Coal mining machine detection early warning method and system based on 4D millimeter wave radar

Abstract

The invention relates to a coal cutter detection early warning method and system based on 4D millimeter wave radars. The method comprises the following steps: installing a plurality of 4D millimeter wave radars on a traction part in a parabola shape; acquiring coal mine environment calibration point cloud information through the echo signal; aligning and calibrating the point cloud data; fusing a plurality of point cloud data; the height of the cutting roller, the height of the face guard and the recovery angle data of the face guard are obtained; and judging whether a safe operation condition is met or not, controlling the coal mining machine to stop action, controlling the alarm module to carry out alarm action and sending out alarm information under a non-safe condition. The system comprises a 4D millimeter wave radar, an alarm module, a wireless communication module and a data processing terminal. The data processing terminal is connected with the 4D millimeter wave radar, the alarm module and the wireless communication module. According to the method and the system, high-precision detection of a complex mine environment can be realized, an accident of collision of the cutting roller and the side protection plate can be avoided, and the safety of mining operation and the stability of long-term operation of equipment can be effectively guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent detection, and in particular relates to a coal mining machine detection and early warning method based on 4D millimeter wave radar. Background Art

[0002] As a key equipment in coal mining, coal mining machines need to accurately sense and locate the working environment to ensure the safety and efficiency of mining operations. Traditional millimeter-wave radar systems are widely used in environmental perception of coal mining machines. However, due to the extremely complex working environment of mines, hydraulic supports may experience sudden situations such as jack jams and oil tank explosions, which may cause the guard plates to be unable to be recovered in time. In actual working conditions, if the millimeter-wave radar cannot accurately detect the above situations, cutting interference is likely to occur, which may easily lead to damage to the coal mining machine drum and rocker arm, and even cause major safety accidents.

[0003] At present, the planar layout of single or multiple millimeter-wave radar devices is usually unable to fully cover the complex environment around the coal mining machine. Especially under the requirement of high-precision environmental perception, the radar point cloud data of the traditional layout method often has problems of insufficient density and low accuracy, which in turn affects the detection accuracy and reliability of the equipment, thereby affecting the overall performance and accuracy of the system. Summary of the invention

[0004] In view of the problems existing in the above-mentioned prior art, the present invention provides a coal mining machine detection and early warning method and system based on 4D millimeter wave radar. The method can achieve high-precision detection of complex mine environments, avoid accidents such as collisions between the coal mining machine cutting drum and the hydraulic support guard plate, and effectively ensure the safety of mining operations and the long-term stability of equipment operation. The system has high detection accuracy and good stability. When danger is detected, the coal mining machine can be stopped by timely control, and relevant management personnel can be reminded in time by means of alarms, so that they can take emergency measures in time, thereby effectively ensuring the safety and reliability of coal mining machine operations.

