Rail-mounted container gantry crane multi-machine anti-collision debugging system and method

Abstract

The application provides a rail-mounted container gantry crane multi-machine anti-collision debugging system and method, which comprises multiple physical gantry cranes, a virtual debugging system and a physical control system, the virtual debugging system comprises a collision detection unit, a virtual scene unit and a motion control unit; the virtual scene unit simulates a physical yard crane operation scene in real time; the collision detection unit performs collision detection according to the real-time operation state of a virtual rail-mounted container gantry crane model in the virtual scene module and the real-time position of a container model; after receiving the collision detection unit data and calculating the safety plan and information evaluation, the motion control unit performs corresponding safety motion control on the rail-mounted container gantry crane entity. The system constructed by the application virtually simulates and debugs the current motion task, verifies the safety, and through repeated adjustment and iterative optimization of the current task, the time for task design can be greatly shortened.

Description

Technical Field

[0001] This invention relates to the field of crane technology, specifically to a multi-machine anti-collision debugging system and method for rail-mounted container gantry cranes. Background Technology

[0002] Rail-mounted container gantry cranes are a common type of lifting and transport equipment in port terminals and railway central station yards, playing an indispensable role in container loading and unloading. When multiple rail-mounted container gantry cranes are operating in a coordinated manner, physical spatial interference can occur between containers within the container area and those being lifted, between trolleys on the rails and boundary objects, and between different trolleys. While safety technologies such as vision, ultrasonic, laser, and mechanical limit devices have been implemented, collision hazards still exist. Furthermore, testing rail-mounted container gantry cranes in multi-machine coordinated operation tasks also presents challenges due to high costs and significant risks.

[0003] When rail-mounted container gantry cranes perform multi-machine collaborative operations, the operating environment is relatively complex, with interference between the trolleys, containers, and other cranes within the operating area in terms of physical spatial positioning. Existing multi-machine collaborative crane operations may encounter the following problems: 1. When operations are carried out at night or in relatively turbulent conditions, and there are blind spots where the lifting equipment obstructs the field of vision, operators / managers may not be able to observe the surrounding obstacles in a timely and complete manner, resulting in collisions between the large vehicle and obstacles such as people, vehicles, and equipment in the site.

[0004] 2. Single collision avoidance technologies (such as ultrasonic collision avoidance technology, machine vision collision avoidance technology, laser collision avoidance technology, near-field sensing collision avoidance technology, infrared detection collision avoidance technology, etc.) may introduce certain collision risk issues.

[0005] 3. When testing multi-machine collaborative operation tasks, rail-mounted container gantry cranes also face problems such as high cost and high risk. Summary of the Invention

[0006] To address the above issues, this invention provides a multi-machine anti-collision debugging system and method for automated rail-mounted container gantry cranes in yards. Compared with traditional physical debugging and purely digital debugging, it reduces the cost of task testing and allows operators / administrators to intuitively understand the operation task process.

[0007] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A multi-machine anti-collision debugging system for rail-mounted container gantry cranes includes multiple physical gantry cranes, a virtual debugging system, and a physical control system, wherein the virtual debugging system includes a collision detection unit, a virtual scene unit, and a motion control unit; The virtual scene unit uses a digital method to establish a corresponding model on the virtual crane yard, thus obtaining a virtual rail-mounted container gantry crane. The virtual rail-mounted container gantry crane is then copied 1:1 into the virtual scene. It also receives motion status information from the physical gantry crane, simulates the actual operation of the yard crane in real time, and monitors the rail-mounted crane in real time during yard operations. The collision detection unit performs collision detection based on the real-time operating status of the virtual track-type container gantry crane model and the real-time position of the container model in the virtual scene unit. After receiving data from the collision detection unit, the motion control unit calculates the safety plan and information assessment, determines whether to decelerate or stop the operation, and transmits the instruction data for operating the crane to the physical motion control system, thereby performing corresponding safety motion control on the rail-mounted container gantry crane.

[0008] Furthermore, the trolley and the main trolley of the physical gantry crane are respectively equipped with mechanical physical anti-collision limit switches and laser or vision sensors; the virtual rail-type container gantry crane is equipped with sensors, including: virtual laser sensors, virtual acceleration sensors, and virtual attitude sensors, which are used to detect distance, acceleration, and target attitude, respectively, and display these data through the UI under the virtual scene unit.

