A multi-bucket turbine intelligent dispatching control method and system

Abstract

The invention discloses an intelligent dispatching control method and system for multiple bucket wheel machines, belonging to the field of electronic information technology, comprising: obtaining spatial position information and cantilever posture of bucket wheel machines through inclinometers, Graham lines and encoders; obtaining surface structure data of a stockpile through a laser scanner, and establishing a three-dimensional model of the stockpile through a multiple spatial variable transposition algorithm; establishing a simplified collision volume block through a physical model of the bucket wheel machine, and checking the motion interference between bucket wheel machines through a separation line theory; establishing a three-degree-of-freedom configuration space of the bucket wheel machine, introducing stockpile information and bucket wheel machine position and posture information into the configuration space, and using a heuristic path-finding algorithm to calculate an optimal dispatching route; realizing intelligent dispatching control of multiple bucket wheel machines, avoiding collision risks between bucket wheel machines and stockpile machines and bucket wheel machines, improving dispatching efficiency, overcoming the difficulty that bucket wheel machines cannot be automatically dispatched, greatly shortening dispatching time, and ensuring safe and stable operation.

Description

Technical Field

[0001] The present invention belongs to the field of electronic information technology, and more specifically, relates to an intelligent dispatching control method and system for a multi-bucket wheel machine. Background Art

[0002] Bucket wheel stacker reclaimer is a high-efficiency continuous loading and unloading machine, mainly used for stacking and reclaiming tasks in large bulk yards. Bucket wheel stacker reclaimer is generally composed of bucket wheel mechanism, slewing mechanism, belt conveyor, pitching and running mechanism. Bucket wheel mechanism and belt conveyor run forward, and adjusting slewing and pitching can complete the reclaiming task. Bucket wheel belt conveyor runs in reverse, and adjusting slewing and other postures can complete the stacking task. In the gap between executing two tasks, the bucket wheel needs to be dispatched, moving from one working material pile position to another working material pile position. In the process of dispatching, there may be motion interference between the bucket wheel and the material pile, or motion interference between multiple bucket wheel machines. If a collision accident occurs, it will directly lead to material supply interruption and economic losses.

[0003] At present, the dispatching and control of bucket wheel stacker reclaimers in domestic steel enterprises generally adopts on-site manual operation or remote manual operation. Operators are required to pay attention to the position and posture of the bucket wheel machine at all times during the dispatching process. Sometimes they need to stop and observe from multiple angles to see if collision can be avoided. This leads to low efficiency and bucket wheel machine collision accidents that affect production.

[0004] In summary, developing intelligent dispatching and control of multiple bucket wheel cranes to enable bucket wheel cranes to automatically and actively avoid obstacles, thereby reducing collision accidents and ensuring the stability of unloading and feeding is a key link in further improving the operating efficiency of the bucket wheel crane system. It is also the basic technology for the full automation transformation of bucket wheel cranes. Summary of the invention

[0005] In view of the above defects or improvement needs of the prior art, the present invention proposes an intelligent scheduling control method and system for multiple bucket wheel excavators, which can solve the problem of automatic scheduling of the position and posture of bucket wheel excavators between tasks, actively avoid obstacles and take a better path, so as to improve the safety and operation efficiency of the bucket wheel excavator system.

[0006] To achieve the above object, according to one aspect of the present invention, a multi-bucket wheel machine intelligent dispatching control method is provided, comprising:

[0007] Accurate positioning of bucket wheel machine position and attitude: The position information of each bucket wheel machine in space and the pitch angle and rotation angle attitude information of the cantilever are obtained through the inclinometer, Graham line, encoder and other sensor equipment installed on the bucket wheel machine;

[0008] Establishment of a three-dimensional model of the stockpile: The surface structure data of the stockpile is obtained through a laser scanner, and a three-dimensional model of the stockpile is established through a multiple spatial variable transposition algorithm. The blocking space is calculated to obtain a feasible range of non-interference between the bucket wheel excavator and the stockpile.

[0009] Multi-bucket wheel machine motion interference detection: A simplified collision detection volume block is established through the physical model of the bucket wheel machine, and the motion interference between the bucket wheels is checked through the separation line theory to calculate the regional space of the collision situation;

[0010] Autonomous pathfinding control: Establish a three-degree-of-freedom configuration space for the bucket wheel machine, introduce the material pile blocking space transformation into the configuration space, introduce the regional space transformation of the bucket wheel machine movement collision situation into the configuration space, and use the autonomous pathfinding algorithm in the configuration space to calculate the optimal obstacle avoidance path based on the position information of each bucket wheel machine in space and the pitch angle and rotation angle posture information of the cantilever.

