Intelligent personnel-limiting barrier gate system for coal mine well and control method of intelligent personnel-limiting barrier gate system
By using multi-sensor fusion technology and intelligent algorithms, the problem of misjudgment in coal mine shaft gate systems under high dust environments has been solved, enabling accurate identification and control of personnel and vehicles, and improving the stability and safety of the system.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-17
- Publication Date
- 2026-03-24
AI Technical Summary
Existing coal mine shaft gate systems suffer from misjudgment due to radar signal attenuation and interference in high-dust environments, making it impossible to accurately identify and control the passage of personnel and vehicles, resulting in problems such as false opening or refusal to open.
Employing multi-sensor fusion technology, including millimeter-wave radar, UWB positioning base station, and infrared thermal imaging module, combined with anti-interference algorithms, multi-modal fusion algorithms, and nearest neighbor association algorithms, a spatiotemporally consistent comprehensive dataset is formed to accurately identify target types and generate control commands.
The system achieves accurate target identification and control in dusty environments, reducing the false judgment rate and ensuring the accuracy and security of the barrier gate system.
Smart Images
Figure CN121719178A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of personnel management technology in mines, and in particular to an intelligent personnel restriction gate system for coal mines and its control method. Background Technology
[0002] In the field of coal mine safety production, personnel restriction management is crucial for hazardous areas (such as mining faces). Mining faces pose high risks, including gas explosions, roof collapses, water inrushes, and fires. If personnel are densely packed, the number of casualties in the event of an accident will increase exponentially. Personnel restriction management, by controlling the number of people on site, can significantly reduce the risk of mass casualties in accidents.
[0003] Currently, common methods for limiting personnel access include manual registration, card access control, and simple video surveillance. Some more advanced systems employ radar-sensored barrier gate systems. The radar module emits electromagnetic waves and receives the echo signals reflected by vehicles or people. Algorithms analyze the signals to determine whether a vehicle is present in the lane. When a vehicle or person is detected, the radar sends a trigger signal to the barrier gate controller, causing the barrier gate to raise and allow passage. After the vehicle passes, if the radar detects no valid echo, it sends a signal to lower the barrier gate back to its original position, completing automatic passage control.
[0004] However, high concentrations of dust in coal mines easily adhere to the surface of radar probes, and at the same time, they strongly scatter and absorb radar electromagnetic waves, resulting in a significant attenuation of the echo signal strength. This not only makes it impossible to accurately obtain dynamic information such as the relative distance and speed of the target, but may also misjudge large areas of dust clouds as targets, causing the gate to open or refuse to open. Summary of the Invention
[0005] Therefore, it is necessary to provide a smart personnel restriction gate system for coal mines and its control method to address the above-mentioned technical problems.
[0006] This invention provides an intelligent personnel restriction barrier system for coal mines, comprising: a sensing layer, a control layer, and an execution layer; The perception layer includes: various sensor modules deployed on the turnstile to acquire raw data of the target in front of the turnstile. The raw data includes: dynamic distance information between the target and the turnstile, target identity information, and target category information. The control layer incorporates anti-interference algorithms, multimodal fusion algorithms, and nearest neighbor association algorithms. The anti-interference algorithm filters the raw data, removing static interference from underground metal and suppressing dynamic dust interference to obtain filtered data. The multimodal fusion algorithm performs coordinate system unification and time synchronization on the filtered data to form spatiotemporally consistent fused data, resulting in a comprehensive dataset. The nearest neighbor association algorithm performs data association on the comprehensive dataset, determines the type of the target in front of the gate, obtains the target attribute judgment result, and generates gate control commands based on the target attribute judgment result. The execution layer is used to control the gate to perform corresponding opening and closing actions according to the gate control instructions.
[0007] Optionally, the various sensor modules deployed on the gate include: millimeter-wave radar module, UWB positioning base station module and infrared thermal imaging module; The millimeter-wave radar module, deployed in front of the gate, is used to acquire dynamic distance information between the target and the gate through radar waves. The dynamic distance information includes: relative distance, relative speed, and azimuth angle; and determines whether the target's trajectory is approaching and passing through the gate based on the dynamic distance information. The UWB positioning base station module is deployed above the gate and is used to communicate with the UWB tag carried by the target to obtain the target's identity information, which includes: absolute coordinates and unique identity ID information. The infrared thermal imaging module is used to acquire infrared thermal radiation images of targets in low-light and high-dust environments, and to distinguish between human bodies and vehicles by the shape characteristics of the heat source, thereby obtaining target category information.