[0009] Furthermore, the collision detection unit is used to perform collision detection on multiple rail-mounted container gantry cranes on the same track in the virtual scene unit, including trolley collision detection, gantry collision detection, and spreader collision detection. It provides anti-collision warning information for multi-machine collaborative operation of the rail-mounted container gantry cranes in the yard. When a collision signal is detected, the virtual scene unit displays the operating status of multiple important position views in the virtual scene through the UI interface, so that operators / administrators can monitor the operation of multiple rail-mounted container gantry cranes in the yard in real time, determine whether to decelerate or stop the operation, and ensure the safe control of multi-machine collaborative operation.

[0010] Furthermore, the data transmission connection between the virtual scene unit and the motion control unit sends data to the virtual scene unit via the OPC UA unified architecture industrial communication protocol. The virtual scene unit is equipped with an OPC UA data transmission interface. The virtual scene unit is equipped with the crane position and updates the position by reading and continuously iterating the data in the nodes.

[0011] Furthermore, the motion control unit is equipped with an interface for transmitting key data, which transmits the response data to the physical control system through a communication protocol, thereby performing corresponding motion control on the rail-mounted container gantry crane, including path planning, acceleration, speed and position control.

[0012] Furthermore, the safety planning and information assessment includes predicting and calculating the collision probability of whether collisions will occur or are about to occur between crane trolleys, between trolleys on the track and boundary objects, between containers in the crane compartment and containers being lifted, and between containers and spreaders in an unloaded state, if they cross the safe distance.

[0013] The present invention also provides a method for anti-collision debugging of multiple rail-mounted container gantry cranes, comprising the following steps: Step S1. The virtual scene unit establishes a data transmission connection with the motion control unit. The virtual scene unit receives the motion status information of the crane, simulates the actual operation scene of the yard crane in real time, and monitors the actual rail crane equipment in real time during yard operations. Step S2. The collision detection unit performs collision detection based on the real-time operating status of the virtual track-type container gantry crane model and the real-time position of the container model in the virtual scene unit. Step S3. The collision detection unit, together with mechanical physical collision avoidance and laser vision collision avoidance, forms a multi-layered collision avoidance control. The collision detection results are used to test and verify whether the task design and motion are safe. Step S4. After receiving the collision detection data, the motion control unit calculates the safety plan and information assessment, determines whether to decelerate or stop the operation, and transmits the command data for operating the crane to the crane physical control system, thereby performing corresponding safety motion control on the rail-mounted gantry crane.

[0014] Furthermore, the collision detection in step S2 includes trolley collision detection, trolley collision detection, and spreader collision detection. The trolley collision detection is used to detect the distance between virtual rail-mounted container gantry cranes and the distance between the crane and the boundary position of the rail. The trolley collision detection is used to detect the distance between the trolley running mechanism of the virtual rail-mounted container gantry crane and the boundary position. When the calculated distance from the boundary position is less than the safe distance, response data is issued and the corresponding data is transmitted to the UI interface for display. The spreader collision detection is used for collision detection between the spreader and the container in both unloaded and loaded states.

[0015] Furthermore, the collision detection process for large or small vehicles is as follows: (1) At any given moment, within the established spatial coordinate system, determine the spatial position of the reference object. A virtual laser sensor on either the trolley or the crane emits a ray to a reference object. The ray length is calculated when it contacts the reference object, thus determining the spatial position of the virtual laser sensors on n virtual rail-mounted container gantry cranes. , , ... ; (2) The ray will be emitted again after a certain time to confirm. Spatial position of n virtual laser sensors at time points , , ... ; (3) Every subsequent time Time-emission ray determination The spatial positions of n virtual laser sensors at any given time are used to determine the relative distances between the trolleys or cranes of n rail-mounted container gantry cranes. ; (4) Based on the safety distance set by the control system If judge Then the cranes are still at a safe distance. If the cranes are not at a safe distance, the system will alert the operator / administrator in the UI of the virtual scene unit that there is a safety risk to the equipment.

[0016] Furthermore, for collision detection between the spreader and the container under both unloaded and loaded conditions, it is necessary to calculate a cuboid containing the target model and simultaneously performing translations and rotations relative to the coordinate axes, which can be represented in three-dimensional space by the following formula:

[0017] in, Represents the region of the cuboid in the spatial coordinate system. Indicates the midpoint. , , Indicates the length of half a side. , , Represents mutually perpendicular unit vectors. a , b , c These are the vector coefficients; The collision detection process between the spreader and the container is as follows: (1) First, obtain the coordinates of each vertex on the surface of the lifting device, whether it is unloaded or loaded. ; (2) Calculate the vertex mean to determine the coordinates of the center point of the cuboid. A third-order matrix based on real symmetry at the center point is obtained by calculating the covariance matrix of the vertices. The formula for calculating covariance is:

[0018]