[0005] In order to achieve the above object, the present invention provides a coal mining machine detection and early warning method based on 4D millimeter wave radar, comprising the following steps: Step 1: Arrange multiple 4D millimeter wave radars along the width direction at the upper end of the traction part of the coal mining machine, and install each 4D millimeter wave radar toward the cutting part of the coal mining machine, and make the pitch angle of each 4D millimeter wave radar be 20°; at the same time, make multiple 4D millimeter wave radars distributed in a parabola shape, and the opening direction of the formed parabola is toward the cutting part of the coal mining machine; Step 2: Make multiple 4D millimeter-wave radars detect the same target cutting area from different emission angles and positions to fully cover the cutting area; use multiple 4D millimeter-wave radars to transmit linear frequency modulation signals to the front cutting area, receive echo signals, pre-process the echo signals of multiple 4D millimeter-wave radars, and obtain coal mine environment calibration point cloud information; Step 3: Send multiple point cloud data obtained by multiple 4D millimeter wave radars to the data processing terminal, and the data processing terminal aligns and calibrates the multiple point cloud data through the intelligent calibration ICT algorithm; S31: Select a reference point from one point cloud data, and find the point closest to the reference point in another adjacent point cloud data as a matching point pair; S32: Calculate the rotation matrix and translation vector according to the matching point pairs, so as to minimize the matching error between two sets of adjacent point cloud data; S33: applying the calculated rotation matrix and translation vector to one of the two point cloud data so that the two point cloud data overlap to the greatest extent; S34: Repeat S31 to S33 until the matching error converges and reaches the expected registration accuracy; S35: Repeat S31 to S34 until the alignment and calibration of multiple point cloud data output by multiple 4D millimeter wave radars is completed; Step 4: Fusing the aligned and calibrated multiple point cloud data through the data processing terminal, densifying the point cloud image, and obtaining the densified point cloud data; Step 5: Extract the point cloud information of the cutting drum and the point cloud information of 1 to 2 side guards in front of the cutting drum from the densified point cloud data, and cluster and track the point cloud information of the cutting drum and the point cloud information of 1 to 2 side guards in front of the cutting drum, so as to obtain the height data of the cutting drum, the height data of the side guards, and the retraction angle data of the side guards in real time; Step six: During normal operation of the cutting drum of the coal mining machine, based on the guard plate height data, guard plate retraction angle data and cutting drum height data, determine whether 1 to 2 guard plates in front of the cutting drum have reached a fully retracted state, or whether they have been retracted to a degree that allows them to pass through the cutting drum. If 1 to 2 guard plates in front of the cutting drum have reached a fully retracted state, or have been retracted to a degree that allows them to pass through the cutting drum, then the safe operating conditions are met. Otherwise, the data processing terminal controls the alarm module connected to it to perform an alarm action, controls the coal mining machine to stop, and sends an alarm message to the remote monitoring terminal through the wireless communication module.

[0006] As a preferred embodiment, the coal mine environment calibration point cloud information in step 2 includes the working space coordinates of the coal mining machine, the relative position of the hydraulic support and the preliminarily estimated possible interference area.

[0007] Preferably, in step five, the point cloud information of the cutting drum includes the angle, radial velocity and position of the cutting drum point cloud, and the point cloud information of the side guard plate includes the angle and position of the side guard plate.

[0008] Furthermore, in order to ensure detection accuracy, in step one, the number of the 4D millimeter-wave radars is 5.

[0009] As a preference, in step 2, the echo signal is pre-processed as a denoising process.

[0010] In the present invention, since the horizontal detection angle of a single 4D millimeter wave radar is about 120°, multiple 4D millimeter wave radars are installed on the upper end of the traction part of the coal mining machine along the width direction of the traction part of the coal mining machine, and multiple 4D millimeter wave radars can be used to effectively expand the lateral detection range to fully cover the lateral coal mining operation area. Since the vertical detection angle of a single 4D millimeter wave radar is ±20°, the pitch angle of each 4D millimeter wave radar is 20°, so that the longitudinal detection range of the 4D millimeter wave radar can fully cover the longitudinal coal mining operation area. On this basis, multiple 4D millimeter-wave radars are arranged in a parabolic shape. On the one hand, each 4D millimeter-wave radar can detect the same target cutting area from different emission angles and positions at the same time, which is helpful to improve the detection capability of the same target cutting area, and can use the signals of multiple radars to complement each other, thereby enhancing the recognition capability of small and medium-sized targets in the same target cutting area. On the other hand, it can ensure that the wireless signal energy emitted by each 4D millimeter-wave radar can be effectively focused on the target cutting area, especially in the complex working environment underground, which can ensure that all-directional coverage from distance to long distance can be achieved, further improving the accuracy and comprehensiveness of the detection of the target cutting area. On the other hand, the parabolic layout can be used to collect echo signals from multiple angles, thereby obtaining richer spatial information, making up for the problem of sparse point clouds obtained by the traditional 4D millimeter-wave radar arrangement method, significantly improving the detection accuracy, and helping to reduce the detection blind area. At the same time, it can help to optimize the received signals, thereby helping to obtain more accurate and reliable detection data. Finally, through the parabolic arrangement, a redundant design scheme is formed. Even if a 4D millimeter-wave radar fails or is interfered, the remaining 4D millimeter-wave radars can still be used for normal detection operations, ensuring the continuous detection operation and enhancing the stability and reliability of the detection process. Using the data processing terminal to align and calibrate multiple point cloud data through the intelligent calibration ICT algorithm can effectively reduce the "ghosting" phenomenon. On this basis, the fusion of multiple point cloud data can obtain dense and accurate point cloud data, which can achieve accurate detection of the cutting area, solving the problem of sparse point cloud and poor calibration effect obtained by traditional millimeter-wave radar technology. During the operation, it is judged in real time whether 1 to 2 guard plates in front of the cutting drum meet the passing conditions, and if the passing conditions are not met, the alarm module is controlled to perform an alarm action, and the coal mining machine is controlled to stop. At the same time, an alarm message is sent to the remote monitoring terminal, which can significantly improve the timeliness of the early warning and greatly reduce the risk of collision between equipment, ensuring the safe operation of the coal mining machine in a complex environment, and at the same time, it also helps to improve production efficiency.