[0011] In some optional embodiments, the surface structure data of the pile is obtained by a laser scanner device, and a three-dimensional model of the pile is established by a multiple spatial variable transposition algorithm, including:

[0012] Determine the precise installation position and attitude angle data of the laser scanner on each bucket wheel machine on site, and then accurately calibrate the Graham line, encoder and inclinometer of each bucket wheel machine;

[0013] The original data of the laser scanner is processed through a triangulation reconstruction algorithm and a multiple space transformation algorithm to generate original point cloud data. The lightweight point cloud model of the material pile is then obtained through point cloud data multiple filtering technology and a rasterization compression algorithm. The scanning data of multiple laser scanners are fused through a rasterization update method, so that multiple scanners can update the point cloud data simultaneously to obtain the final updated 3D model of the material pile.

[0014] In some optional embodiments, the three-degree-of-freedom configuration space of the bucket wheel machine is established, the material pile blocking space conversion is introduced into the configuration space, and the regional space conversion of the bucket wheel machine movement collision situation is introduced into the configuration space, including:

[0015] According to the bucket wheel machine's travel position x, rotation angle θ and pitch angle γ, the configuration space (x, θ, γ) is constructed. Each state of the bucket wheel machine corresponds to a point in the configuration space. According to the mechanical limit value x of the bucket wheel machine, min ,x max ,θ min ,θ max ,γ min ,γ max Construct a cuboid path search range in the configuration space, where x min ,x maxThey represent the minimum and maximum limit values ​​of the bucket wheel machine's travel position, θ min ,θ max They represent the minimum and maximum limit values ​​of the bucket wheel excavator's rotation angle, γ min ,γ max They respectively represent the minimum limit value and the maximum limit value of the bucket wheel machine's pitch angle;

[0016] The configuration space is meshed according to the speed of each degree of freedom of the bucket wheel machine to ensure that the meshes in three dimensions are consistent in time scale;

[0017] After the grid is divided, each grid has its coordinate value (x i ,θ i ,γ i ) also has the attribute of whether it is blocked. If the bucket wheel machine collides with other bucket wheels, material piles, and track platforms at the position and posture represented by this coordinate value, the blocking attribute of the grid is true, otherwise it is false. i ,θ i ,γ i ) represents the travel position x of the bucket wheel machine represented by the i-th grid i 、Rotation angle θ i and pitch angle γ i ;

[0018] Using the physical space model of the bucket wheel machine and the three-dimensional model of the stockpile, spatial overlap comparison is performed to calculate all grids with obstructions.

[0019] The blocking grid between bucket wheel machines is calculated by using the spatial model and positional relationship between bucket wheel machines.

[0020] In some optional implementations, an optimal obstacle avoidance path is calculated using an autonomous path-finding algorithm in the configuration space, including:

[0021] Convert the scheduling target point from the task center to the target point in the configuration space (x goal ,θ goal ,γ goal ), and the starting point is the current position of the bucket wheel machine (x start ,θ start ,γ start ), the scheduling calculation problem of bucket wheel excavator is transformed into finding a shorter connected path from the starting point to the target point in the configuration space that avoids the blocking grid, (x goal ,θ goal ,γ goal ) represents the target travel position x of the bucket wheel excavator goal 、Target rotation angle θ goal and the target pitch angle γ goal ,(xstart ,θ start ,γ start ) represents the starting travel position x of the bucket wheel excavator start 、Starting rotation angle θ start and the starting pitch angle γ start ;

[0022] In the constructed configuration space, from the starting point (x start ,θ start ,γ start ) starts to use heuristic search. Each search evaluates the neighborhood grid points. The evaluation function includes cost function and heuristic function. The cost function optimizes the running time of the scheduling path, and the heuristic function reduces the search time and storage space cost, speeding up the calculation process. Each search uses the optimal grid in the evaluation grid, and then iterates to the next search until the starting point (x start ,θ start ,γ start ) Search to the target point (x goal ,θ goal ,γ goal ) is a feasible path.

[0023] In some optional embodiments, the method further comprises:

[0024] After rendering the three-dimensional model of the material pile, a visual display effect is obtained, thereby realizing real-time remote monitoring of the material pile model.