[0019] in, , These are the two values ​​of the covariance formula, which are the three-dimensional position coordinates of each vertex. , The mean of the coordinates of all vertices. A third-order matrix consisting of the values ​​of the covariance of the center points; (3) Calculate the inner product of the eigenvectors using a real symmetric third-order matrix, and remove the three eigenvectors whose inner product is zero. , , Used to determine the orientation of a cuboid; (4) Traverse all vertices on the target model The lengths of each side of the cuboid can be obtained by projecting it in three directions, thereby determining the spatial position of the cuboid; (5) Based on the separation surface, detect whether the cuboids intersect. The line where the normal vector of the separation surface is located is the separation axis. Calculate the projection of the edge of each cuboid on the separation axis and detect whether the projections of the edge of different cuboids intersect. If the projections on any axis coincide, the cuboids are considered to be colliding.

[0020] Compared with the prior art, this application has the following beneficial effects: This invention discloses a multi-machine anti-collision debugging system and method for rail-mounted container gantry cranes. Utilizing digital twin technology, the system integrates the rail-mounted container gantry crane and related operational scenarios in a yard. This system and method enable real-time monitoring of the physical cranes during yard operations, allowing for understanding the operational status of each piece of equipment. Beyond the traditional safety functions provided by laser, vision, and radar, it further offers predictive and safety assurance. After loading a virtual scenario into the debugging system, those skilled in the art can manipulate the virtual yard rail-mounted container gantry crane to perform motion simulations by adjusting configuration parameters or writing motion programs, verifying the reachability and collision prevention of the task parameters and motion programs. Compared to traditional physical debugging and purely digital debugging, the system built using this method performs virtual simulation and debugging of the current motion task, verifying its safety (whether there is a risk of collision). Through repeated adjustments and iterative optimization, the task design time can be significantly shortened. Attached Figure Description

[0021] Figure 1A schematic diagram of a multi-machine anti-collision debugging system for a rail-mounted container gantry crane provided by the present invention; Figure 2 A schematic diagram of the multi-layer anti-collision control process in a multi-machine anti-collision debugging system and method for a rail-mounted container gantry crane provided by the present invention; Figure 3 A schematic diagram of the crane operation in a multi-layer anti-collision control system and method for a rail-mounted container gantry crane provided by the present invention; Figure 4 A schematic diagram of the anti-collision debugging process in a multi-machine anti-collision debugging system and method for a rail-mounted container gantry crane provided by the present invention; Figure 5 This is a schematic diagram of a cuboid containing the target model of the present invention; Figure 6 This is a schematic diagram of the process for collision detection of cuboid spreaders (loaded / unloaded) in a multi-machine anti-collision debugging system and method for a rail-mounted container gantry crane provided by the present invention. Detailed Implementation

[0022] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0023] This embodiment provides a multi-machine anti-collision debugging system for rail-mounted container gantry cranes, including multiple physical gantry cranes, a virtual debugging system, and a physical control system. The virtual debugging system includes a collision detection unit, a virtual scene unit, and a motion control unit. The virtual scene unit uses a digital method to establish a corresponding model on the virtual crane yard, thus obtaining a virtual rail-mounted container gantry crane. The virtual rail-mounted container gantry crane is then copied 1:1 into the virtual scene. It also receives motion status information from the physical gantry crane, simulates the actual operation of the yard crane in real time, and monitors the rail-mounted crane in real time during yard operations. The collision detection unit performs collision detection based on the real-time operating status of the virtual track-type container gantry crane model and the real-time position of the container model in the virtual scene unit. After receiving data from the collision detection unit, the motion control unit calculates the safety plan and information assessment, determines whether to decelerate or stop the operation, and transmits the instruction data for operating the crane to the physical motion control system, thereby performing corresponding safety motion control on the rail-mounted container gantry crane.

[0024] The physical gantry crane is equipped with mechanical physical anti-collision limit switches and laser or vision sensors on its trolley and gantry respectively; the virtual rail-type container gantry crane is equipped with sensors, including: virtual laser sensors, virtual acceleration sensors, and virtual attitude sensors, which are used to detect distance, acceleration, and target attitude respectively, and display these data through the UI under the virtual scene unit.

[0025] The collision detection unit is used to perform collision detection on multiple rail-mounted container gantry cranes on the same track in the virtual scene unit, including trolley collision detection, gantry collision detection, and spreader collision detection. It provides collision avoidance warning information for multi-machine collaborative operation of rail-mounted container gantry cranes in the yard. When a collision signal is detected, the virtual scene unit displays the operation status of multiple important position views in the virtual scene through the UI interface, allowing operators / administrators to monitor the operation of multiple rail-mounted container gantry cranes in the yard in real time, determine whether to slow down or stop the operation, and ensure the safe control of multi-machine collaborative operation.

