Coal mine solid intelligent filling support robot

Abstract

The present invention discloses a coal mine solid intelligent filling support robot, including eight systems consisting of a mechanical body system, a perception system, an AI video analysis system, an analysis and decision system, a software system, a control drive system, a power system, and a human-computer interaction system. The eight systems implement adaptive filling support, parameter perception, working condition identification, process self-driving, programmable, remote control operation, and digital twin functions one by one or in groups, and execute the operation logic according to the mining and filling process self-driving to complete the complete self-driving process. It realizes autonomous operation of adaptive support and filling, ensures that the quality of support and filling meets the requirements, effectively improves the efficiency of filling operations, and realizes green, safe, intelligent, and efficient solid filling mining. It can replace traditional coal miners to implement underground coal mining and filling operations, and is particularly suitable for underground solid intelligent filling mining sites in coal mines.

Description

Technical Field

[0001] The invention relates to a robot for underground coal mining and filling operations, and in particular to a coal mine solid intelligent filling and supporting robot. Background Art

[0002] At present, the demand for underground source treatment of bulk coal-based solid waste is increasing day by day, and the rigid development of solid intelligent filling technology is imminent. Although the existing filling technology has obvious advantages in the in-situ disposal of deep well gangue and surface deformation control, it has not reached the level of high efficiency and high yield, and cannot meet the actual engineering needs of the industry for the time being, which restricts its progress as the main mining method to serve the green construction of mines on a large scale. The reasons are: the core filling equipment has poor adaptability to complex geological conditions and low reliability under complex working conditions. The comprehensive mechanized solid filling process requires manual operation of the electro-hydraulic control button or the reversing valve stem. The mining and filling process has many links, the execution and switching time is long, the mining and filling processes are grouped and executed in sequence, the process is decentralized, and the degree of automation is low. Compared with traditional comprehensive mining, the recovery efficiency of backfill mining is reduced by nearly 30% and the cost per ton of coal is increased by about 15%. There are technical bottlenecks such as low single-face output, multiple types of work on the working face and low work efficiency, which significantly affects the large-scale promotion and utilization of backfill mining technology, and seriously restricts its progress as the main mining method to serve the green construction of mines on a large scale. Therefore, there is an urgent need to develop backfill support robots to upgrade backfill mining technology. Summary of the invention

[0003] In order to overcome the above-mentioned shortcomings, the purpose of the present invention is to provide a coal mine solid intelligent filling support robot for integrating support and filling in the working face filling area, with real-time monitoring of material feeding and filling process, automatic judgment of filling rate and automatic identification of filling body shape, etc., to realize autonomous filling operation under reliable support conditions and ensure that the filling rate and quality meet the requirements.

[0004] In order to achieve the above objectives, the technical solution adopted by the present invention is: a coal mine solid intelligent filling and support robot, including eight systems consisting of a mechanical body system, a perception system, an AI video analysis system, an analysis and decision-making system, a software system, a control and drive system, a power system, and a human-computer interaction system. The eight systems implement adaptive filling and support, parameter perception, working condition identification, process self-drive, programmable, remote control operation, and digital twin functions one by one or in groups, and self-drive according to the mining and filling process. Execution logic completes the complete self-driving process.

[0005] Preferably, the mechanical body system adopts front and rear top beams and four-link coaxial articulation, the front vertical support mechanical arm and the rear vertical support mechanical arm are respectively articulated to the front and rear top beams and the base, the compaction mechanical arm is articulated to the base and its swing angle is controlled by the swing beam mechanical arm, the material transport multi-hole bottom unloading conveyor is suspended on the rear top beam and its front and rear travel is controlled by the rear pull sliding mechanical arm, as well as the overall structure consisting of a first-level guarding mechanical arm, a second-level guarding mechanical arm, a telescopic beam mechanical arm, a front top beam side thrust mechanical arm, a rear top beam side thrust mechanical arm, a front pushing mechanical arm, and a balancing mechanical arm.