[0008] Optionally, the built-in anti-interference algorithm in the control layer is used to filter the raw data, removing static interference from downhole metals and suppressing dynamic interference from dust, resulting in filtered data, specifically including: Anti-interference algorithms include: static interference filtering algorithm and dust dynamic interference suppression algorithm; The static interference filtering algorithm is used to establish a static environment map around the gate using the radar waves of the millimeter-wave radar module. It marks radar scattering points that exist for a long time and whose positions are fixed as static background interference and filters them out from the dynamic distance information between the target and the gate. The dust dynamic interference suppression algorithm is used to dynamically adjust the radar detection sensitivity threshold based on the dust signal attenuation model. It also uses an adaptive threshold segmentation algorithm on the infrared images of the infrared thermal imaging module to distinguish between large-area low-temperature dust clouds and high-temperature, regularly shaped interference targets, and to filter them out from the target identity information and target category information to obtain filtered data.
[0009] Optionally, the multimodal fusion algorithm built into the control layer is used to unify the coordinate system and synchronize the time of the filtered data, forming spatiotemporally consistent fused data to obtain a comprehensive dataset, specifically including: The dynamic distance information detected by the millimeter-wave radar module, the target identity information obtained by the UWB positioning base station module, and the target category information identified by the infrared thermal imaging module are correlated and matched to form independent tracking targets, resulting in a comprehensive dataset.
[0010] Optionally, the nearest neighbor association algorithm built into the control layer is used to perform data association on the comprehensive dataset, determine the type of the target in front of the gate, and obtain the target attribute judgment result, specifically including: If the target in front of the gate has a radar motion trajectory from the millimeter-wave radar module, a unique identity ID from the UWB positioning base station module, and a human thermal imaging outline from the infrared thermal imaging module, then the target attribute judgment result is an authorized person. If the target in front of the gate simultaneously possesses radar motion trajectory from the millimeter-wave radar module, unique identity ID information from the UWB positioning base station module, and high-temperature heat source characteristics of the vehicle engine from the infrared thermal imaging module, then the target attribute judgment result is an authorized vehicle.
[0011] Optionally, the control layer is specifically used to generate gate control instructions based on the target attribute judgment results, including: If a target is simultaneously identified as having dynamic distance information from the millimeter-wave radar module, unique identity ID information from the UWB positioning base station module, and category information from the infrared thermal imaging module, and its movement trajectory is approaching and passing through the barrier gate, then an instruction to open the barrier gate is generated. If the target does not carry a UWB tag or the tag permissions are not compatible, a gate opening refusal command will be generated and an audible and visual alarm will be triggered.
[0012] Optionally, after the gate is opened, the execution layer continuously monitors the target's passage status and controls the gate to close after a delay once the target has passed.
[0013] This invention provides a control method for an intelligent personnel restriction barrier system in a coal mine, comprising: Obtain raw data of the target in front of the gate. The raw data includes: dynamic distance information between the target and the gate, target identity information, and target category information. An anti-interference algorithm is used to filter the raw data to remove static interference from underground metals and suppress dynamic interference from dust, resulting in filtered data. A multimodal fusion algorithm is used to unify the coordinate system and synchronize the time of the filtered data to form spatiotemporally consistent fused data, resulting in a comprehensive dataset. A nearest neighbor association algorithm is used to associate the comprehensive dataset to determine the type of the target in front of the gate, obtain the target attribute judgment result, and generate gate control instructions based on the target attribute judgment result. Control the gate to perform the corresponding opening and closing actions according to the gate control command.
[0014] The intelligent personnel restriction barrier system and control method for coal mines provided in this invention have the following advantages compared with the prior art: This invention mitigates the impact of dust through a three-layer algorithm: First, an anti-interference algorithm filters the raw data from the sensing layer (especially radar signals affected by dust) in real time, directly filtering out abnormal signals generated by dust clouds and suppressing interference input at its source. Next, a multi-modal fusion algorithm synchronizes the coordinates and time of data from multiple sources, including radar and vision. When radar signals are attenuated or distorted due to dust, the algorithm automatically enhances and fuses reliable data from other sensors to form a more robust comprehensive dataset. Finally, a nearest neighbor association algorithm dynamically associates and recognizes patterns in the comprehensive dataset, accurately distinguishing between the continuous trajectory of a real target and the instantaneous or disordered signals caused by dust.