[0026] The data transmission connection between the virtual scene unit and the motion control unit sends data to the virtual scene unit through the OPC UA unified architecture industrial communication protocol. The virtual scene unit is equipped with an OPC UA data transmission interface. The virtual scene unit is equipped with the crane position and updates the position by reading and continuously iterating the data in the node.

[0027] The motion control unit is equipped with an interface for transmitting key data. It transmits response data to the physical control system via a communication protocol, thereby enabling corresponding motion control of the rail-mounted container gantry crane, including path planning, acceleration, speed, and position control.

[0028] Safety planning and information assessment includes predicting and calculating the probability of collisions between crane trolleys, between trolleys on rails and boundary objects, between containers in the crane compartment and containers being lifted, and between containers and spreaders in an unloaded state, to determine whether they will cross the safe distance and collide or whether a collision is imminent.

[0029] This embodiment also provides a method for multi-machine anti-collision debugging of a rail-mounted container gantry crane, including the following steps: Step S1. The virtual scene unit establishes a data transmission connection with the motion control unit. The virtual scene unit receives the motion status information of the crane, simulates the actual operation scene of the yard crane in real time, and monitors the actual rail crane equipment in real time during yard operations. Step S2. The collision detection unit performs collision detection based on the real-time operating status of the virtual track-type container gantry crane model and the real-time position of the container model in the virtual scene unit. Step S3. The collision detection unit, together with mechanical physical collision avoidance and laser vision collision avoidance, forms a multi-layered collision avoidance control. The collision detection results are used to test and verify whether the task design and motion are safe. Step S4. After receiving the collision detection data, the motion control unit calculates the safety plan and information assessment, determines whether to decelerate or stop the operation, and transmits the command data for operating the crane to the crane physical control system, thereby performing corresponding safety motion control on the rail-mounted gantry crane.

[0030] The collision detection in step S2 includes trolley collision detection, trolley collision detection, and spreader collision detection. The trolley collision detection is used to detect the distance between virtual rail-mounted container gantry cranes and the distance between the crane and the boundary position of the rail. The trolley collision detection is used to detect the distance between the trolley running mechanism of the virtual rail-mounted container gantry crane and the boundary position. When the calculated distance from the boundary position is less than the safe distance, response data is issued and the corresponding data is transmitted to the UI interface for display. The spreader collision detection is used for collision detection between the spreader and the container in both unloaded and loaded states.

[0031] Figure 1 This is a schematic diagram of the multi-machine anti-collision debugging system for automated rail-mounted container gantry cranes in a yard according to the present invention. The physical gantry crane, the virtual debugging system, and the physical control system together constitute the anti-collision debugging system of this embodiment. The virtual debugging system includes a collision detection unit, a virtual scene unit, and a motion control unit. Figure 2 This is a schematic diagram of the multi-layer anti-collision system for cranes according to the present invention.

[0032] Specifically, when the virtual debugging system establishes a data transmission connection with the physical control system of the rail-mounted container gantry crane, the system acts as an anti-collision debugging system to understand the operating status of each piece of equipment. The anti-collision system is divided into three layers: the virtual debugging system transmits the command data for operating the crane to the physical motion control system for anti-collision; mechanical and physical anti-collision limit switches are installed on the trolley and carriage of the physical gantry crane for mechanical and physical anti-collision; and laser or vision sensors are used for anti-collision. In addition to the safety functions provided by traditional laser, vision, radar and mechanical anti-collision, it further provides prediction and safety assurance.

[0033] The aforementioned multi-layered collision protection specifically includes the following steps: 1. Establish a virtual debugging system. The virtual debugging system serves as a data transmission connection with the control system of the rail-mounted container gantry crane. The virtual scene unit receives the crane's motion status information, including: motor status data (speed, position) for the movement of various crane mechanisms, and calculates and converts it into the speed and position data of the crane in the yard (speed and position of the trolley, hoisting, etc.), data from various sensors on the crane (laser, radar, vision, attitude, etc.), and simulates the actual operation scenario of the crane in the yard in real time, enabling real-time monitoring of the rail-mounted gantry crane during yard operations. Specifically, in the virtual scene unit, software such as 3D MAX is used to digitally create corresponding models of virtual cranes and other storage yards (cranes and the equipment, rails, and containers on them), and the virtual models are copied 1:1 into the virtual scene.

[0034] Furthermore, the steps for establishing virtual scene units are as follows: 1.1. Create the virtual scene unit using Unity 3D to display the model and scene that needs to be displayed.

