions of terms such as "one embodiment", "some embodiments", "specific embodiments", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0111] The foregoing are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for monitoring the coal flow of an underground belt, characterized in that, An edge computer applied to an underground belt coal flow monitoring system. The underground belt coal flow monitoring system further includes: a belt conveyor mechanism and a belt conveyor drive roller that are cooperatively connected; a belt conveyor drive motor connected to the belt conveyor drive roller through a coupling; a belt conveyor frequency converter electric drive system connected to the belt conveyor drive motor through a power cable; a power supply module connected to the power supply module of the belt conveyor frequency converter electric drive system through a power cable; a belt electric control PLC system connected to the control module of the belt conveyor frequency converter electric drive system through a communication network cable; a control host connected to the belt electric control PLC system through a communication network cable; an edge computer respectively connected to the control host and an explosion-proof high-definition camera through communication network cables. The explosion-proof high-definition camera is installed directly above the conveyor belt in the belt conveyor mechanism through a mounting bracket. The method includes the following steps: Obtain the coal flow video captured by the explosion-proof high-definition camera in real time; Use a coal flow monitoring discrimination algorithm model to analyze the image information of each target image within a unit time in the coal flow video. The image information includes the total number of pixels and the pixel value of each pixel, and determine the belt value and coal flow value of each target image; Calculate and determine the coal flow load ratio according to the belt value and coal flow value of each target image, and send it to the control host; The coal flow monitoring discrimination algorithm model is constructed by the following method: Prepare the source data for coal flow video analysis, and select the underground belt coal flow video stream file recorded by the explosion-proof high-definition camera deployed in the coal mine as the source data for video analysis; Use UnifiedTestFrame image processing software to perform image frame segmentation processing on the coal flow video stream file to generate frame-by-frame coal flow image files; Define the model as a coal flow monitoring discrimination algorithm model; Define the model algorithm as an image percentage segmentation calculation algorithm; Define the model rules, including defining the attributes, sizes, calibration methods, and statistical rules of the belt, and defining the attributes, sizes, calibration methods, and statistical rules of the coal flow; Define the coal flow ratio calculation rule; Import the coal flow image files generated by image processing into the model source file library, select and classify the coal flow image files from the library for calibration, and divide them into low coal flow load levels, medium coal flow load levels, and high coal flow load levels according to the coal flow load. The low coal flow load level includes no coal flow load on the belt, 1%-10% coal flow load, 11%-20% coal flow load, 21%-30% coal flow load. The medium coal flow load level includes 31%-40% coal flow load, 41%-50% coal flow load, 51%-60% coal flow load, 61%-70% coal flow load. The high coal flow load level includes 71%-80% coal flow load, 81%-90% coal flow load. The steps are as follows: Select coal flow image files with different coal flow loads on the same target field of view and the same target section of the belt for calibration. Among them, calibrate 5 - 10 coal flow image files with no coal flow load on the belt, and calibrate 30 - 40 coal flow image files with coal flow loads of 1% - 10%, 11% - 20%, 21% - 30%, 31% - 40%, 41% - 50%, 51% - 60%, 61% - 70%, 71% - 80%, and 81% - 90% on the belt respectively. First, for the section of the target belt section without coal flow, connect the calibration points into lines and then connect the lines into frames to obtain multiple belt frames. Then, for the section of the target belt section with coal flow, connect the calibration points into lines and then connect the lines into frames to obtain multiple small coal flow frames. According to the statistical rules, and based on the image percentage segmentation calculation algorithm, automatically calculate the belt value, coal flow value, and coal flow occupancy ratio for calibration.

2. The underground belt coal flow monitoring method according to claim 1, wherein According to the statistical rules, and based on the image percentage segmentation calculation algorithm, automatically calculate the belt value, coal flow value, and coal flow occupancy ratio, including the following steps: Read the width and height of the target field of view area, and calculate the total number of pixels in the target field of view area. Scan each pixel in the target field of view area, read its pixel value, and perform statistics on the pixel values to form a data table of different gray values. According to the data table of different gray values, calculate the pixel occupancy ratio of the belt frame and the pixel occupancy ratio of the small coal flow frame respectively, which are denoted as the belt value and the coal flow value. Denote the ratio of the coal flow value to the sum of the belt value and the coal flow value as the coal flow occupancy ratio, and respectively perform recognition optimization on the gray value ranges of the belt frame and the small coal flow frame.