[0006] Preferably, the sensing system is composed of stroke, inclination, distance, pressure and inertia sensors, and the sensors are contact or non-contact; wherein: the stroke sensor is used to sense the stroke of each robotic arm, and is respectively installed on the front vertical support robotic arm, the rear vertical support robotic arm, the balancing robotic arm, the compacting robotic arm and the swing beam robotic arm; the inclination sensor is used to sense the sinking angle of the front and rear top beams, the horizontal inclination angle of the base and the angle between the front connecting rod and the base, and is respectively installed on the front and rear top beams, the base and the front connecting rod; the distance sensor is used to monitor and sense the height of the top beam from the base, and is installed at the hinge of the front and rear top beams; the pressure sensor is used to sense the supporting force of the front and rear vertical support robotic arms and the compacting force of the compacting robotic arm of the mechanical body mechanism, and is respectively installed at the bottom of the front and rear vertical support robotic arms and the bottom of the compacting robotic arm; the inertia sensor is used to sense the inclination of the mechanical body, and is installed on the base.

[0007] Preferably, the AI ​​video analysis system is composed of an AI camera, computer vision and image processing algorithm hardware and software. The AI ​​camera includes a depth camera, an infrared camera or a pan-tilt camera. The AI ​​camera is installed in the middle of the rear vertical supporting mechanical arm in the middle of the rear top beam to collect unloading and compaction scenes, monitor the angle, stroke and drop height of the compaction mechanical arm, and verify the data of inclination sensors and stroke sensors. The AI ​​video analysis system analyzes the interference between the compaction mechanical arm and the material transport multi-hole bottom unloading conveyor.

[0008] Preferably, the analysis and decision-making system is composed of a database of mechanical body parameters and environmental working condition parameters, a large amount of video and analysis index set shot by an AI video analysis system, a mechanical body mechanism interference identification and control algorithm, a process autonomous organization algorithm, a process action path autonomous planning algorithm, and software and hardware. The software and hardware include but are not limited to a central processing unit, a storage device, a cloud server, a database client, and a management system.

[0009] Preferably, the software system is developed by a software platform and a core algorithm to achieve big data feedback fusion of the perception system, mechanical body system, control drive system, and AI video analysis system. The software platform includes configuration software, simulation software, etc.

[0010] Preferably, the control drive system is composed of a mechanical body, an electro-hydraulic control system, and a closed-loop feedback control algorithm.

[0011] Preferably, the power system is composed of a pump station, pipelines and sensors installed on the pipelines, so as to realize the power supply for the front and rear vertical support mechanical arms, material unloading, compaction and other process actions.

[0012] Preferably, the human-machine interaction system is composed of an industrial display and a handheld remote control, so as to realize real-time display and manual intervention of the whole filling process.

[0013] Preferably, the function of the adaptive filling support integrates the analysis and decision-making system, the adaptive hydraulic power supply of the power system and the electro-hydraulic adaptive control of the control drive system on the basis of the mechanical body structure, so as to realize the process actions of the mechanical body adaptively supporting the top plate, unloading materials and compacting materials.

[0014] Preferably, the parameter perception function is that the perception system perceives in real time the stroke and working resistance of each robotic arm, the posture parameters of the mechanical body, and the inclination parameters of the mechanical body base and uploads them to the analysis and decision-making system to form a mechanical body posture database and an environmental working condition parameter database.

[0015] Preferably, the function of working condition identification is supported by the AI ​​video analysis system and the analysis and decision-making system, which integrates the mechanical body identification, external environment identification and abnormal working condition judgment modules, analyzes the massive videos and analysis indicator sets taken by the AI ​​video analysis system, and determines the abnormal working condition identification results of the entire filling process.

[0016] Preferably, the self-driving function of the process is supported by a perception system, an AI video analysis system, an analysis and decision-making system, and a control and drive system. It perceives the posture parameters of the mechanical body and the environmental working condition parameters and verifies them with the AI ​​video analysis results, plans the mechanism actions and outputs action instructions to the control and drive system, so as to realize the self-driving execution of unloading, compaction, rack moving, and rack adjustment processes.

[0017] Preferably, the programmable function is supported by a software system, integrating the upper computer software program programming and PLC control programming functions to achieve real-time adjustment of the mechanism action sequence and parameters.

[0018] Preferably, the remote control function is supported by a software system and a human-computer interaction system, integrating the NFC near-field communication function and the remote three-dimensional display module to adjust the motion parameters of the mechanical body and realize remote control of the mechanical body's motion behavior.

[0019] Preferably, the functions of the digital twin are supported by the mechanical system, the perception system and the human-computer interaction system, which retrieve the motion parameters of the mechanical body and the environmental working condition parameters and integrate the three-dimensional model of the mechanical body, and control the synchronization of the three-dimensional model and the actual machine motion in real time to achieve virtual real-time mapping of the entire process of the mechanical body posture and filling process.