[0025] According to another aspect of the present invention, there is provided an intelligent dispatching and control system for multiple bucket wheel machines, comprising: multiple bucket wheel machines, a position attitude sensor, a laser scanner, an airborne data acquisition processor, a model data storage server, a background computing server, and a bucket wheel machine controller;

[0026] The position and attitude sensors include Graham lines, encoders and inclinometers. The Graham lines are installed on the side of the bucket wheel machine's running track to accurately locate the bucket wheel machine's travel position. The encoder installed on the bucket wheel machine measures the cantilever's rotation position in real time to calculate the rotation angle. The inclinometer installed on the bucket wheel machine's cantilever obtains the cantilever's pitch angle in real time. The travel position, rotation angle and pitch angle are transmitted to the background computing server by the onboard data acquisition processor.

[0027] The laser scanner is installed on the boom of the bucket wheel machine and moves with the boom. The data of the stockpile scan is transmitted to the background computing server for preprocessing to generate a 3D model of the stockpile. The 3D model is stored in the model data storage server after rasterization and denoising algorithm.

[0028] The backend computing server calculates the blocking space based on the three-dimensional model, obtains the feasible range of non-interference between the bucket wheel machine and the stockpile, establishes a simplified collision detection volume block through the physical model of the bucket wheel machine, checks the motion interference between the bucket wheels through the separation line theory, calculates the regional space of the collision situation, establishes the three-degree-of-freedom configuration space of the bucket wheel machine, introduces the stockpile blocking space conversion into the configuration space, and introduces the regional space conversion of the bucket wheel machine motion collision situation into the configuration space. Based on the position information of each bucket wheel machine in space and the pitch angle and rotation angle posture information of the cantilever, the autonomous path-finding algorithm is used in the configuration space to generate the scheduling trajectory node, and transmit it to the bucket wheel machine controller;

[0029] The bucket wheel excavator controller processes the dispatching trajectory nodes to generate control signals to control the movement of the bucket wheel excavator.

[0030] In some optional implementation schemes, the background computing server is used to determine the precise installation position and attitude angle data of the laser scanner on each bucket wheel machine on site, and after accurately calibrating the Graham lines, encoders and inclinometers of each bucket wheel machine, the original data of the laser scanner is subjected to a triangulation reconstruction algorithm and a multiple space transformation algorithm to generate original point cloud data, and then a lightweight stockpile point cloud model is obtained through multiple filtering technology of the point cloud data and a rasterization compression algorithm. The scanning data of multiple laser scanners are fused and processed through a rasterization update method, so that multiple scanners can update the point cloud data at the same time, and the final updated three-dimensional model of the stockpile is obtained.

[0031] In some optional implementation schemes, the background computing server is used to construct a configuration space (x, θ, γ) according to the walking position x, the rotation angle θ and the pitch angle γ of the bucket wheel machine. Each state of the bucket wheel machine corresponds to a point in the configuration space. min ,x max ,θ min ,θ max ,γ min ,γ max Construct a cuboid path search range in the configuration space, where x min ,x max They represent the minimum and maximum limit values ​​of the bucket wheel machine's travel position, θ min ,θ max They represent the minimum and maximum limit values ​​of the bucket wheel excavator's rotation angle, γ min ,γ max They represent the minimum and maximum limit values ​​of the bucket wheel machine's pitch angle respectively; the configuration space is gridded according to the speed of each degree of freedom of the bucket wheel machine to ensure that the grids of the three dimensions are consistent on the time scale; after gridding, each grid has its coordinate value (x i ,θi ,γ i ) also has the attribute of whether it is blocked. If the bucket wheel machine collides with other bucket wheels, material piles, and track platforms at the position and posture represented by this coordinate value, the blocking attribute of the grid is true, otherwise it is false. i ,θ i ,γ i ) represents the travel position x of the bucket wheel machine represented by the i-th grid i 、Rotation angle θ i and pitch angle γ i ; Using the physical space model of the bucket wheel machine and the three-dimensional model of the stockpile, spatial overlapping comparison is performed to calculate all the blocked grids; using the spatial model and position relationship between bucket wheel machines, the blocked grids between bucket wheel machines are calculated.