[0011] This method realizes the rational use of multiple 4D millimeter-wave radars by innovatively arranging multiple 4D millimeter-wave radars with a parabolic distribution and a pitch angle of 20°, thereby effectively expanding the radar detection range and greatly reducing the detection blind spots in the working environment of the coal mining machine. On this basis, combined with the point cloud intelligent calibration technology, the point cloud map is fused to obtain dense point cloud data, which solves the problems of sparse point cloud and inaccurate data, and improves the accuracy and stability of the overall detection of the system. This method can effectively solve the problem that a single millimeter-wave radar or multiple millimeter-wave radars arranged in a simple manner cannot fully cover the complex environment around the coal mining machine. Especially under the requirement of high-precision environmental perception, the radar point cloud data obtained by the traditional arrangement method often has the problems of insufficient density and low accuracy. Therefore, this method realizes high-precision detection of complex mine environments, avoids the collision between the cutting drum of the coal mining machine and the hydraulic support guard plate, and effectively ensures the safety of mining operations and the stability of long-term operation of equipment.

[0012] The present invention also provides a coal mining machine detection and early warning system based on 4D millimeter wave radar, which is used to implement a coal mining machine detection and early warning method based on 4D millimeter wave radar, including 4D millimeter wave radar, alarm module, wireless communication module and data processing terminal; Multiple 4D millimeter-wave radars are sequentially installed at the upper end of the traction part of the coal mining machine along the width direction, and the angle between each 4D millimeter-wave radar and the traction part of the coal mining machine is 20°; at the same time, multiple 4D millimeter-wave radars are distributed in a parabola shape, and the opening direction of the formed parabola is toward the cutting part of the coal mining machine; multiple 4D millimeter-wave radars are used to transmit linear frequency modulation signals to the front cutting area from different positions and angles, and obtain coal mine environment calibration point cloud information based on the echo signal, and then send the coal mine environment calibration point cloud information to the data processing terminal; The alarm module is installed on the coal mining machine and is used to perform alarm actions; The wireless communication module is installed on the coal mining machine and is used to establish a communication connection between the data processing terminal and the monitoring terminal; The data processing terminal is respectively connected to multiple 4D millimeter-wave radars, alarm modules, wireless communication modules and coal mining machines, and is used to align and calibrate multiple point cloud data emitted by multiple 4D millimeter-wave radars, and to fuse the multiple point cloud data after alignment and calibration to obtain densified point cloud data, and is used to obtain cutting drum height data, side guard plate height data and side guard plate retraction angle data based on the densified point cloud data, and is used to determine whether the cutting drum can pass through 1 to 2 side guard plates in front of the cutting drum. If it cannot pass, the coal mining machine is controlled to stop and the alarm module is controlled to perform an alarm action, and an alarm message is sent to a remote monitoring terminal through the wireless communication module.

[0013] Furthermore, in order to ensure data processing efficiency, the data processing terminal is an industrial computer.

[0014] Furthermore, in order to improve the warning effect, the alarm module is an audible and visual alarm.