[0020] Preferably, the self-driving execution operation logic of the collection and filling process starts the power system to supply power, calls the mechanical body posture database and environmental working condition parameter database perceived by the perception system, retrieves the abnormal working condition identification result of the whole process of the filling process determined by the AI ​​video analysis system, and transmits the perception parameters and the identification results to the analysis and decision system. The analysis and decision system performs the next step of robot arm motion planning, outputs the action instructions to the control drive system, and adjusts and corrects the action parameters of each robot arm in combination with the PID action error. At the same time, the action parameters are synchronously transmitted to the software system and the human-computer interaction system to realize the three-dimensional mapping of the real machine action. The self-driving execution operation logic of the collection and filling process explains the internal coordination logic of the eight systems in the self-driving process: the mechanical body system, the perception system, the AI ​​video analysis system, the analysis and decision system, the control drive system, the power system, the software system and the human-computer interaction system.

[0021] Preferably, the complete self-driving process is a "mining, supporting, transporting, unloading and tamping" process flow, which is characterized in that the logic of the connection between the mechanical body movements in the "mining, supporting, transporting, unloading and tamping" self-driving process is clarified, specifically: by starting the power system, calling the parameter perception function of the perception system to perceive the mechanical body's posture, calling the analysis results of the AI ​​video analysis system to verify each other, calling the analysis and decision-making system's working condition recognition function to determine whether there is unloading interference, and if there is interference, calling the control drive system process self-driving function to regulate the mechanism to act until the interference disappears, and then self-driving to execute the blanking process action, the perception system perceives the blanking height in real time, and after reaching the specified blanking height, calling the control drive system to self-drive to close the unloading port and enter the tamping process; before tamping, calling the parameter perception system and the AI ​​video analysis system to compare and obtain the mechanical body's posture Posture, based on the posture parameters, the working condition recognition function is executed to analyze whether the compaction action planning will cause mechanism interference. If there is interference, the compaction action is replanned until the interference disappears. Then the compaction mechanism is autonomously driven to extend, and the action parameters of the mechanical body are uploaded to the software system and the human-computer interaction system in real time, and the three-dimensional mapping of the real machine is completed through the digital twin function; when the compaction mechanism is retracted, the above-mentioned parameter perception, working condition recognition, process self-driving and digital twin functions are repeated to complete a compaction action; then the process self-driving function of the control drive system is called to adjust the compaction angle by adjusting the stroke of the swing beam robot arm, and the compaction process action logic is repeated to carry out the next compaction; according to the above logic, the designed number of compaction actions are completed, the next blanking is started, and the blanking and compaction action logic is repeated to complete the filling process flow.

[0022] Preferably, in the entire process flow of the compaction of blanking, the function of the digital twin synchronously displays the actual machine action, intervenes in the human-computer interaction system in real time, starts and stops with one button, edits the process action combination and modifies the action parameters, and realizes programmable and remote control operation functions.

[0023] Beneficial effects of the invention: The invention effectively solves the technical problems of low single-face yield level, multiple types of work on the working face, and low work efficiency; the support and filling of the working face filling area are integrated, and it has the functions of real-time monitoring of the feeding and filling process, automatic determination of the filling rate, and automatic identification of the filling body shape, so as to realize autonomous filling operations under adaptive and reliable support conditions, and ensure that the filling rate and quality meet the requirements. Sensors, computer vision, digital twins and other technologies are used to realize autonomous perception of working conditions under complex environmental conditions, theoretical research and design algorithms, models and data sample libraries are used to realize reliable division, definition and characterization of all working conditions, numerical and physical simulation platforms are used to realize autonomous identification and regulation of abnormal working conditions and autonomous execution of all mining and filling processes, and digital twin technology is used to realize virtual monitoring and operation and maintenance of filling equipment. It has shown unique technical advantages in solid intelligent filling mining. It solves the problems of adaptively supporting the mine roof, transporting filling materials to the goaf, providing sufficient filling power for the filling equipment, detecting mine data, warning and predicting mine disasters, and remotely and autonomously executing the filling process. It realizes dense filling of goafs, lossless green mining, unmanned intelligent mining with robots replacing workers, and remote unmanned autonomous operation. The work efficiency is three times that of miners, and mining can be carried out efficiently and safely. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a system framework diagram of this embodiment;

[0025] Figure 2 This is the self-driving execution logic diagram of the collection and filling process of this embodiment;

[0026] Figure 3 It is a complete self-driven process flow chart of "mining, support, transportation, unloading and ramming" in this embodiment.