[0015] This processing chain no longer relies on the perfect operation of a single sensor. It can still extract real target information in dusty environments, completely solving the problem of misjudgment caused by dust in existing technologies and ensuring the accuracy of gate control commands. Attached Figure Description
[0016] Figure 1 This is a schematic diagram of the equipment layout of an intelligent personnel restriction barrier system for a coal mine, provided in one embodiment. Figure 2 This is a schematic diagram of the control method for an intelligent personnel restriction gate system in a coal mine, provided in one embodiment. Figure 3 This is a flowchart illustrating a control method for an intelligent personnel restriction gate system in a coal mine, as provided in one embodiment. Detailed Implementation
[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.
[0018] I. System Content.
[0019] This invention provides an intelligent personnel restriction barrier system for coal mines, which includes a sensing layer, a control layer, and an execution layer.
[0020] The perception layer includes various sensor modules deployed on the turnstile to acquire raw data of the target in front of the turnstile. The raw data includes dynamic distance information between the target and the turnstile, target identity information, and target category information.
[0021] The control layer incorporates anti-interference algorithms, multimodal fusion algorithms, and nearest neighbor association algorithms. The anti-interference algorithm filters the raw data, removing static interference from downhole metal and suppressing dynamic dust interference, resulting in filtered data. The multimodal fusion algorithm performs coordinate system unification and time synchronization on the filtered data, forming spatiotemporally consistent fused data, thus obtaining a comprehensive dataset. The nearest neighbor association algorithm performs data association on the comprehensive dataset, determines the type of target in front of the gate, obtains the target attribute judgment result, and generates gate control commands based on the target attribute judgment result.
[0022] The execution layer is used to control the gate to perform corresponding opening and closing actions according to the gate control instructions.
[0023] Preferably, the various sensor modules deployed on the gate include: a millimeter-wave radar module, a UWB positioning base station module, and an infrared thermal imaging module.
[0024] A millimeter-wave radar module, deployed in front of the turnstile, is used to acquire dynamic distance information between the target and the turnstile via radar waves. This dynamic distance information includes relative distance, relative speed, and azimuth. Based on this dynamic distance information, the module determines whether the target's trajectory indicates it is approaching and attempting to pass through the turnstile.
[0025] The UWB positioning base station module is deployed above the gate and is used to communicate with the UWB tag carried by the target to obtain the target's identity information, which includes: absolute coordinates and unique identity ID information.
[0026] The infrared thermal imaging module is used to acquire infrared thermal radiation images of targets in low-light and high-dust environments, and to distinguish between human bodies and vehicles by the shape characteristics of the heat source, thereby obtaining target category information.
[0027] Preferably, the built-in anti-interference algorithm in the control layer is used to filter the raw data, removing static interference from downhole metals and suppressing dynamic interference from dust, to obtain filtered data, specifically including: Anti-interference algorithms include: static interference filtering algorithm and dust dynamic interference suppression algorithm.
[0028] The static interference filtering algorithm is used to establish a static environment map around the gate using radar waves from the millimeter-wave radar module. It marks radar scattering points that exist for a long time and whose positions remain unchanged as static background interference and filters them out from the dynamic distance information between the target and the gate.
[0029] The dust dynamic interference suppression algorithm is used to dynamically adjust the radar detection sensitivity threshold based on the dust signal attenuation model. It also uses an adaptive threshold segmentation algorithm on the infrared images of the infrared thermal imaging module to distinguish between large-area low-temperature dust clouds and high-temperature, regularly shaped interference targets, and to filter them out from the target identity information and target category information to obtain filtered data.
[0030] Preferably, the multimodal fusion algorithm built into the control layer is used to unify the coordinate system and synchronize the time of the filtered data, forming spatiotemporally consistent fused data to obtain a comprehensive dataset, specifically including: The dynamic distance information detected by the millimeter-wave radar module, the target identity information obtained by the UWB positioning base station module, and the target category information identified by the infrared thermal imaging module are correlated and matched to form independent tracking targets, resulting in a comprehensive dataset.
[0031] Preferably, the nearest neighbor association algorithm built into the control layer is used to perform data association on the comprehensive dataset, determine the type of the target in front of the gate, and obtain the target attribute judgment result, specifically including: If the target in front of the gate simultaneously possesses a radar motion trajectory from a millimeter-wave radar module, a unique identity ID from a UWB positioning base station module, and a human thermal imaging outline from an infrared thermal imaging module, then the target attribute determination result is an authorized person.