[0015] In the present invention, by arranging multiple 4D millimeter-wave radars distributed along the width direction and in a parabolic state on the traction part of the coal mining machine, and making the pitch angle of each 4D millimeter-wave radar 20°, not only can the detection range of the coal mining operation be fully expanded both horizontally and vertically, but also multiple 4D millimeter-wave radars can be used to simultaneously detect the same target cutting area from different emission angles and positions, which helps to improve the detection capability of the same target cutting area, and the signals of multiple radars can be used to complement each other, thereby enhancing the recognition capability of small and medium targets in the same target cutting area. In addition, the parabolic layout can be used to collect echo signals from multiple angles, and richer spatial information can be obtained, which makes up for the problem of sparse point clouds obtained by the traditional 4D millimeter-wave radar arrangement method, can significantly improve the detection accuracy, and is conducive to reducing the detection blind spots in the working environment of the coal mining machine. At the same time, it can help to optimize the processing of the received signals, thereby helping to obtain more accurate and reliable detection data. Furthermore, through this parabolic arrangement, a redundant design scheme is formed. Even if a 4D millimeter-wave radar fails or is interfered with, the remaining 4D millimeter-wave radars can still be used for normal detection operations, ensuring the continuity of detection operations and enhancing the stability and reliability of the detection process. Through the setting of the data processing terminal, it is convenient to align and calibrate multiple point cloud data emitted by multiple 4D millimeter-wave radars through intelligent calibration technology, and obtain dense point cloud data by fusing multiple aligned and calibrated point cloud data, so that the cutting drum height data, the guard plate height data and the guard plate retraction angle data can be accurately obtained based on the dense point cloud data, which can help to achieve effective anticipation of the cutting drum action, and can timely control the coal mining machine to stop the action and control the alarm module to perform an alarm action during a possible collision, and send an alarm message to the remote monitoring terminal through the wireless communication module. In this way, the system can effectively solve the problems of insufficient detection accuracy and sparse radar point cloud in the interference area during the cutting process of the coal mining machine, improve the overall detection accuracy and stability of the system, realize accurate judgment of the coal mining status, and can timely remind relevant management personnel through timely alarms when danger is found, so that they can take emergency measures in time, thereby effectively ensuring the safety and reliability of the coal mining machine operation, and helping to improve the efficiency of coal mining operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the position between the coal mining machine and the hydraulic support in the present invention; Figure 2 It is a schematic diagram of assembling multiple 4D millimeter wave radars in the present invention; Figure 3 yes Figure 2 A top view of Figure 4 is a flow chart of the method part of the present invention; Figure 5 It is a principle block diagram of the system part in the present invention.

[0017] In the figure: 1. 4D millimeter wave radar, 2. Coal mining machine traction part, 3. Cutting drum, 4. Coal mining machine cutting part, 5. Hydraulic support, 6. Guard plate, 7. Coal mining machine. DETAILED DESCRIPTION

[0018] The present invention will be further described below in conjunction with the accompanying drawings.

[0019] like Figures 1 to 5 As shown, the present invention provides a coal mining machine detection and early warning method based on 4D millimeter wave radar, comprising the following steps: Step 1: Arrange multiple 4D millimeter wave radars 1 along the width direction at the upper end of the traction part 2 of the coal mining machine, and install each 4D millimeter wave radar 1 toward the cutting part 4 of the coal mining machine, and make the pitch angle of each 4D millimeter wave radar 1 20°; at the same time, make multiple 4D millimeter wave radars 1 distributed in a parabola shape, and the opening direction of the formed parabola faces the cutting part 4 of the coal mining machine; Step 2: Make multiple 4D millimeter wave radars 1 detect the same target cutting area from different emission angles and positions to fully cover the cutting area; use multiple 4D millimeter wave radars 1 to transmit linear frequency modulation signals to the front cutting area, receive echo signals, pre-process the echo signals of multiple 4D millimeter wave radars 1, and obtain coal mine environment calibration point cloud information; Step 3: sending multiple point cloud data obtained by multiple 4D millimeter wave radars 1 to a data processing terminal, and the data processing terminal aligns and calibrates the multiple point cloud data through an intelligent calibration ICT algorithm; S31: Select a reference point from one point cloud data, and find the point closest to the reference point in another adjacent point cloud data as a matching point pair; S32: Calculate the rotation matrix and translation vector according to the matching point pairs, so as to minimize the matching error between two sets of adjacent point cloud data; S33: applying the calculated rotation matrix and translation vector to one of the two point cloud data so that the two point cloud data overlap to the greatest extent; S34: Repeat S31 to S33 until the matching error converges and reaches the expected registration accuracy; S35: Repeat S31 to S34 until the alignment and calibration of multiple point cloud data output by the multiple 4D millimeter wave radars 1 is completed; Step 4: Fusing the aligned and calibrated multiple point cloud data through the data processing terminal, densifying the point cloud image, and obtaining the densified point cloud data; Step 5: Extract the point cloud information of the cutting drum 3 and the point cloud information of 1 to 2 side guards 6 in front of the cutting drum 3 from the densified point cloud data, and cluster and track the point cloud information of the cutting drum 3 and the point cloud information of 1 to 2 side guards 6 in front of the cutting drum 3, so as to obtain the height data of the cutting drum 3, the height data of the side guards 6, the retraction angle data of the side guards 6 and other information in real time; Step six: During the normal operation of the cutting drum 3 of the coal mining machine, based on the height data of the guard plate 6, the retraction angle data of the guard plate 6 and the height data of the cutting drum 3, it is determined whether 1 to 2 guard plates 6 in front of the cutting drum 3 have reached a fully retracted state, or whether they have been retracted to a degree that allows them to pass through the cutting drum 3. If 1 to 2 guard plates 6 in front of the cutting drum 3 have reached a fully retracted state, or have been retracted to a degree that allows them to pass through the cutting drum 3, the safe operating conditions are met. Otherwise, the data processing terminal controls the alarm module connected to it to perform an alarm action, controls the coal mining machine 7 to stop operating, and sends an alarm message to the remote monitoring terminal through the wireless communication module.