[0027] In the figure:

[0028] 101-first level guard plate, 102-second level guard plate, 103-first level guard mechanical arm, 104-telescopic beam, 105-second level guard mechanical arm, 106-front exploration beam, 107-telescopic beam mechanical arm;

[0029] 201-front top beam side push mechanical arm, 202-front top beam, 203-rear top beam side push mechanical arm, 204-rear top beam, 205-upper connecting rod, 206-front connecting rod, 207-rear connecting rod, 208-rear vertical support mechanical arm, 209-base, 210-front push mechanical arm, 211-front vertical support mechanical arm, 212-balance mechanical arm, 213-industrial display;

[0030] 301-rear pull-sliding mechanical arm, 302-rear hinged beam, 303-high-strength chute suspension chain, 304-porous bottom discharge conveyor slide rail, 305-waste material compaction, 306-waste material transportation;

[0031] 401-swing beam mechanical arm, 402-baffle, 403-swing beam, 404-tamping mechanical arm;

[0032] 501-travel sensor, 502-tilt sensor, 503-height sensor, 504-pressure sensor, 505-inertial sensor, 506-AI camera. DETAILED DESCRIPTION

[0033] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more definite definition of the protection scope of the present invention.

[0034] See also Figure 1-3 As shown, the present embodiment discloses a coal mine solid intelligent filling support robot, which can replace traditional coal miners to implement underground coal mining and filling operations, and is particularly suitable for comprehensive mechanized solid intelligent filling mining face filling coal mining, including eight systems consisting of a mechanical body system, a perception system, an AI video analysis system, an analysis and decision-making system, a software system, a control and drive system, a power system, and a human-computer interaction system. The eight systems implement adaptive filling support, parameter perception, working condition identification, process self-driving, programmable, remote control operation, and digital twin functions one by one or in groups, and complete the complete self-driving process (i.e., autonomously execute the complete self-driving process flow of "mining, support, transportation, unloading and tamping" of solid intelligent filling in coal mines) according to the self-driving execution operation logic of the mining and filling process.

[0035] The mechanical main body system mainly adopts the front and rear top beams and four-link coaxial hinges, four vertical support arms, the compaction mechanical arm is hinged to the base and its swing angle is controlled by the inclined pull mechanical arm, the material transport multi-hole bottom unloading conveyor hangs the material on the rear top beam and its front and rear travel is controlled by the rear pull sliding mechanical arm, and the overall structure consists of 12 groups of mechanical arms including the first-level guarding mechanical arm 103, the second-level guarding mechanical arm 105, the telescopic beam mechanical arm 107, the front top beam side thrust mechanical arm 201, the rear top beam side thrust mechanical arm 203, the front push mechanical arm 210, and the balancing mechanical arm. Figure 1As shown, the main structure includes a primary guard plate 101, a secondary guard plate 102, a primary guard mechanical arm 103, a telescopic beam 104, a secondary guard mechanical arm 105, a front exploration beam 106, a telescopic beam mechanical arm 107, a front top beam side pushing mechanical arm 201, a front top beam 202, a rear top beam side pushing mechanical arm 203, a rear top beam 204, an upper connecting rod 205, a front connecting rod 206, a rear connecting rod 207, a rear supporting mechanical arm 208, a base 209, a front pushing mechanical arm 210, a front supporting mechanical arm 211, a balancing mechanical arm 212, a rear pulling sliding mechanical arm 301, a rear articulated beam 302, a high-strength chute suspension chain 303, a multi-hole bottom unloading conveyor slide rail 304, a swing beam mechanical arm 401, a baffle 402, a swing beam 403 and a compacting mechanical arm 404.