3. The underground belt coal flow monitoring method according to claim 1 or 2, characterized in that, According to the belt value and coal flow value of each target image, calculate and determine the coal flow load ratio, specifically including the following steps: Calculate the coal flow occupancy ratio of each target image by dividing the coal flow value of each target image by the sum of the belt value and the coal flow value. Sum up the coal flow occupancy ratios of each target image within a unit time and then calculate the average value to calculate and determine the coal flow load ratio.

4. The underground belt coal flow monitoring method according to claim 1, characterized in that Applied to the control host in the underground belt coal flow monitoring system, the method includes the following steps: Receive the coal flow load ratio determined in real time in the edge computer. According to the pre-developed program that different coal flow load ratios correspond to different belt speed parameter application programs, calculate the power supply frequency output by the belt conveyor inverter electric drive system to the belt conveyor drive motor. Convert the power supply frequency into the inverter adjustment parameter of the belt electric control PLC system communication protocol and output it to the belt electric control PLC system, so as to control the belt conveyor inverter electric drive system through the belt electric control PLC system and adjust the belt running speed.

5. The underground belt coal flow monitoring method according to claim 4, wherein The corresponding relationship between the coal flow load ratio and the power supply frequency output by the belt conveyor inverter electric drive system to the belt conveyor drive motor is: 0 - 10% corresponds to 5 Hz - 10 Hz; 11% - 20% corresponds to 11 Hz - 15 Hz; 21% - 30% corresponds to 16 Hz - 20 Hz; 31% - 40% corresponds to 21 Hz - 25 Hz; 41% - 50% corresponds to 26 Hz - 30 Hz; 51% - 60% corresponds to 31 Hz - 35 Hz; 61% - 70% corresponds to 36 Hz - 40 Hz; 71% - 80% corresponds to 41 Hz - 45 Hz; 81% - 90% corresponds to 46 Hz - 50 Hz.

6. An underground belt coal flow monitoring system for running the monitoring method according to any one of claims 1 to 5, characterized in that, Including: A belt conveyor transmission mechanism and a belt conveyor drive roller which are cooperatively connected and set; A belt conveyor drive motor, which is connected to the belt conveyor drive roller through a coupling; a belt conveyor frequency converter electric drive system, which is connected to the belt conveyor drive motor through a power cable; A power supply module, which is connected to the power supply module of the belt conveyor frequency converter electric drive system through a power cable; a belt conveyor electric control PLC system, which is connected to the control module of the belt conveyor frequency converter electric drive system through a communication network cable; a control host, which is connected to the belt conveyor electric control PLC system through a communication network cable; an edge computer, which is respectively connected to the control host and an explosion-proof high-definition camera through a communication network cable, and the explosion-proof high-definition camera is installed directly above the conveyor belt in the belt conveyor transmission mechanism through a mounting bracket.

7. The underground belt coal flow monitoring system according to claim 6, wherein The control host is directly connected to the edge computer through a communication network cable or linked through a network link by a network switch system; The edge computer is directly connected to the explosion-proof high-definition camera through a communication network cable or linked through a network link by a network switch system; The belt conveyor electric control PLC system is directly connected to the control host through a communication network cable or linked through a network link by a network switch system, and the belt conveyor electric control PLC system is pre-developed and debugged for matching.

8. The underground belt coal flow monitoring system according to claim 7, wherein The belt conveyor frequency converter electric drive system is a standard explosion-proof frequency converter device, which is fixedly installed in a belt electric control chamber. The belt conveyor frequency converter electric drive system receives a 4 mA - 20 mA analog current signal sent by the belt conveyor electric control PLC system through a communication network cable, and the belt conveyor frequency converter electric drive system outputs a power supply with a corresponding frequency to the belt drive motor; The belt conveyor electric control PLC system is fixedly installed in an explosion-proof electric control cabinet in the belt electric control chamber, receives the frequency converter adjustment parameters sent by the control host through a communication network cable, and sends a corresponding 4 mA - 20 mA analog current signal to the belt conveyor frequency converter electric drive system; The control host is fixedly installed in an explosion-proof electric control cabinet in the belt electric control chamber; The edge computer is fixedly installed in an explosion-proof electric control cabinet in the belt electric control chamber.

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