[0020] As a preference, the coal mine environment calibration point cloud information in step 2 includes the working space coordinates of the coal mining machine 7, the relative position of the hydraulic support 5 and the preliminarily estimated possible interference area.

[0021] As a preference, in step five, the point cloud information of the cutting drum 3 includes the angle, radial speed and position of the point cloud of the cutting drum 3 , and the point cloud information of the side guard plate 6 includes the angle and position of the side guard plate 6 .

[0022] In order to ensure detection accuracy, in step one, the number of the 4D millimeter wave radars 1 is 5.

[0023] As a preference, in step 2, the echo signal is pre-processed as a denoising process.

[0024] In the present invention, since the horizontal detection angle of a single 4D millimeter wave radar is about 120°, multiple 4D millimeter wave radars are installed on the upper end of the traction part of the coal mining machine along the width direction of the traction part of the coal mining machine, and multiple 4D millimeter wave radars can be used to effectively expand the lateral detection range to fully cover the lateral coal mining operation area. Since the vertical detection angle of a single 4D millimeter wave radar is ±20°, the pitch angle of each 4D millimeter wave radar is 20°, so that the longitudinal detection range of the 4D millimeter wave radar can fully cover the longitudinal coal mining operation area. On this basis, multiple 4D millimeter-wave radars are arranged in a parabolic shape. On the one hand, each 4D millimeter-wave radar can detect the same target cutting area from different emission angles and positions at the same time, which is helpful to improve the detection capability of the same target cutting area, and can use the signals of multiple radars to complement each other, enhance the recognition capability of small and medium targets in the same target cutting area, and realize the rational use of multiple 4D millimeter-wave radars. On the other hand, it can ensure that the wireless signal energy emitted by each 4D millimeter-wave radar can be effectively focused on the target cutting area, especially in the complex working environment underground, it can ensure that all-directional coverage from distance to long distance can be achieved, further improving the accuracy and comprehensiveness of the detection of the target cutting area. On the other hand, the parabolic layout can be used to collect echo signals from multiple angles, so as to obtain richer spatial information, make up for the problem of sparse point cloud obtained by the traditional 4D millimeter-wave radar arrangement method, significantly improve the detection accuracy, and help reduce the detection blind area. At the same time, it can help to optimize the received signal, and then help to obtain more accurate and reliable detection data. Finally, through the parabolic arrangement, a redundant design scheme is formed. Even if a 4D millimeter-wave radar fails or is interfered, the remaining 4D millimeter-wave radars can still be used for normal detection operations, ensuring the continuous detection operation and enhancing the stability and reliability of the detection process. Using the data processing terminal to align and calibrate multiple point cloud data through the intelligent calibration ICT algorithm can effectively reduce the "ghosting" phenomenon. On this basis, the fusion of multiple point cloud data can obtain dense and accurate point cloud data, which can achieve accurate detection of the cutting area, solving the problem of sparse point cloud and poor calibration effect obtained by traditional millimeter-wave radar technology. During the operation, it is judged in real time whether 1 to 2 guard plates in front of the cutting drum meet the passing conditions, and if the passing conditions are not met, the alarm module is controlled to perform an alarm action, and the coal mining machine is controlled to stop. At the same time, an alarm message is sent to the remote monitoring terminal, which can significantly improve the timeliness of the early warning and greatly reduce the risk of collision between equipment, ensuring the safe operation of the coal mining machine in a complex environment, and at the same time, it also helps to improve production efficiency.