[0032] If the target in front of the gate simultaneously possesses radar motion trajectory from the millimeter-wave radar module, unique identity ID information from the UWB positioning base station module, and high-temperature heat source characteristics of the vehicle engine from the infrared thermal imaging module, then the target attribute judgment result is an authorized vehicle.
[0033] Preferably, the control layer is specifically used to generate gate control commands based on the target attribute judgment result, including: If a target is simultaneously identified as having dynamic distance information from the millimeter-wave radar module, a unique identity ID from the UWB positioning base station module, and category information from the infrared thermal imaging module, and its movement trajectory is approaching and passing through the barrier gate, then a gate opening command is generated.
[0034] If the target does not carry a UWB tag or the tag permissions are not compatible, a gate opening refusal command will be generated and an audible and visual alarm will be triggered.
[0035] Preferably, all sensor modules of the sensing layer are integrated within an intrinsically safe explosion-proof enclosure.
[0036] Preferably, after the gate is opened, the execution layer continuously monitors the target's passage status and controls the gate to close after a delay once the target has passed.
[0037] A specific embodiment of the present invention is provided: 1. For example Figure 1 The diagram shows the equipment layout of an intelligent personnel restriction gate system for coal mines provided by this invention. It includes a personnel restriction controller, which serves as the control layer of the entire system, enabling voice alarms and gate device start / stop. A dynamic target recognizer, which is the perception layer of the entire system, includes:
[0038] Millimeter-wave radar: used to detect dynamic information of targets such as range, velocity, and azimuth. UWB module: used to obtain the target's precise absolute coordinates and unique identity ID information; Infrared thermal imaging equipment: used to distinguish between human bodies and vehicles; Explosion-proof cameras for mining are used to monitor personnel entering and exiting restricted areas and are installed at the entrances and exits of these areas. The turnstile equipment is the execution layer of the entire system, used to restrict the number of vehicles / personnel outside the restricted area. The barrier equipment is installed at the entrance and exit of the restricted area.
[0039] Figure 2 This is a principle block diagram of an intelligent personnel restriction gate system and its control method in coal mines, including a sensing layer, a control layer, and an execution layer. The underground intelligent gate system is combined with the existing personnel precise positioning system and auxiliary transportation system. The host computer system determines the number of people / vehicles in the current restricted area, establishes the opening certificate for opening the gate, and the personnel restriction controller realizes voice alarm and equipment start and stop, realizing intelligent personnel restriction management in the underground working face restricted area and other important workplaces.
[0040] 2. The specific perception layer includes the following components: Millimeter-wave radar module: Deployed in front of the turnstile, it uses frequency-modulated continuous wave (FMCW) radar, for example, operating at a frequency of 77 GHz, with an adjustable detection range of 0-20 meters. It uses radar waves to detect dynamic information of targets within the sensing area, including the relative distance, relative speed, and azimuth angle between the target and the turnstile.
[0041] UWB positioning base station module: Communicates with UWB tags worn by miners / vehicles and is deployed above the turnstile. For example, it communicates with UWB tags integrated into miners' lamp caps or UWB tags installed on mine vehicles, achieving a positioning accuracy better than 30 centimeters. The UWB positioning base station module and UWB tags can obtain precise absolute coordinates and unique identification ID information of each other.
[0042] Infrared thermal imaging module: Employs an uncooled vanadium oxide microbolometer core, with a resolution of 384x288 and thermal sensitivity <50mK. Used to acquire infrared thermal radiation images of targets in low-light, high-dust environments, distinguishing between humans and vehicles based on the shape characteristics of the heat source.
[0043] Intrinsically safe explosion-proof enclosure: All the above sensor modules are integrated into the explosion-proof enclosure of the gate, meeting the explosion-proof requirements of underground coal mines.
[0044] 3. The specific control layer is an embedded microprocessor with the main controller at its core, such as an embedded processor using the ARM Cortex-A53 architecture, running a Linux system. It is electrically connected to the various modules of the perception layer and has built-in multi-source information fusion processing algorithms and anti-interference algorithms for: Data processing: Receive and process raw data sent by various sensors, such as preliminary processing of point cloud data from millimeter-wave radar, UWB positioning data, and infrared thermal imaging data.
[0045] Anti-interference processing: Run anti-interference algorithms, such as creating a static environment map around the barrier gate, marking long-term, fixed-location radar scattering points as static background interference (such as metal supports) and filtering them out in real time; based on the dust attenuation model of the signal, dynamically adjust the radar detection sensitivity threshold, and use an adaptive threshold segmentation algorithm for infrared images to distinguish between large-area low-temperature dust clouds and high-temperature, regularly shaped targets.