[0036] The sensing system is composed of sensors of travel type, inclination type, distance type, pressure type, and inertia type. The sensors are contact or non-contact type (a total of 5 types and 9 types of contact and non-contact sensors). Among them: the travel type sensors are used to sense the travel of each mechanical arm, and are respectively installed on the front vertical support mechanical arm, the rear support mechanical arm, the balance mechanical arm, the compaction mechanical arm and the swing beam mechanical arm; the inclination type sensors are used to sense the sinking angle of the front and rear top beams, the horizontal inclination angle of the base, and the angle between the front connecting rod and the base, and are respectively installed on the front and rear top beams, the base and the front connecting rod; the distance type sensors are used to monitor and sense the height of the top beam from the base, and are installed at the hinge of the front and rear top beams; the pressure type sensors are used to sense the support force of the front and rear support mechanical arms of the mechanical body and the compaction force of the compaction mechanical arm, and are respectively installed at the bottom of the front vertical support mechanical arm, the rear vertical support mechanical arm and the compaction mechanical arm; the inertia type sensors are used to sense the inclination angle of the mechanical body, and are installed on the base.

[0037] Specifically, sensor installation interfaces or built-in sensors are reserved on the main structure of the mechanical body: such as travel sensor 501, tilt sensor 502, height sensor 503, inertial sensor 505, and industrial display screen 213, forming the mechanical system of the coal mine solid intelligent filling and support robot, realizing gangue material transportation 306 and gangue material compaction 305; based on the pump station and pipelines matching the mechanical body, and sensor installation positions or built-in sensors are reserved on the key pipelines of the mechanical body: pressure sensor 504, forming the power system of the coal mine solid intelligent filling and support robot.

[0038] Then, 9 types of sensors of 5 categories are set to realize the precise perception function of five levels of data: mechanical body working mechanism parameters, internal mechanism position, spatial relative position, external working condition parameters, and external environment parameters. Among them, parameters such as stroke / pressure are perceived by contact sensors, and working condition parameters such as drop height are perceived by non-contact sensors in multiple dimensions, forming the perception system of the coal mine solid intelligent filling support robot. The schematic diagram of the perception system sensor configuration is shown in the figure. Figure 1 shown.

[0039] According to different usage scenarios, the AI ​​video analysis system is composed of an AI camera 506, computer vision and image processing algorithm hardware and software. The AI ​​camera includes a depth camera, an infrared camera or a pan-tilt camera, etc. The AI ​​camera is installed in the middle of the rear vertical support robot arm in the middle of the rear top beam to collect unloading and compaction scenes, monitor the compaction robot arm angle, stroke and drop height, and verify the data with the inclination sensors (such as the swing beam angle sensor) and the stroke sensors (compacting cylinder stroke sensor). The AI ​​video analyzes the interference between the compaction robot arm and the multi-hole bottom unloading conveyor for transporting materials.

[0040] The analysis and decision-making system consists of a database of mechanical parameters and environmental working condition parameters, a large amount of video and analysis index set taken by the AI ​​video analysis system, an interference recognition and control algorithm for the mechanical body, an autonomous process organization algorithm, an autonomous process action path planning algorithm, and software and hardware (CPU, storage device, cloud server, database client, and management system). The working condition recognition function is realized based on the perception parameters of the perception system and the analysis results of the AI ​​video analysis system, and the process self-driving function is realized in combination with the control drive system.

[0041] The software system is developed by the software platform and core algorithms to realize the big data feedback fusion of the perception system, mechanical system, control and drive system, and AI video analysis system. The software platform includes configuration software, simulation software, etc.

[0042] The control drive system consists of a mechanical body, an electro-hydraulic control system, and a closed-loop feedback control algorithm.

[0043] The power system consists of a pump station, pipelines and sensors installed on the pipelines, which can provide power to support the robot arm movements, material unloading, compaction and other process movements.

[0044] The human-machine interaction system consists of an industrial display and a handheld remote control, which enables real-time display and manual intervention of the entire filling process.

[0045] The function of adaptive filling support integrates the analysis and decision-making system, the adaptive hydraulic power supply of the power system, and the electro-hydraulic adaptive control of the control drive system on the basis of the mechanical body structure. It realizes the process actions of the mechanical body adaptively supporting the top plate, unloading materials, and compacting materials.

[0046] The parameter perception function is that the perception system perceives the stroke and working resistance of each robotic arm, the posture parameters of the mechanical body, and the inclination parameters of the mechanical body base in real time and uploads them to the analysis and decision-making system to form a mechanical body posture database and an environmental working condition parameter database.

[0047] The function of working condition identification is supported by the AI ​​video analysis system and the analysis and decision-making system, which integrates the mechanical body identification, external environment identification and abnormal working condition judgment modules, analyzes the massive videos and analysis indicator sets taken by the AI ​​video analysis system, and determines the abnormal working condition identification results of the entire filling process.