[0035] 1.2. Determine the position data (x, y, z) of the model in three directions by creating a three-dimensional map.

[0036] 1.3. Classify the models in the virtual scene by level to facilitate classification and control of the models through code.

[0037] Specifically, the data transmission connection between the virtual scene unit and the crane control system sends the data to the virtual scene unit via the OPC UA (OPC Unified Architecture) industrial communication protocol. The virtual scene unit is equipped with an OPC UA data transmission interface. The OPC UA communication protocol includes objects, nodes, and the types and names of custom data. The virtual scene unit is equipped with the crane position, and the position is updated by reading and continuously iterating the data in the nodes.

[0038] 2. The collision detection unit performs collision detection based on the real-time operating status of the virtual track-type container gantry crane model and the real-time position of the container model in the virtual scene unit; Specifically, the collision detection unit is used to perform collision detection on multiple rail-mounted container gantry cranes on the same track in the virtual unit, including trolley collision detection, hoist collision detection, and spreader collision detection. It provides collision avoidance warning information for multi-crane collaborative operation of the container gantry cranes in the yard using corresponding collision detection methods. When a collision signal is detected, the virtual scene unit displays the operating status from multiple important positional perspectives in the virtual scene through a UI interface, allowing operators / administrators to monitor the operation of multiple rail-mounted container gantry cranes in the yard in real time, determine whether to slow down or stop operation, and ensure safe control of multi-crane collaborative operation. The large trolley collision detection is used to detect the distance between virtual rail-mounted container gantry cranes and the distance between the crane and the boundary of the rail. The small trolley collision detection is used to detect the distance between the trolley running mechanism of the virtual rail-mounted container gantry crane and the boundary. When the calculated distance from the boundary is less than the safe distance, response data is issued and the corresponding data is transmitted to the UI interface for display.

[0039] Specifically, the large vehicle collision detection process is as follows: 1. At any given moment, within the established spatial coordinate system, determine the spatial position of the reference object. The virtual laser sensors emit rays to a reference object, and the length of the ray is calculated when the ray touches the reference object, thus determining the spatial position of the three virtual laser sensors. , , .

[0040] 2. The ray will be emitted again after a certain time to confirm. Spatial position of the three virtual laser sensors at any given time , , .

[0041] 3. Every subsequent time Time-emission ray determination The spatial positions of three virtual laser sensors at any given time are used to determine the relative distance between the three rail-mounted container gantry cranes. .

[0042] 4. Based on the safety distance set by the control system. If judge Then the cranes are still at a safe distance. If the cranes are not at a safe distance, the system will alert the operator / administrator in the UI of the virtual scene unit that there is a safety risk to the equipment.

[0043] The collision detection process for the small vehicle is similar to that for the large vehicle. It only requires determining the spatial position of the virtual laser sensor on a single track gantry and judging whether there is a risk of collision based on the safe distance.

[0044] The collision detection also includes collision detection between the spreader and the container in both unloaded and loaded states. Figure 6 The flowchart illustrating the cuboid collision detection of the spreader (loaded / unloaded) in the multi-machine anti-collision debugging system and method for a rail-mounted container gantry crane provided by this invention is shown. It detects collisions between the spreader and the container in both unloaded and loaded states. It requires calculating a cuboid containing the target model and simultaneously performing translations and rotations relative to the coordinate axes, which is represented in three-dimensional space by the following formula:

[0045] in, Represents the region of the cuboid in the spatial coordinate system. Indicates the midpoint. , , Indicates the length of half a side. , , Represents mutually perpendicular unit vectors. a , b , c These are the vector coefficients; such as Figure 5 As shown Furthermore, such as Figure 6 As shown, the collision detection process is as follows: 1. First, obtain the coordinates of each vertex on the surface of the lifting device (unloaded and loaded). .

[0046] 2. Calculate the vertex mean to determine the coordinates of the center point of the cuboid. A third-order matrix based on real symmetry at the center point is obtained by calculating the covariance matrix of the vertices.

[0047] The formula for calculating covariance is:

[0048]

[0049] in, , These are the two values ​​of the covariance formula, which are the three-dimensional position coordinates of each vertex. , The mean of the coordinates of all vertices. It is a third-order matrix composed of the values ​​of the covariance of the center points.

[0050] 3. Calculate the inner product of the eigenvectors using a real symmetric third-order matrix, and remove the three eigenvectors whose inner product is zero. , , Used to determine the orientation of a cuboid.

[0051] 4. Traverse all vertices on the target model. The lengths of each side of the cuboid can be obtained by projecting it in three directions, thereby determining the spatial position of the cuboid.