[0046] Multimodal fusion: The multimodal fusion algorithm is run to first align and synchronize the radar coordinate system, UWB coordinate system and image coordinate system in a unified manner. Then, the nearest neighbor association algorithm is used to associate the dynamic target points detected by the radar, the tag ID location points obtained by the U base station, and the heat source targets identified in the infrared image to form independent "tracking targets". The three types of information are then fused to comprehensively determine the target attributes.
[0047] Command generation: According to the predetermined personnel restriction logic rules, if the association judgment result is an authorized person or authorized vehicle, and its movement trajectory indicates that it intends to approach the gate and pass through, then a gate opening command is generated; if the target is detected to be not carrying a UWB tag or the tag permissions are not consistent, even if the radar and infrared detect the target, a gate opening refusal command is generated, and an audible and visual alarm command can be triggered.
[0048] 4. The specific execution layer involves the gate mechanism receiving instructions from the main controller and executing opening and closing actions. For example, a hydraulically driven barrier gate with anti-collision function can be used. When an opening instruction is received, the gate smoothly lifts; when a target is detected passing through (e.g., radar detects that the target has moved a certain distance away from the gate), a closing instruction is received, and the gate automatically closes.
[0049] II. Methods and Contents.
[0050] This invention also provides a control method for an intelligent personnel restriction gate system in a coal mine, the method comprising: Obtain raw data of the target in front of the gate. The raw data includes: dynamic distance information between the target and the gate, target identity information, and target category information.
[0051] An anti-interference algorithm is used to filter the raw data to remove static interference from downhole metal and suppress dynamic interference from dust, resulting in filtered data. A multimodal fusion algorithm is then used to unify the coordinate system and synchronize the time of the filtered data to form spatiotemporally consistent fused data, resulting in a comprehensive dataset. A nearest neighbor association algorithm is used to associate data within the comprehensive dataset to determine the type of target in front of the gate, obtaining target attribute judgment results. Based on these results, gate control commands are generated.
[0052] Control the gate to perform the corresponding opening and closing actions according to the gate control command.
[0053] Another specific embodiment of the present invention is provided: Step S1: Data acquisition and preprocessing.
[0054] Millimeter-wave radar, UWB base station, and infrared thermal imaging module simultaneously acquire raw data of the target area. Preliminary filtering of the radar point cloud data removes obvious noise points; noise reduction and non-uniformity correction are applied to the infrared images to improve data quality and prepare for subsequent processing.
[0055] Step S2: Anti-interference processing based on the downhole environment.
[0056] Metal static interference filtering: Through continuous learning, a static environment map around the barrier gate is established. Radar scattering points that exist for a long time and whose positions remain unchanged are marked as static background interference (such as metal supports), and are filtered out in real time during subsequent detection to reduce metal reflection interference.
[0057] Dust dynamic interference suppression: Based on the dust attenuation model of the signal, the detection sensitivity threshold of the radar is dynamically adjusted to adapt to different dust concentration environments; an adaptive threshold segmentation algorithm is used for infrared images to effectively distinguish large-area low-temperature dust clouds from high-temperature, regularly shaped targets, thereby reducing the impact of dust interference.
[0058] Step S3: Multimodal information fusion and target decision-making.
[0059] Spatiotemporal alignment: The radar coordinate system, UWB coordinate system and image coordinate system are aligned and synchronized in time to ensure the consistency of data from different sensors in spatiotemporal space.
[0060] Target association: The nearest neighbor association algorithm is used to associate the dynamic target points detected by the radar, the tag ID location points obtained by the U base station, and the heat source targets identified in the infrared image to form independent "tracking targets" for easy comprehensive analysis.
[0061] Attribute discrimination: The system integrates three types of information for comprehensive discrimination. If a target has a radar motion trajectory, a valid UWB identity ID, and a human-like thermal imaging outline, it is determined to be an authorized person. If it has a radar motion trajectory, a valid UWB vehicle ID, and a high-temperature heat source resembling a vehicle engine, it is determined to be an authorized vehicle.
[0062] Step S4: Intelligent logic control and execution.
[0063] Specific examples Figure 3 As shown, the personnel positioning platform checks whether entry into the restricted area is permitted based on vehicle / personnel information. If the association result indicates authorized personnel or vehicles, and their movement trajectory shows an intention to approach the barrier gate, the dynamic target recognizer transmits the information to the control layer. The control layer compares the target information with the personnel movement platform data. If the control layer grants permission, the main controller sends an opening command to the gate, and the gate opens. If the target is detected without a UWB tag or with incorrect tag permissions, even if the radar and infrared sensors detect the target, the controller will refuse to open the gate and may trigger an audible and visual alarm to indicate the abnormal situation.