[0048] The process self-driving function is supported by the perception system, AI video analysis system, analysis and decision-making system, and control and drive system. It perceives the machine body posture parameters and environmental parameters and verifies them with the AI ​​video analysis results, plans the mechanism action and outputs the action command to the control and drive system. It realizes the self-driving execution of unloading, compaction, rack transfer, and rack adjustment processes.

[0049] The programmable function is supported by the software system, which integrates the upper computer software program programming and PLC control programming functions. It realizes the real-time adjustment of the mechanism action sequence and parameters.

[0050] The remote control function is supported by the software system and the human-computer interaction system, integrating the NFC near-field communication function and the remote three-dimensional display module to adjust the mechanical body's motion parameters and realize remote control of the mechanical body's motion behavior.

[0051] The functions of the digital twin are supported by the mechanical system, the perception system and the human-computer interaction system. It perceives the motion parameters of the mechanical body and the environmental working conditions and integrates the three-dimensional model of the mechanical body. It controls the synchronization of the three-dimensional model and the actual machine motion in real time to achieve virtual real-time mapping of the entire process of the mechanical body's posture and filling process.

[0052] The self-driving execution logic of the filling process explains the internal coordination logic of the eight major systems in the self-driving process, namely the mechanical body system, the perception system, the AI ​​video analysis system, the analysis and decision-making system, the control and drive system, the power system, the software system and the human-computer interaction system. By starting the power system to supply power, the mechanical body posture database and the environmental working condition parameter database perceived by the perception system are called, and the abnormal working condition identification results of the whole filling process determined by the AI ​​video analysis system are retrieved. The perception parameters and the identification results are transmitted to the analysis and decision-making system together. The analysis and decision-making system carries out the next step of robot arm motion planning, outputs the motion instructions to the control and drive system, and adjusts the motion parameters of each robot arm in combination with the PID motion error. At the same time, the motion parameters are synchronously transmitted to the software system and the human-computer interaction system to realize the three-dimensional mapping of the actual machine motion.

[0053] The complete self-driving process is the "mining, support, transportation, unloading and tamping" process flow, which is characterized by clarifying the logic of the mechanical body action connection in the "mining, support, transportation, unloading and tamping" self-driving process, specifically: by starting the power system, calling the parameter perception function of the perception system to perceive the mechanical body posture, calling the analysis results of the AI ​​video analysis system to verify each other, calling the analysis and decision-making system working condition recognition function to determine whether there is unloading interference, if there is interference, calling the control drive system process self-driving function to adjust the mechanism action until the interference disappears, and then self-driving executes the blanking process action, the perception system senses the blanking height in real time, and after reaching the specified blanking height, calls the control drive system to self-drive to close the unloading port and enter the tamping process; before tamping, call the parameter perception system and AI video analysis system for comparison to obtain the mechanical body posture, The working condition recognition function is executed based on the posture parameters to analyze whether the planned compaction action will cause mechanism interference. If there is interference, the compaction action is re-planned until the interference disappears. Then the compaction mechanism is autonomously driven to extend, and the mechanical body motion parameters are uploaded to the software system and the human-computer interaction system in real time, and the three-dimensional mapping of the real machine is completed through the digital twin function; when the compaction mechanism retracts, the above-mentioned parameter perception, working condition recognition, process self-driving and digital twin functions are repeated to complete a compaction action; then the process self-driving function of the control drive system is called to adjust the compaction angle by adjusting the stroke of the swing beam robot arm, and the compaction process action logic is repeated to carry out the next compaction; according to the above logic, the designed number of compaction actions are completed, the next blanking is started, and the blanking and compaction action logic is repeated to complete the filling process flow.

[0054] During the entire process of compacting the blanking material, the digital twin function synchronously displays the actual machine actions, intervenes in the human-computer interaction system in real time, and enables one-click start and stop, editing of process action combinations, and modification of action parameters to realize programmable and remote control operation functions.

[0055] This embodiment integrates configuration software, simulation software and other software platforms with core algorithms to form a software system, realizes the big data feedback fusion of the perception system, mechanical body system, control drive system, and AI video analysis system, and has the functions of historical data storage, remote control, monitoring and early warning, and programmability of the solid intelligent filling support robot in coal mines; finally, based on the perception system, mechanical body system and human-computer interaction system, virtual reality, augmented reality and mixed reality technologies are used to realize the digital twin function, realize the synchronous multi-dimensional display of the working process of the solid intelligent filling support robot in coal mines, and realize the virtual monitoring of the solid intelligent filling support robot in coal mines and the feedback and optimization of the filling effect.