[0032] In some optional embodiments, the background computing server is used to convert the scheduling target point from the task center into the target point (x goal ,θ goal ,γ goal ), and the starting point is the current position of the bucket wheel machine (x start ,θ start ,γ start ), the scheduling calculation problem of bucket wheel excavator is transformed into finding a shorter connected path from the starting point to the target point in the configuration space that avoids the blocking grid, (x goal ,θ goal ,γ goal ) represents the target travel position x of the bucket wheel excavator goal 、Target rotation angle θ goal and the target pitch angle γ goal ,(x start ,θ start ,γ start ) represents the starting travel position x of the bucket wheel excavator start 、Starting rotation angle θ start and the starting pitch angle γ start ; In the constructed configuration space, from the starting point (x start ,θ start ,γ start ) starts to use heuristic search. Each search evaluates the neighborhood grid points. The evaluation function includes cost function and heuristic function. The cost function optimizes the running time of the scheduling path, and the heuristic function reduces the search time and storage space cost, speeding up the calculation process. Each search uses the optimal grid in the evaluation grid, and then iterates to the next search until the starting point (x start ,θ start ,γ start ) Search to the target point (xgoal ,θ goal ,γ goal ) is a feasible path.

[0033] In some optional implementation schemes, the background computing server is used to render the three-dimensional model of the material pile to obtain a visual display effect, thereby realizing real-time remote monitoring of the material pile model.

[0034] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:

[0035] 1. By introducing configuration space, collision detection of bucket wheel machine physical model, three-dimensional model of material pile, etc., the optimal path scheduling of multiple bucket wheel machines for intelligent obstacle avoidance is realized, completing a key link in the fully automatic operation of bucket wheel machines, improving the overall operation efficiency of the material yard, and ensuring the safety and reliability of the operation of multiple equipment. At the same time, due to path optimization, energy use is reduced, low-carbon emission reduction is achieved, and good economic benefits and social value are created for the enterprise.

[0036] 2. After the application of the intelligent scheduling and control method for multiple bucket wheel machines of the present invention, the control effect is good, and the intelligent automatic scheduling and control of bucket wheel machines between tasks is realized, overcoming the technical difficulties of active obstacle avoidance scheduling and control of bucket wheel machines. At the same time, it is compatible with different numbers of bucket wheel machine configurations. The entire scheduling process does not require human participation, saving a lot of labor costs.

[0037] 3. The three-dimensional model of the stockpile established by the present invention is conducive to the precise management and monitoring of the production of the stockyard. Based on the three-dimensional model of the stockpile, the active collision avoidance between the bucket wheel machine and the stockpile is realized through the point cloud algorithm. Based on the simplified collision volume block and collision detection algorithm of the bucket wheel machine, the active collision avoidance between the bucket wheel machines is realized, thereby improving the operational safety of the bucket wheel machine.

[0038] 4. The present invention utilizes an autonomous path optimization algorithm in the bucket wheel machine configuration space to realize the optimal calculation of the bucket wheel machine scheduling path, improve the scheduling efficiency of the bucket wheel machine, save energy and reduce carbon emissions, and create good economic benefits and social value for the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a hardware architecture diagram of a multi-bucket wheel excavator intelligent dispatching and control system provided by an embodiment of the present invention;

[0040] Figure 2 It is a flow chart of establishing a three-dimensional model of a stockpile provided by an embodiment of the present invention;

[0041] Figure 3 This is an autonomous path-finding control flow chart provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0043] In view of the problems existing in the operation scheduling and control of multiple bucket wheel machines, the present invention applies laser scanner 3D modeling imaging technology, point cloud data analysis technology and autonomous pathfinding technology to the workflow of bucket wheel machines. By scanning the material pile, a 3D digital model of the material pile is established to obtain the feasible spatial range of the bucket wheel machine. At the same time, active collision detection technology and autonomous pathfinding technology are used to guide the intelligent automatic scheduling of the bucket wheel machine. The position and posture of the bucket wheel machine between tasks can be automatically scheduled, while ensuring that there is no motion interference between the bucket wheel machine and the material pile, the bucket wheel machine and the belt system, and the bucket wheel machine, thereby improving scheduling efficiency and safety.

[0044] This embodiment discloses a method and system for intelligent dispatching and controlling a bucket wheel machine in a blast furnace material yard of a steel enterprise. Since the material yard has been unmanned on site and adopts a remote operation working mode, there are blind spots when manually observing the environment on site through video monitoring, and the machine often stops to adjust the direction of the camera for observation, which affects the working efficiency of the bucket wheel machine and there is a risk of collision of the bucket wheel machine. Therefore, the development of an intelligent dispatching and controlling method for multiple bucket wheel machines under the existing equipment conditions has become an urgent problem for the enterprise to solve.

[0045] In this example, there are three bucket wheel machines in the blast furnace material yard, two of which share a track, and the other uses a separate track. The material piles are distributed on both sides of the track, and there is a risk of collision between the three bucket wheel machines.