[0052] 5. Based on the separation surface, the intersection of cuboids is detected. The line containing the normal vector of the separation surface is the separation axis. The projection of the edge of each cuboid onto the separation axis is calculated, and the intersection of the projections of the edges of different cuboids is detected. If the projections coincide on any axis, a collision between the cuboids is considered. The spreader collision detection is used to detect the distance between the spreader (loaded / unloaded) of the virtual rail-mounted container gantry crane and the container model in the yard in the lifting and swinging directions. According to the open / closed state in the motion control unit, the collision detection range of the spreader is switched. When the calculated distance to the container is less than the safe distance, response data is issued, and the corresponding data is also transmitted to the UI interface for display.

[0053] 3. After the motion control unit receives the collision detection data and calculates the safety plan and information assessment, it determines whether to decelerate or stop the operation. The command data for operating the crane (speed, position, etc. of each mechanism motor) is transmitted to the crane's physical control system via the OPC UA communication protocol. This enables corresponding safe motion control of the rail-mounted container gantry crane, achieving collision avoidance between crane trolleys, between rail trolleys and boundary objects, between containers within the trolley area and containers being lifted, and between containers and unloaded spreaders. The collision detection results are used for safety planning and information assessment, providing safety warnings and decision-making resources for personnel in the rail-mounted container crane field. When a collision detection response signal is received, unsafe work areas and targets where collisions are about to occur are displayed in the virtual scene unit.

[0054] Specifically, the information assessment in step 3 includes predicting and calculating the collision probability of whether collisions will occur or occur between crane trolleys, between trolleys on the track and boundary objects, between containers in the crane compartment and containers being lifted, and between containers and spreaders in an unloaded state.

[0055] The safety motion control in step 3 includes whether the large and small vehicles decelerate or stop, path planning, and control of acceleration, speed, and position. Path planning can employ common path planning algorithms, such as A*. Algorithms such as Dijkstra's algorithm, genetic algorithm, and ant colony algorithm plan paths to enable spreaders, spreaders, and containers to bypass obstacles (containers in the yard), achieving collision avoidance between containers in the large container area and containers that are being lifted.

[0056] Furthermore, the motion control unit is equipped with an interface for transmitting key data, transmitting response data to the control system. Specifically, data transmission is conducted between the host computer and industrial control computer, and other physical control systems, via a communication protocol, thereby enabling corresponding motion control of the rail-mounted container gantry crane, including path planning and control of acceleration, speed, and position. Path planning can employ common path planning algorithms, such as A... Algorithms such as Dijkstra's algorithm, genetic algorithm, and ant colony algorithm plan paths to allow the spreader, spreader, and container to bypass obstacles (containers within the yard), achieving collision avoidance between containers in the large container area and containers being lifted. This embodiment uses algorithm A. The algorithm uses a container bay location map to divide the grid. After the algorithm generates a path, it transmits the motion parameters of the trolley and crane of the rail-mounted container gantry crane required for the path to the control system to achieve collision avoidance between containers in the trolley area and containers that are being lifted.

[0057] The anti-collision debugging system and the control system of the rail-mounted container gantry crane are connected for data transmission via a communication protocol. The communication adopts a Client / Server (C / S) architecture. The control systems of multiple rail-mounted container gantry cranes in the yard adopt a client structure, while the virtual debugging system adopts a server structure.

[0058] Furthermore, the collision prediction of the lifting device calculates the object's trajectory using information such as object model information, velocity, and forces. This trajectory perfectly matches the actual rigid body trajectory, and the calculated trajectory is displayed in the virtual scene unit UI. Figure 3 In the present invention, 6 is a multi-machine anti-collision debugging system and method for a rail-mounted container gantry crane, used to predict the swaying path of the spreader (loaded / unloaded) during operation.

[0059] 4. The anti-collision adjustment system, together with mechanical physical anti-collision and laser vision anti-collision, forms a multi-layered anti-collision control system. Figure 3 This is a schematic diagram of the crane operation for multi-layer anti-collision control in this invention. 1, 2, and 3 are mechanical and physical anti-collision limit switches on the trolley and the crane respectively, and 4 and 5 are laser or vision sensors installed on the trolley and the crane respectively. After the anti-collision debugging system is established through steps S1, S2, and S3, it also has anti-collision function through interconnection with the controller. Figure 4This is a schematic diagram of the anti-collision debugging process in a multi-machine anti-collision debugging system and method for a rail-mounted container gantry crane provided by the present invention.