[0056] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A coal mine solid intelligent filling support robot, characterized by: It includes eight systems consisting of a mechanical body system, a perception system, an AI video analysis system, an analysis and decision-making system, a software system, a control and drive system, a power system, and a human-computer interaction system. The eight systems implement adaptive filling support, parameter perception, working condition identification, process self-driving, programmable, remote control operation, and digital twin functions one by one or in groups, and execute the operation logic of the mining and filling process self-driving to complete the complete self-driving process; The mechanical body system adopts front and rear top beams and four-link coaxial articulation, the front vertical support mechanical arm and the rear vertical support mechanical arm are respectively articulated on the front and rear top beams and the base, the compaction mechanical arm is articulated on the base and its swing angle is controlled by the swing beam mechanical arm, the material transport multi-hole bottom unloading conveyor is suspended on the rear top beam and its front and rear travel is controlled by the rear pull sliding mechanical arm, and the overall structure consists of a first-level guarding mechanical arm, a second-level guarding mechanical arm, a telescopic beam mechanical arm, a front top beam side thrust mechanical arm, a rear top beam side thrust mechanical arm, a front push mechanical arm, and a balancing mechanical arm; The sensing system is composed of sensors of travel type, inclination type, distance type, pressure type, and inertia type, and the sensors are contact or non-contact type; The AI ​​video analysis system is composed of an AI camera, computer vision and image processing algorithm hardware and software. The AI ​​camera includes a depth camera, an infrared camera or a pan / tilt camera. The AI ​​camera is installed in the middle of the rear vertical support mechanical arm in the middle of the rear top beam to collect unloading and compaction scenes, monitor the angle, stroke and drop height of the compaction mechanical arm, and verify the data of the inclination sensor and the stroke sensor. The AI ​​video analysis system analyzes the interference between the compaction mechanical arm and the multi-hole bottom unloading conveyor for transporting materials; The analysis and decision-making system is composed of a database of mechanical body parameters and environmental working condition parameters, a massive amount of video and analysis indicator set shot by an AI video analysis system, a mechanical body mechanism interference identification and control algorithm, a process autonomous organization algorithm, a process action path autonomous planning algorithm, and software and hardware; The software system is developed by the software platform and the core algorithm to realize the big data mutual feedback fusion of the perception system, the mechanical body system, the control drive system, and the AI ​​video analysis system. The software platform includes configuration software and simulation software; The control drive system is composed of a mechanical body, an electro-hydraulic control system, and a closed-loop feedback control algorithm; The power system is composed of a pump station, pipelines and sensors installed on the pipelines; The human-computer interaction system consists of an industrial display and a handheld remote control.

2. The coal mine solid intelligent filling and supporting robot according to claim 1 is characterized in that: The travel sensors are used to sense the travel of each robotic arm and are respectively installed on the front vertical support robotic arm, the rear vertical support robotic arm, the balancing robotic arm, the compacting robotic arm and the swing beam robotic arm; The inclination sensors are used to sense the sinking angle of the front and rear top beams, the horizontal inclination angle of the base, and the angle between the front connecting rod and the base, and are respectively installed on the front and rear top beams, the base, and the front connecting rod; The distance sensor is used to monitor and sense the height between the top beam and the base, and is installed at the hinge of the front and rear top beams; The pressure sensors are used to sense the supporting force of the front and rear vertical supporting mechanical arms and the compacting force of the compacting mechanical arms of the mechanical body mechanism, and are respectively installed at the bottom of the front vertical supporting mechanical arm, the bottom of the rear vertical supporting mechanical arm and the bottom of the compacting mechanical arm.

3. The coal mine solid intelligent filling and supporting robot according to claim 1 is characterized in that: The function of the adaptive filling support is based on the mechanical body structure and integrates the analysis and decision-making system, the adaptive supply of hydraulic power of the power system and the electro-hydraulic adaptive control of the control drive system.

4. The coal mine solid intelligent filling and supporting robot according to claim 1, characterized in that: The parameter perception function is that the perception system perceives the stroke and working resistance of each robotic arm, the posture parameters of the mechanical body, and the inclination parameters of the mechanical body base in real time and uploads them to the analysis and decision-making system to form a mechanical body posture database and an environmental working condition parameter database.