[0025] This method realizes the rational use of multiple 4D millimeter-wave radars by innovatively arranging multiple 4D millimeter-wave radars with a parabolic distribution and a pitch angle of 20°, thereby effectively expanding the radar detection range and greatly reducing the detection blind spots in the working environment of the coal mining machine. On this basis, combined with the point cloud intelligent calibration technology, the point cloud map is fused to obtain dense point cloud data, which solves the problems of sparse point cloud and inaccurate data, and improves the accuracy and stability of the overall detection of the system. This method can effectively solve the problem that a single millimeter-wave radar or multiple millimeter-wave radars arranged in a simple manner cannot fully cover the complex environment around the coal mining machine. Especially under the requirement of high-precision environmental perception, the radar point cloud data obtained by the traditional arrangement method often has the problems of insufficient density and low accuracy. Therefore, this method realizes high-precision detection of complex mine environments, avoids the collision between the cutting drum of the coal mining machine and the hydraulic support guard plate, and effectively ensures the safety of mining operations and the stability of long-term operation of equipment.

[0026] The present invention also provides a coal mining machine detection and early warning system based on 4D millimeter wave radar, which is used to implement a coal mining machine detection and early warning method based on 4D millimeter wave radar, including 4D millimeter wave radar 1, an alarm module, a wireless communication module and a data processing terminal; Multiple 4D millimeter wave radars 1 are sequentially distributed at the upper end of the shearer traction part 2 along the width direction, and each 4D millimeter wave radar 1 is installed on the shearer traction part 2 facing the shearer cutting part 4, and at the same time, the pitch angle of each 4D millimeter wave radar 1 is 20°; at the same time, multiple 4D millimeter wave radars 1 are distributed in a parabola shape, and the opening direction of the formed parabola is toward the shearer cutting part 4; multiple 4D millimeter wave radars 1 are used to transmit linear frequency modulation signals to the front cutting area from different positions and angles, and obtain coal mine environment calibration point cloud information based on the echo signal, and then send the coal mine environment calibration point cloud information to the data processing terminal; The alarm module is installed on the coal mining machine 7 and is used to perform alarm actions; The wireless communication module is installed on the coal mining machine 7 and is used to establish a communication connection between the data processing terminal and the monitoring terminal; The data processing terminal is respectively connected to multiple 4D millimeter-wave radars 1, alarm modules, wireless communication modules and coal mining machines 7, and is used to align and calibrate multiple point cloud data emitted by multiple 4D millimeter-wave radars 1, and to fuse the multiple point cloud data after alignment and calibration to obtain densified point cloud data, which is used to obtain the height data of the cutting drum 3, the height data of the side guard plate 6 and the retraction angle data of the side guard plate 6 based on the densified point cloud data, and is used to determine whether the cutting drum 3 can pass through 1 to 2 side guard plates 6 in front of the cutting drum 3. If it cannot pass, the coal mining machine 7 is controlled to stop the action, the alarm module is controlled to perform an alarm action, and an alarm message is sent to a remote monitoring terminal through the wireless communication module.

[0027] In order to ensure data processing efficiency, the data processing terminal is an industrial computer.

[0028] In order to improve the warning effect, the alarm module is an audible and visual alarm.