[0060] If the virtual debugging system disconnects from the data transmission connection of the control system, the system can function as a virtual debugging system for operators / administrators to debug, test, and verify the safety of task design and motion control. Specifically, this includes the following steps: I. The system serves as a virtual debugging system, debugging the automated control logic and adjusting relevant parameters of three rail-mounted container gantry cranes in a virtual environment, and realizing multi-crane collaborative operation tasks through virtual simulation.

[0061] Specifically, as in step I, a digital replica of the physical manufacturing environment is created. The virtual rail-mounted container gantry crane model, the virtual sensor model, and the container model in the yard are copied 1:1 into the virtual scene unit. Corresponding model speed, acceleration interfaces, and task (position) interfaces are set on the UI to control the movement of the corresponding models. For example, (1, 1, 1) / (2, 3, 4) means the spreader picks up the containers in the first column, first row, and first layer and places them in the second column, third row, and fourth layer of the yard.

[0062] Furthermore, the container model of the yard is generated by acquiring the position information of containers in each bay of the yard, and the position information is the position coordinates of the center of each container.

[0063] II. The collision detection unit performs collision detection based on the operating status of the three cranes in the virtual scene unit and the position of the container model.

[0064] Furthermore, in step II, the virtual scene unit does not acquire the operating status of the three cranes through sensor data. Instead, it uses a virtual rail-mounted container gantry crane model with dynamic attributes, a virtual sensor model, and a container model from the yard. By writing integral equations for speed, acceleration, and distance, the virtual rail crane can move according to the speed and acceleration of the physical crane, thus simulating the motion state and scenario of the rail-mounted container gantry crane. The virtual rail-mounted container gantry crane is equipped with sensors, including a virtual laser sensor, a virtual accelerometer, and a virtual attitude sensor, which are used to detect distance, acceleration, and target attitude, respectively. This data is displayed through the UI of the virtual scene unit.

[0065] The motion control unit establishes a dynamic model of the crane's swing motion. By solving the swing motion equations in real time, the virtual rail-mounted container gantry crane simulates the real crane's operating state. In this embodiment, based on the Lagrange equation theory, the dynamic equations are expressed as follows:

[0066] in: L It is a Lagrange function. F i As a generalized force in generalized coordinates, the angle of swing in the direction of the trolley's motion or the direction of the trolley's motion is obtained by solving equations in real time, and the angle data of the swing is transmitted to the model in the virtual scene unit, so that the angle of the sling relative to the suspension point in the virtual scene is continuously iterated.

[0067] III. The results of collision detection are used to test and verify whether the task design and motion are safe. If no collision is displayed in the UI of the virtual scene unit, the task is feasible in the virtual debugging system. The task can be assigned and transmitted to the control system for execution, reducing the safety risks of actual operation.

[0068] The specific embodiments described herein are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to substitute them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

Claims

1. A multi-machine anti-collision debugging system for a rail-mounted container gantry crane, characterized in that, It includes multiple physical gantry cranes, a virtual commissioning system, and a physical control system, wherein the virtual commissioning system includes a collision detection unit, a virtual scene unit, and a motion control unit; The virtual scene unit uses a digital method to create a corresponding model of the virtual crane yard, thus obtaining a virtual rail-mounted container gantry crane. This virtual rail-mounted container gantry crane is then replicated 1:1 into the virtual scene. It receives motion status information from the physical gantry crane, simulating the real-time operation of the crane in the yard, and monitors the physical rail-mounted crane in real-time during yard operations. The physical gantry crane's trolley and crane are equipped with mechanical physical anti-collision limit switches and laser or vision sensors, respectively. The virtual rail-mounted container gantry crane is equipped with sensors, including a virtual laser sensor, a virtual acceleration sensor, and a virtual attitude sensor, used to detect distance, acceleration, and target attitude, respectively, and these data are displayed through the UI of the virtual scene unit. The data transmission connection between the virtual scene unit and the motion control unit sends data to the virtual scene unit through the OPC UA unified architecture industrial communication protocol. The virtual scene unit is equipped with an OPC UA data transmission interface. The virtual scene unit is equipped with the crane position and updates the position by reading and continuously iterating the data in the nodes. The collision detection unit performs collision detection based on the real-time operating status of the virtual rail-mounted container gantry crane model and the real-time position of the container model in the virtual scene unit; the collision detection includes: (1) At any given moment, within the established spatial coordinate system, determine the spatial position of the reference object. A virtual laser sensor on either the trolley or the crane emits a ray to a reference object. The ray length is calculated when it contacts the reference object, thus determining the spatial position of the virtual laser sensors on n virtual rail-mounted container gantry cranes. , , ... ; (2) The ray will be emitted again after a certain time to confirm. Spatial position of n virtual laser sensors at time points , , ... ; (3) Every subsequent time Time-emission ray determination The spatial positions of n virtual laser sensors at any given time are used to determine the relative distances between the trolleys or cranes of n rail-mounted container gantry cranes. ; (4) Based on the safety distance set by the control system If judge Then the cranes are still at a safe distance. If the cranes are not at a safe distance, the system will alert the operator / administrator in the UI of the virtual scene unit that there is a safety risk to the equipment. After receiving data from the collision detection unit, the motion control unit calculates the safety plan and information assessment, determines whether to decelerate or stop the operation, and transmits the instruction data for operating the crane to the physical motion control system, thereby performing corresponding safety motion control on the rail-mounted container gantry crane.