[0046] A 2D laser scanner is installed on both sides of the cantilever of each bucket wheel machine. As the cantilever of the bucket wheel machine moves, the pile of materials is scanned, and the scanned data is transmitted back to the airborne data acquisition processor, which is then transmitted to the background server for processing to generate a three-dimensional model of the pile of materials. The three-dimensional model is stored in the database for update after rasterization and denoising algorithm, and the three-dimensional model is updated and displayed in real time at the operation station in the control room. The background computing server constructs the configuration space of the bucket wheel machine and combines the position and posture information of all bucket wheel machines to perform real-time intelligent optimization and anti-collision calculations on the scheduling trajectory of each bucket wheel machine, and sends the calculation results to the bucket wheel machine PLC controller for intelligent scheduling and control of the bucket wheel machine, thereby improving the operating efficiency of the bucket wheel machine, saving energy and reducing carbon emissions, and improving operational safety.

[0047] The intelligent dispatching and control system of multi-bucket wheel machine is mainly divided into two parts: hardware equipment and software program. The hardware equipment mainly includes: 2D laser scanner, network switch, Gray bus communication positioning device, distance encoder, inclinometer, airborne data acquisition processor, model data storage server, background computing server, bucket wheel machine PLC controller, etc. The hardware architecture is as follows Figure 1 As shown. The 2D laser scanner is installed on the bucket wheel machine cantilever. As the cantilever moves, the Gray busbar communication positioning device is installed on the side of the bucket wheel machine's running track to accurately locate the bucket wheel machine's travel position. The distance encoder installed on the bucket wheel machine measures the cantilever's rotation position in real time to calculate the rotation angle value. The inclinometer installed on the bucket wheel machine's cantilever obtains the cantilever's pitch angle in real time. The travel position, rotation angle, and pitch angle are transmitted to the background computing server by the onboard data acquisition processor through the network switch device. The background computing server calculates the bucket wheel machine's dispatching trajectory in real time through the laser scanner data and the real-time position and posture information of multiple bucket wheels, and converts the dispatching trajectory into a control signal and sends it to the bucket wheel machine's PLC controller to control the bucket wheel machine to perform intelligent dispatching tasks.

[0048] The intelligent dispatching and control software for multi-bucket wheel cranes mainly includes: laser scanner data acquisition software, point cloud data processing and storage software, real-time remote operation software for bucket wheel cranes, real-time display software for three-dimensional models of material yards, and control and calculation software for bucket wheel cranes. The laser scanner data acquisition software obtains the original message information of the scanner, and reconstructs the real-time scanned material pile point cloud data by combining the precise installation position and posture information of the scanner, the walking, rotating and pitching data of the bucket wheel crane, and the structural information of the bucket wheel crane. The material pile point cloud data is processed into a lightweight three-dimensional model of the material pile through a variety of filtering methods and compression technologies. The three-dimensional model is written into the model data storage server in real time for storage and backup. The real-time display software of the three-dimensional model of the material pile retrieves the data from the model data storage server, and renders the material pile point cloud data to obtain a visual display effect, which is convenient for operators to observe the changes in the material pile in time. The real-time remote operation software of the bucket wheel crane sends the dispatching task to the control and calculation software of the bucket wheel crane. The control and calculation software of the bucket wheel crane retrieves the latest data from the model data storage server, calculates the optimal dispatching path, and sends it to the PLC controller of the bucket wheel crane, thereby realizing the intelligent dispatching of the bucket wheel crane.

[0049] The intelligent dispatching and control scheme of multiple bucket wheel excavators mainly includes three parts: establishing a three-dimensional model of the stockpile, establishing the bucket wheel machine configuration space, and optimizing the dispatching path.

[0050] Solution for establishing a three-dimensional model of a stockpile:

[0051] like Figure 2As shown in the figure, the precise installation position and attitude angle data of the laser scanner on each bucket wheel machine are first determined on site, and then the Graham line, encoder and inclinometer of each bucket wheel machine are accurately calibrated to ensure data accuracy. The raw data of the laser scanner is transmitted to the background computing server through the network switch. The raw data is processed by the triangulation reconstruction algorithm and the multiple space transformation algorithm to generate the original point cloud data, and then the point cloud data multiple filtering technology and rasterization compression algorithm are used to obtain the lightweight stockpile point cloud model. Among them, the scanning data of multiple laser scanners are fused and processed by the rasterization update method, so that multiple scanners can update the point cloud data at the same time. The compressed point cloud data is stored in the model data storage server for backup and preservation. The three-dimensional model of the stockpile can be rendered and displayed in real time in the visualization software of the centralized control center, realizing real-time remote monitoring of the stockpile model.