5. The coal mine solid intelligent filling and supporting robot according to claim 1 is characterized in that: The function of working condition identification is supported by the AI ​​video analysis system and the analysis and decision-making system, which integrates the mechanical body identification, external environment identification and abnormal working condition judgment modules, analyzes the massive videos and analysis indicator sets taken by the AI ​​video analysis system, and determines the abnormal working condition identification results of the entire filling process.

6. The coal mine solid intelligent filling and supporting robot according to claim 1, characterized in that: The self-driving function of the process is supported by a perception system, an AI video analysis system, an analysis and decision-making system, and a control and drive system. It perceives the posture parameters of the mechanical body and the environmental working condition parameters and verifies them with the AI ​​video analysis results, plans the mechanism action and outputs the action instructions to the control and drive system.

7. The coal mine solid intelligent filling and supporting robot according to claim 1 is characterized in that: The programmable functions are supported by a software system, integrating upper computer software program programming and PLC control programming functions.

8. The coal mine solid intelligent filling and supporting robot according to claim 1, characterized in that: The remote control function is supported by the software system and the human-computer interaction system, integrating the NFC near-field communication function and the remote three-dimensional display module to adjust the movement parameters of the mechanical body.

9. The coal mine solid intelligent filling and supporting robot according to claim 1, characterized in that: The functions of the digital twin are supported by the mechanical system, the perception system and the human-computer interaction system. It perceives the motion parameters of the mechanical body and the environmental working conditions and integrates the three-dimensional model of the mechanical body, controls the synchronization of the three-dimensional model and the actual machine motion in real time, and realizes virtual real-time mapping of the entire process of the mechanical body posture and filling process.

10. The coal mine solid intelligent filling and supporting robot according to claim 1, characterized in that: The self-driving execution operation logic of the filling process starts the power system to supply power, calls the mechanical body posture database and environmental working condition parameter database perceived by the perception system, retrieves the abnormal working condition identification result of the whole filling process determined by the AI ​​video analysis system, and transmits the perception parameters and the identification result to the analysis and decision-making system. The analysis and decision-making system performs the next step of robot arm motion planning, outputs motion instructions to the control drive system, and corrects the motion parameters of each robot arm in combination with PID motion error adjustment. At the same time, the motion parameters are synchronously transmitted to the software system and the human-computer interaction system to realize three-dimensional mapping of real machine motion.

11. The coal mine solid intelligent filling and supporting robot according to claim 1, characterized in that: The complete self-driving process is a "mining, support, transportation, unloading and tamping" process flow, which starts the power system, calls the parameter perception function of the perception system to perceive the posture of the mechanical body, retrieves the analysis results of the AI ​​video analysis system for mutual verification, calls the working condition recognition function of the analysis and decision-making system to determine whether there is unloading interference, and if there is interference, calls the process self-driving function of the control drive system to adjust the mechanism action until the interference disappears, and then self-drives to perform the blanking process action, and the perception system perceives the blanking height in real time. After reaching the specified blanking height, the control drive system is called to self-drive to close the unloading port and enter the tamping process; before tamping, call the parameter perception system and the AI ​​video analysis system for comparison to obtain the posture of the mechanical body, and execute the working condition recognition function based on the posture parameters to analyze whether the tamping action plan will produce mechanism interference. If there is interference, re-plan the tamping action until the interference disappears, and then autonomously drive the tamping mechanism to extend, and the mechanical body action parameters are uploaded to the software system and the human-computer interaction system in real time, and the real machine three-dimensional mapping is completed through the digital twin function; when the tamping mechanism retracts, the above-mentioned parameter perception, working condition recognition, process self-driving and digital twin functions are repeatedly executed to complete a tamping action; Then, the process self-driving function of the control drive system is called, the compaction angle is adjusted by adjusting the stroke of the swing beam mechanical arm, and the compaction process action logic is repeated to perform the next compaction; the designed number of compaction actions are completed according to the above logic, the next blanking is started, and the blanking and compaction action logic is repeated to complete the filling process flow.

12. The coal mine solid intelligent filling and supporting robot according to claim 11, characterized in that: During the entire process of compacting the blanking material, the digital twin function synchronously displays the actual machine actions, intervenes in the human-computer interaction system in real time, and enables one-key start and stop, editing of process action combinations, and modification of action parameters to realize programmable and remote control operation functions.

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