2. The multi-machine anti-collision debugging system for a rail-mounted container gantry crane according to claim 1, characterized in that, The collision detection unit is used to perform collision detection on multiple rail-mounted container gantry cranes on the same track in the virtual scene unit, including trolley collision detection, gantry collision detection, and spreader collision detection. It provides anti-collision warning information for multi-machine collaborative operation of the rail-mounted container gantry cranes in the yard. When a collision signal is detected, the virtual scene unit displays the operation status of multiple important position views in the virtual scene through the UI interface, allowing operators / administrators to monitor the operation of multiple rail-mounted container gantry cranes in the yard in real time, determine whether to slow down or stop the operation, and ensure the safe control of multi-machine collaborative operation.

3. The multi-machine anti-collision debugging system for a rail-mounted container gantry crane according to claim 1, characterized in that, The motion control unit is equipped with an interface for transmitting key data. It transmits response data to the physical control system via a communication protocol, thereby performing corresponding motion control on the rail-mounted container gantry crane, including path planning, acceleration, speed, and position control.

4. The multi-machine anti-collision debugging system for a rail-mounted container gantry crane according to claim 1, characterized in that, The safety planning and information assessment includes predicting and calculating the collision probability of whether collisions will occur or are about to occur between crane trolleys, between trolleys on the track and boundary objects, between containers in the crane compartment and containers being lifted, and between containers and spreaders in an unloaded state, if they cross the safe distance.

5. A method for multi-machine anti-collision debugging of a rail-mounted container gantry crane, characterized in that, Includes the following steps: Step S1. The virtual scene unit establishes a data transmission connection with the motion control unit. The virtual scene unit receives the motion status information of the crane, simulates the actual operation scene of the yard crane in real time, and monitors the actual rail crane equipment in real time during yard operations. Step S2. The collision detection unit performs collision detection based on the real-time operating status of the virtual rail-mounted container gantry crane model and the real-time position of the container model in the virtual scene unit; the collision detection includes trolley collision detection, gantry collision detection, and spreader collision detection; The collision detection process for large or small vehicles is as follows: (1) At any given moment, within the established spatial coordinate system, determine the spatial position of the reference object. A virtual laser sensor on either the trolley or the crane emits a ray to a reference object. The ray length is calculated when it contacts the reference object, thus determining the spatial position of the virtual laser sensors on n virtual rail-mounted container gantry cranes. , , ... ; (2) The ray will be emitted again after a certain time to confirm. Spatial position of n virtual laser sensors at time points , , ... ; (3) Every subsequent time Time-emission ray determination The spatial positions of n virtual laser sensors at any given time are used to determine the relative distances between the trolleys or cranes of n rail-mounted container gantry cranes. ; (4) Based on the safety distance set by the control system If judge Then the cranes are still at a safe distance. If the cranes are not at a safe distance, the system will alert the operator / administrator in the UI of the virtual scene unit that there is a safety risk to the equipment. Step S3. The collision detection unit, together with mechanical physical collision avoidance and laser vision collision avoidance, forms a multi-layered collision avoidance control. The collision detection results are used to test and verify whether the task design and motion are safe. Step S4. After receiving the collision detection data, the motion control unit calculates the safety plan and information assessment, determines whether to decelerate or stop the operation, and transmits the command data for operating the crane to the crane entity control system, thereby performing corresponding safety motion control on the rail-mounted container gantry crane entity.

6. The multi-machine anti-collision debugging method for a rail-mounted container gantry crane according to claim 5, characterized in that, The trolley collision detection is used to detect the distance between virtual rail-mounted container gantry cranes and the distance between the crane and the boundary of the rail. The trolley collision detection is used to detect the distance between the trolley running mechanism of the virtual rail-mounted container gantry crane and the boundary. When the calculated distance from the boundary is less than the safe distance, response data is issued and the corresponding data is transmitted to the UI interface for display. The spreader collision detection is used to detect collisions between the spreader and the container in both unloaded and loaded states.

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