[0052] Bucket wheel mechanism configuration space establishment plan:

[0053] like Figure 3 As shown in the figure, according to the degrees of freedom of the bucket wheel machine: walking position x, rotation angle θ, pitch angle γ, the configuration space (x, θ, γ) is constructed. Each state (position and posture) of the bucket wheel machine corresponds to a point in the configuration space. According to the mechanical limit value x of the bucket wheel machine, min ,x max ,θ min ,θ max ,γ min ,γ max A rectangular path search range in the configuration space is constructed. The configuration space is meshed according to the speed of each degree of freedom of the bucket wheel machine to ensure that the three-dimensional grids are consistent in time scale. After meshing, each grid has its own coordinate value (x i ,θ i ,γ i ) also has the attribute of whether it is blocked. If the bucket wheel machine collides with other bucket wheels, stockpiles, and track platforms at the position and posture represented by this coordinate value, the blocking attribute of the grid is true, otherwise it is false. Using the physical space model of the bucket wheel machine and the three-dimensional model of the stockpile, spatial overlap comparison is performed to calculate all the blocked grids. Using the spatial model and positional relationship between bucket wheels, the blocking grids between bucket wheels are calculated. The scheduling target point from the task center is converted to the target point in the configuration space (x goal ,θ goal ,γ goal ), and the starting point is the current position of the bucket wheel machine (x start ,θ start ,γ start), the scheduling calculation problem of bucket wheel excavator is transformed into finding a shorter connected path from the starting point to the target point in the configuration space that avoids the blocking grid.

[0054] Scheduling path optimization solution:

[0055] In the constructed configuration space, a heuristic search is used starting from the starting point. Each search evaluates the neighborhood grid points. The evaluation function includes a cost function and a heuristic function. The cost function optimizes the running time of the scheduling path, and the heuristic function reduces the search time and storage space cost, speeding up the calculation process. Each search uses the optimal grid in the evaluation grid, and then iterates the next search until a feasible path from the starting point to the target point is found. Finally, the path value is converted into a control signal of the bucket wheel machine and sent to the corresponding bucket wheel machine PLC controller to control the bucket wheel machine in real time, thereby completing the intelligent scheduling task of the bucket wheel machine.

[0056] By introducing configuration space, collision detection of bucket wheel machine physical models, and three-dimensional model data of material piles, the optimal path scheduling of multiple bucket wheel machines for intelligent obstacle avoidance is achieved, completing a key link in the fully automatic operation of bucket wheel machines, improving the overall operating efficiency of the material yard, and ensuring the safety and reliability of the operation of multiple equipment. At the same time, due to path optimization, energy use is reduced, low-carbon emission reduction is achieved, and good economic benefits and social value are created for the enterprise.

[0057] It should be pointed out that, according to the needs of implementation, the various steps / components described in this application can be split into more steps / components, and two or more steps / components or partial operations of steps / components can be combined into new steps / components to achieve the purpose of the present invention.

[0058] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A multi-bucket wheel machine intelligent dispatching control method, characterized in that: include: The position information of each bucket wheel machine in space and the pitch angle and rotation angle attitude information of the boom are obtained through the inclinometer, Graham line and encoder installed on the bucket wheel machine; The surface structure data of the pile is obtained through laser scanner equipment, and a three-dimensional model of the pile is established through a multiple spatial variable transposition algorithm. The blocking space is calculated to obtain the feasible range of non-interference between the bucket wheel excavator and the pile. A simplified collision detection volume block is established through the physical model of the bucket wheel machine, and the motion interference between bucket wheels is checked through the separation line theory to calculate the regional space of the collision situation; The three-degree-of-freedom configuration space of the bucket wheel machine is established, the material pile blocking space transformation is introduced into the configuration space, and the regional space transformation of the bucket wheel machine movement collision situation is introduced into the configuration space. Based on the position information of each bucket wheel machine in space and the pitch angle and rotation angle posture information of the cantilever, the autonomous path-finding algorithm is used in the configuration space to calculate the optimal obstacle avoidance path; The method of establishing a three-degree-of-freedom configuration space of a bucket wheel machine, introducing the material pile blocking space conversion into the configuration space, and introducing the regional space conversion of the bucket wheel machine movement collision situation into the configuration space includes: According to the bucket wheel machine's travel position x, rotation angle θ and pitch angle γ, the configuration space (x, θ, γ) is constructed. Each state of the bucket wheel machine corresponds to a point in the configuration space. According to the mechanical limit value x of the bucket wheel machine, min ,x max ,θ min ,θ max ,γ min ,γ max Construct a cuboid path search range in the configuration space, where x min ,x max They represent the minimum and maximum limit values ​​of the bucket wheel machine's travel position, θ min ,θ max They represent the minimum and maximum limit values ​​of the bucket wheel excavator's rotation angle, γ min ,γ max They respectively represent the minimum limit value and the maximum limit value of the bucket wheel machine's pitch angle; The configuration space is meshed according to the speed of each degree of freedom of the bucket wheel machine to ensure that the meshes in three dimensions are consistent in time scale; After the grid is divided, each grid has its coordinate value (x i ,θ i ,γ i ) also has the attribute of whether it is blocked. If the bucket wheel machine collides with other bucket wheels, material piles, and track platforms at the position and posture represented by this coordinate value, the blocking attribute of the grid is true, otherwise it is false. i ,θ i ,γ i ) represents the travel position x of the bucket wheel machine represented by the i-th grid i 、Rotation angle θ i and pitch angle γ i ; Using the physical space model of the bucket wheel machine and the three-dimensional model of the stockpile, spatial overlap comparison is performed to calculate all grids with obstructions. The blocking grid between bucket wheel machines is calculated by using the spatial model and positional relationship between bucket wheel machines.