[0029] In the present invention, by arranging multiple 4D millimeter-wave radars distributed along the width direction and in a parabolic state on the traction part of the coal mining machine, and making the pitch angle of each 4D millimeter-wave radar 20°, not only can the detection range of the coal mining operation be fully expanded both horizontally and vertically, but also multiple 4D millimeter-wave radars can be used to simultaneously detect the same target cutting area from different emission angles and positions, which helps to improve the detection capability of the same target cutting area, and the signals of multiple radars can be used to complement each other, thereby enhancing the recognition capability of small and medium targets in the same target cutting area. In addition, the parabolic layout can be used to collect echo signals from multiple angles, and richer spatial information can be obtained, which makes up for the problem of sparse point clouds obtained by the traditional 4D millimeter-wave radar arrangement method, can significantly improve the detection accuracy, and is conducive to reducing the detection blind spots in the working environment of the coal mining machine. At the same time, it can help to optimize the processing of the received signals, thereby helping to obtain more accurate and reliable detection data. Furthermore, through this parabolic arrangement, a redundant design scheme is formed. Even if a 4D millimeter-wave radar fails or is interfered with, the remaining 4D millimeter-wave radars can still be used for normal detection operations, ensuring the continuity of detection operations and enhancing the stability and reliability of the detection process. Through the setting of the data processing terminal, it is convenient to align and calibrate multiple point cloud data emitted by multiple 4D millimeter-wave radars through intelligent calibration technology, and obtain dense point cloud data by fusing multiple aligned and calibrated point cloud data, so that the cutting drum height data, the guard plate height data and the guard plate retraction angle data can be accurately obtained based on the dense point cloud data, which can help to achieve effective anticipation of the cutting drum action, and can timely control the coal mining machine to stop the action and control the alarm module to perform an alarm action during a possible collision, and send an alarm message to the remote monitoring terminal through the wireless communication module. In this way, the system can effectively solve the problems of insufficient detection accuracy and sparse radar point cloud in the interference area during the cutting process of the coal mining machine, improve the overall detection accuracy and stability of the system, realize accurate judgment of the coal mining status, and can timely remind relevant management personnel through timely alarms when danger is found, so that they can take emergency measures in time, thereby effectively ensuring the safety and reliability of the coal mining machine operation, and helping to improve the efficiency of coal mining operations.

Claims

1. A coal mining machine detection and early warning method based on 4D millimeter wave radar, characterized in that: The steps include: Step 1: Arrange a plurality of 4D millimeter wave radars (1) along the width direction at the upper end of the coal mining machine traction part (2), and install each 4D millimeter wave radar (1) toward the coal mining machine cutting part (4), and make the pitch angle of each 4D millimeter wave radar (1) be 20 degrees; at the same time, make the plurality of 4D millimeter wave radars (1) distributed in a parabola shape, and the opening direction of the formed parabola is toward the coal mining machine cutting part (4); Step 2: multiple 4D millimeter wave radars (1) are used to detect the same target cutting area from different emission angles and positions to fully cover the cutting area; multiple 4D millimeter wave radars (1) are used to transmit linear frequency modulation signals to the front cutting area, and echo signals are received, and the echo signals of the multiple 4D millimeter wave radars (1) are pre-processed to obtain coal mine environment calibration point cloud information; Step 3: sending the multiple point cloud data obtained by the multiple 4D millimeter wave radars (1) to the data processing terminal, and the data processing terminal aligns and calibrates the multiple point cloud data through an intelligent calibration ICT algorithm; S31: Select a reference point from one point cloud data, and find the point closest to the reference point in another adjacent point cloud data as a matching point pair; S32: Calculate the rotation matrix and translation vector according to the matching point pairs, so as to minimize the matching error between two sets of adjacent point cloud data; S33: applying the calculated rotation matrix and translation vector to one of the two point cloud data so that the two point cloud data overlap to the greatest extent; S34: Repeat S31 to S33 until the matching error converges and reaches the expected registration accuracy; S35: Repeat S31 to S34 until the alignment and calibration of the multiple point cloud data output by the multiple 4D millimeter wave radars (1) is completed; Step 4: Fusing the aligned and calibrated multiple point cloud data through the data processing terminal, densifying the point cloud image, and obtaining the densified point cloud data; Step 5: extracting the point cloud information of the cutting drum (3) and the point cloud information of one to two side guards (6) in front of the cutting drum (3) from the densified point cloud data, and clustering and tracking the point cloud information of the cutting drum (3) and the point cloud information of one to two side guards (6) in front of the cutting drum (3), so as to obtain the height data of the cutting drum (3), the height data of the side guards (6) and the retraction angle data of the side guards (6) in real time; Step 6: During the normal operation of the cutting drum (3) of the coal mining machine, the height data of the guard plate (6), the retraction angle data of the guard plate (6) and the height data of the cutting drum (3) are combined to determine whether one or two guard plates (6) in front of the cutting drum (3) have reached a fully retracted state, or have been retracted to a degree that allows them to pass through the cutting drum (3). If one or two guard plates (6) in front of the cutting drum (3) have reached a fully retracted state, or have been retracted to a degree that allows them to pass through the cutting drum (3), then the safe operation conditions are met. Otherwise, the data processing terminal controls the alarm module connected thereto to perform an alarm action, controls the coal mining machine (7) to stop operating, and sends an alarm message to a remote monitoring terminal through the wireless communication module.