[0064] After the gate is opened, the controller continuously monitors the target's passage status through sensors. After confirming passage, the gate is closed after a delay, completing the control process for one person or vehicle passage.
[0065] III. Description of Effects.
[0066] 1. High anti-interference capability: Through static map learning and dynamic dust suppression algorithm, the core pain points of downhole metal reflection and dust interference are effectively solved, which greatly reduces the false alarm rate and false alarm rate of the system and improves the system stability.
[0067] 2. High recognition accuracy: It integrates the advantages of three technologies: motion sensing (radar), identity recognition (UWB), and shape discrimination (infrared). These technologies complement and verify each other, overcoming the limitations of single sensor technologies, and achieving accurate judgment of targets and identities, thus completely eliminating the "tailgating" phenomenon.
[0068] 3. High environmental adaptability: The application of infrared thermal imaging technology allows it to operate stably in extreme environments such as complete darkness and dust in mines, completely independent of visible light. Furthermore, all designs comply with intrinsically safe explosion-proof standards for mining applications, ensuring safety and reliability.
[0069] 4. Intelligent and integrated: Integrating multiple sensors into one unit and achieving automatic decision-making through intelligent algorithms, forming a complete system solution that greatly improves the automation level and safety of underground personnel management in coal mines.
[0070] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.
Claims
1. A coal mine shaft intelligent personnel-limited barrier system, characterized in that, The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system.
2. The intelligent personnel gate system for coal mine shafts as claimed in claim 1, characterized in that, The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system.
3. The intelligent personnel gate system for coal mine shafts as claimed in claim 1, characterized in that, The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system.
4. The intelligent personnel gate system for coal mine shafts of claim 1, wherein, The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. 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The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control system. The application relates to a barrier gate control The dynamic distance information detected by the millimeter wave radar module, the target identity information acquired by the UWB positioning base station module, and the target category information identified by the infrared thermal imaging module in the screening data are associated and matched to form an independent tracking target, and a comprehensive data set is obtained.
5. The intelligent personnel gate system for coal mine shafts of claim 1, wherein, The nearest neighbor association algorithm built in the control layer is used for data association on the comprehensive data set to determine the type of the target in front of the gate, and a target attribute judgment result is obtained, specifically including: If the target in front of the gate has radar motion trajectory from the millimeter wave radar module, unique identity ID information from the UWB positioning base station module, and human thermal imaging profile from the infrared thermal imaging module, the target attribute judgment result is an authorized person; If the target in front of the gate has radar motion trajectory from the millimeter wave radar module, unique identity ID information from the UWB positioning base station module, and vehicle engine high-temperature heat source feature from the infrared thermal imaging module, the target attribute judgment result is an authorized vehicle.
6. The intelligent personnel gate system for coal mine shafts of claim 1, wherein, The control layer is specifically used for generating a gate control instruction according to the target attribute judgment result, including: If the target is simultaneously identified as having dynamic distance information from the millimeter wave radar module, unique identity ID information from the UWB positioning base station module, and category information from the infrared thermal imaging module, and its motion trajectory is approaching and passing through the gate, an open gate instruction is generated; If the target does not carry a UWB tag or the tag permission is not matched, a gate opening rejection instruction is generated and a sound and light alarm is triggered.
7. The intelligent personnel gate system for coal mine shafts of claim 1, wherein, The execution layer continuously monitors the passing state of the target after the gate is opened, and controls the gate to close with a delay after confirming the passing of the target.
8. A control method of an intelligent personnel-limited gate system of a coal mine shaft, characterized by, It includes: Obtaining the original data of the target in front of the gate, the original data including: dynamic distance information of the target and the gate, target identity information, and target category information; Using an anti-interference algorithm to screen the original data to filter out underground metal static interference and suppress dust dynamic interference to obtain screening data; using a multi-modal fusion algorithm to coordinate the coordinate system and synchronize the time of the screening data to form spatiotemporally consistent fusion data to obtain a comprehensive data set; using a nearest neighbor association algorithm to data associate the comprehensive data set to determine the type of the target in front of the gate to obtain a target attribute judgment result, and generating a gate control instruction according to the target attribute judgment result; Controlling the gate to perform corresponding opening and closing actions according to the gate control instruction.