2. The method according to claim 1, characterized in that The method of obtaining the surface structure data of the pile by means of a laser scanner device and establishing a three-dimensional model of the pile by means of a multiple spatial variable transposition algorithm includes: Determine the precise installation position and attitude angle data of the laser scanner on each bucket wheel machine on site, and then accurately calibrate the Graham line, encoder and inclinometer of each bucket wheel machine; The original data of the laser scanner is processed through a triangulation reconstruction algorithm and a multiple space transformation algorithm to generate original point cloud data. The lightweight point cloud model of the material pile is then obtained through point cloud data multiple filtering technology and a rasterization compression algorithm. The scanning data of multiple laser scanners are fused through a rasterization update method, so that multiple scanners can update the point cloud data simultaneously to obtain the final updated 3D model of the material pile.

3. The method according to claim 2, characterized in that The autonomous path-finding algorithm is used in the configuration space to calculate the optimal obstacle avoidance path, including: Convert the scheduling target point from the task center to the target point in the configuration space (x goal ,θ goal ,γ goal ), and the starting point is the current position of the bucket wheel machine (x start ,θ start ,γ start ), the scheduling calculation problem of bucket wheel excavator is transformed into finding a shorter connected path from the starting point to the target point in the configuration space that avoids the blocking grid, (x goal ,θ goal ,γ goal ) represents the target travel position x of the bucket wheel excavator goal 、Target rotation angle θ goal and the target pitch angle γ goal ,(x start ,θ start ,γ start ) represents the starting travel position x of the bucket wheel excavator start 、Starting rotation angle θ start and the starting pitch angle γ start ; In the constructed configuration space, from the starting point (x start ,θ start ,γ start ) starts to use heuristic search. Each search evaluates the neighborhood grid points. The evaluation function includes cost function and heuristic function. The cost function optimizes the running time of the scheduling path, and the heuristic function reduces the search time and storage space cost, speeding up the calculation process. Each search uses the optimal grid in the evaluation grid, and then iterates to the next search until the starting point (x start ,θ start ,γ start ) Search to the target point (x goal ,θ goal ,γ goal ) is a feasible path.

4. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: After rendering the three-dimensional model of the material pile, a visual display effect is obtained, thereby realizing real-time remote monitoring of the material pile model.