2. A coal mining machine detection and early warning method based on 4D millimeter wave radar according to claim 1, characterized in that: The coal mine environment calibration point cloud information in step 2 includes the working space coordinates of the coal mining machine (7), the relative position of the hydraulic support (5) and the preliminarily estimated possible interference area.

3. A coal mining machine detection and early warning method based on 4D millimeter wave radar according to claim 1, characterized in that: In step five, the point cloud information of the cutting drum (3) includes the angle, radial speed and position of the point cloud of the cutting drum (3), and the point cloud information of the side guard plate (6) includes the angle and position of the side guard plate (6).

4. The method for detecting and warning a coal mining machine based on 4D millimeter wave radar according to claim 1 is characterized in that: In step 1, the number of the 4D millimeter wave radars (1) is 5.

5. The method for detecting and warning a coal mining machine based on 4D millimeter wave radar according to claim 1 is characterized in that: In step 2, the echo signal is pre-processed to remove noise.

6. A coal mining machine detection and early warning system based on 4D millimeter wave radar, used to implement a coal mining machine detection and early warning method based on 4D millimeter wave radar as described in any one of claims 1 to 5, characterized in that: It includes a 4D millimeter wave radar (1), an alarm module, a wireless communication module and a data processing terminal; A plurality of 4D millimeter wave radars (1) are sequentially distributed at the upper end of the coal mining machine traction part (2) along the width direction, and each 4D millimeter wave radar (1) is installed on the coal mining machine traction part (2) facing the coal mining machine cutting part (4), and at the same time, the pitch angle of each 4D millimeter wave radar (1) is 20 degrees; at the same time, the plurality of 4D millimeter wave radars (1) are distributed in a parabola shape, and the opening direction of the formed parabola faces the coal mining machine cutting part (4); the plurality of 4D millimeter wave radars (1) are used to transmit linear frequency modulation signals to the front cutting area from different positions and angles, and obtain coal mine environment calibration point cloud information based on the echo signal, and then send the coal mine environment calibration point cloud information to the data processing terminal; The alarm module is installed on the coal mining machine (7) and is used to perform an alarm action; The wireless communication module is installed on the coal mining machine (7) and is used to establish a communication connection between the data processing terminal and the monitoring terminal; The data processing terminal is respectively connected to a plurality of 4D millimeter wave radars (1), an alarm module, a wireless communication module and a coal mining machine (7), and is used to align and calibrate a plurality of point cloud data emitted by the plurality of 4D millimeter wave radars (1), and to fuse the plurality of point cloud data after alignment and calibration to obtain dense point cloud data, and is used to obtain the height data of the cutting drum (3), the height data of the side guard plate (6) and the retraction angle data of the side guard plate (6) based on the dense point cloud data, and is used to determine whether the cutting drum (3) can pass through 1 to 2 side guard plates (6) in front of the cutting drum (3). If it cannot pass through, the coal mining machine (7) is controlled to stop action, the alarm module is controlled to perform an alarm action, and an alarm message is sent to a remote monitoring terminal through the wireless communication module.

7. A coal mining machine detection and early warning system based on 4D millimeter wave radar according to claim 6, characterized in that: The data processing terminal is an industrial computer.

8. The coal mining machine detection and early warning system based on 4D millimeter wave radar according to claim 6 is characterized in that: The alarm module is an audible and visual alarm.

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