5. An intelligent dispatching and control system for a multi-bucket wheel excavator, characterized in that: include: Multiple bucket wheel machines, position and attitude sensors, laser scanners, airborne data acquisition processors, model data storage servers, background computing servers, bucket wheel machine controllers; The position and attitude sensors include Graham lines, encoders and inclinometers. The Graham lines are installed on the side of the bucket wheel machine's running track to accurately locate the bucket wheel machine's travel position. The encoder installed on the bucket wheel machine measures the cantilever's rotation position in real time to calculate the rotation angle. The inclinometer installed on the bucket wheel machine's cantilever obtains the cantilever's pitch angle in real time. The travel position, rotation angle and pitch angle are transmitted to the background computing server by the onboard data acquisition processor. The laser scanner is installed on the boom of the bucket wheel machine and moves with the boom. The data of the stockpile scan is transmitted to the background computing server for preprocessing to generate a 3D model of the stockpile. The 3D model is stored in the model data storage server after rasterization and denoising algorithm. The backend computing server calculates the blocking space based on the three-dimensional model, obtains the feasible range of non-interference between the bucket wheel machine and the stockpile, establishes a simplified collision detection volume block through the physical model of the bucket wheel machine, checks the motion interference between the bucket wheels through the separation line theory, calculates the regional space of the collision situation, establishes the three-degree-of-freedom configuration space of the bucket wheel machine, introduces the stockpile blocking space conversion into the configuration space, and introduces the regional space conversion of the bucket wheel machine motion collision situation into the configuration space. Based on the position information of each bucket wheel machine in space and the pitch angle and rotation angle posture information of the cantilever, the autonomous path-finding algorithm is used in the configuration space to generate the scheduling trajectory node, and transmit it to the bucket wheel machine controller; The bucket wheel machine controller processes the dispatching trajectory nodes to generate control signals to control the action of the bucket wheel machine; The backend computing server is used to construct a configuration space (x, θ, γ) according to the walking position x, rotation angle θ and pitch angle γ of the bucket wheel machine. Each state of the bucket wheel machine corresponds to a point in the configuration space. min ,x max ,θ min ,θ max ,γ min ,γ max Construct a cuboid path search range in the configuration space, where x min ,x max They represent the minimum and maximum limit values ​​of the bucket wheel machine's travel position, θ min ,θ max They represent the minimum and maximum limit values ​​of the bucket wheel excavator's rotation angle, γ min ,γ max They represent the minimum and maximum limit values ​​of the bucket wheel machine's pitch angle respectively; the configuration space is gridded according to the speed of each degree of freedom of the bucket wheel machine to ensure that the grids of the three dimensions are consistent on the time scale; after gridding, each grid has its coordinate value (x i ,θ i ,γ i ) also has the attribute of whether it is blocked. If the bucket wheel machine collides with other bucket wheels, material piles, and track platforms at the position and posture represented by this coordinate value, the blocking attribute of the grid is true, otherwise it is false. i ,θ i ,γ i ) represents the travel position x of the bucket wheel machine represented by the i-th grid i 、Rotation angle θ i and pitch angle γ i ; Using the physical space model of the bucket wheel machine and the three-dimensional model of the stockpile, spatial overlapping comparison is performed to calculate all the blocked grids; using the spatial model and position relationship between bucket wheel machines, the blocked grids between bucket wheel machines are calculated.

6. The system according to claim 5, characterized in that The background computing server is used to determine the precise installation position and attitude angle data of the laser scanner on each bucket wheel machine on site, and after accurately calibrating the Graham line, encoder and inclinometer of each bucket wheel machine, the original data of the laser scanner is subjected to a triangulation reconstruction algorithm and a multiple space transformation algorithm to generate original point cloud data, and then a lightweight stockpile point cloud model is obtained through point cloud data multiple filtering technology and a rasterization compression algorithm. The scanning data of multiple laser scanners are fused and processed through a rasterization update method, so that multiple scanners can update the point cloud data at the same time, and the final updated stockpile three-dimensional model is obtained.

7. The system according to claim 6, characterized in that The backend computing server is used to convert the scheduling target point from the task center into the target point (x goal ,θ goal ,γ goal ), and the starting point is the current position of the bucket wheel machine (x start ,θ start ,γ start ), the scheduling calculation problem of bucket wheel excavator is transformed into finding a shorter connected path from the starting point to the target point in the configuration space that avoids the blocking grid, (x goal ,θ goal ,γ goal ) represents the target travel position x of the bucket wheel excavator goal 、Target rotation angle θ goal and the target pitch angle γ goal ,(x start ,θ start ,γ start ) represents the starting travel position x of the bucket wheel excavator start 、Starting rotation angle θ start and the starting pitch angle γ start ; In the constructed configuration space, from the starting point (x start ,θ start ,γ start ) starts to use heuristic search. Each search evaluates the neighborhood grid points. The evaluation function includes cost function and heuristic function. The cost function optimizes the running time of the scheduling path, and the heuristic function reduces the search time and storage space cost, speeding up the calculation process. Each search uses the optimal grid in the evaluation grid, and then iterates to the next search until the starting point (x start ,θ start ,γ start ) Search to the target point (x goal ,θ goal ,γ goal ) is a feasible path.

8. The system according to any one of claims 5 to 7, characterized in that: The background computing server is used to render the three-dimensional model of the stockpile to obtain a visual display effect, thereby realizing real-time remote monitoring of the stockpile model.

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