Multi-agent based continuous casting breakout simulation method and device

Abstract

This application provides a continuous casting billet exit simulation method and apparatus based on multi-agent systems. The method includes: acquiring continuous casting billet exit process information; establishing a continuous casting billet exit simulation model based on the continuous casting billet exit process information and a preset model library. The continuous casting billet exit simulation model includes: a billet module, a billet exit track module, a transverse movement zone module, a cooling bed module, a hot conveying module, and their respective corresponding simulation logic rules. The preset model library includes: intelligent agents for the cutting and conveying track, intelligent agents for the lifting baffle, intelligent agents for the transverse movement zone roller conveyor, intelligent agents for the marking machine, intelligent agents for the lifting machine, intelligent agents for the pushing machine, intelligent agents for the cooling bed, and intelligent agents for the collecting bed; and completing the continuous casting billet exit simulation based on the continuous casting billet exit simulation model. This application can model the continuous casting billet exit process, improving the efficiency of continuous casting billet exit simulation while ensuring its reliability.

Description

Technical Field

[0001] This application relates to the field of continuous casting billet simulation technology, and in particular to a continuous casting billet simulation method and apparatus based on multi-agent systems. Background Technology

[0002] With the rapid development of the steel industry, continuous casting technology has become a core process in modern steel production. As a crucial link connecting the continuous casting machine with subsequent rolling processes, the efficiency and stability of the continuous casting billet discharge system directly affect the capacity and quality of the entire production line. The increasingly faster billet discharge pace of modern multi-strand high-speed continuous casting machines places higher demands on the logistics scheduling, equipment coordination, and spatial configuration of the billet discharge system.

[0003] Currently, continuous casting billet exit design is based on static estimation, which cannot predict problems during the dynamic operation of billet exit and subsequent matching. Furthermore, existing simulation research processes only cover the beginning of continuous casting, excluding the billet exit stage. Traditional simulation modeling methods rely on manual model construction, requiring repeated processing of data relationships and model details, resulting in low efficiency. When requirements change, the model structure must be manually adjusted, making it difficult to quickly respond to business changes. Different modelers may use different logics, lacking unified data standards, making model components difficult to reuse, leading to redundant development and requiring lengthy training for new members. The disadvantages of traditional modeling are particularly pronounced in large, complex projects, cross-domain collaborations, and rapid iteration requirements.

[0004] For example, patent CN115098922B discloses a method for rapidly constructing a steelmaking-continuous casting logistics simulation model based on modular design. Using modular design and Plant Simulation software, the steelmaking-continuous casting process, including converter steelmaking, ladle transportation, refining, continuous casting, and ladle maintenance, is broken down into reusable process, logistics line, and scheduling rule modules to build the simulation model. However, its research scope only covers the process up to continuous casting, without simulating the billet unloading stage.

[0005] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section. Summary of the Invention

[0006] To address at least one problem in the prior art, this application proposes a multi-agent-based continuous casting billet production simulation method and apparatus, which can model the continuous casting billet production process and improve the efficiency of continuous casting billet production simulation while ensuring its reliability.

[0007] To address the aforementioned technical problems, this application provides the following technical solution: Firstly, this application provides a multi-agent-based continuous casting billet simulation method, including: Obtain information on the continuous casting billet exit process; Based on the continuous casting billet exit process information and the preset model library, a continuous casting billet exit simulation model is established. The continuous casting billet exit simulation model includes: billet module, billet exit track module, transverse transfer zone module, cooling bed module, hot delivery module and their respective simulation logic rules. The preset model library includes: cutting and conveying track intelligent body, lifting baffle intelligent body, transverse transfer zone roller conveyor intelligent body, marking machine intelligent body, steel lifting machine intelligent body, steel pushing machine intelligent body, cooling bed intelligent body and collection bed intelligent body. Based on the continuous casting billet simulation model, the continuous casting billet simulation was completed.

[0008] In one embodiment, the step of completing the continuous casting billet simulation based on the continuous casting billet simulation model includes: Acquire input data, which includes: billet output variables, transverse shift zone variables, and other parameters; The input data is input into the continuous casting billet simulation model to obtain the output results of the continuous casting billet simulation model. The output results include: billet discharge time interval, billet residence time on the walking beam cooling bed, time of operation of each equipment, and state percentage of each equipment.

[0009] In one embodiment, after establishing the equipment and process simulation model, the method further includes: Establish a three-dimensional model corresponding to the continuous casting billet simulation model, and display the three-dimensional model on the front end; Based on the continuous casting billet simulation model and the three-dimensional model, the continuous casting billet simulation is completed.

[0010] In one embodiment, the multi-agent-based continuous casting billet simulation method further includes: Receive input data from the front end; The input data is input into the continuous casting billet simulation model to obtain the output result of the continuous casting billet simulation model, and the running state of the three-dimensional model is adjusted based on the output result.

[0011] In one embodiment, the multi-agent-based continuous casting billet simulation method further includes: The output results of the continuous casting billet simulation are evaluated for abnormality based on the preset simulation result evaluation index.

[0012] In one embodiment, the continuous casting billet exit process information includes: key process parameters, multiple processing steps, and the duration of each processing step.

[0013] In one embodiment, the billet module is used to simulate the casting of a billet; the billet exit track module is used to simulate the process of the billet entering, transporting, and exiting the billet on the billet exit track; the transverse transfer zone module is used to simulate the process of the billet performing the transverse transfer zone process, which includes: marking, lifting, and pushing; the cooling bed module is used to simulate the process of the billet entering, storing, cooling, and exiting the billet in the cooling bed; and the hot delivery module is used to simulate the process of the billet undergoing secondary marking, billet collection, rotation, and furnace loading.

[0014] Secondly, this application provides a multi-agent-based continuous casting billet simulation device, comprising: The acquisition module is used to acquire information about the continuous casting billet exit process. The construction module is used to establish a continuous casting billet simulation model based on the continuous casting billet exit process information and a preset model library. The continuous casting billet exit simulation model includes: a billet module, a billet exit track module, a transverse movement zone module, a cooling bed module, a hot delivery module, and their respective simulation logic rules. The preset model library includes: a cutting and conveying track intelligent entity, a lifting baffle intelligent entity, a transverse movement zone roller conveyor intelligent entity, a marking machine intelligent entity, a steel lifting machine intelligent entity, a steel pushing machine intelligent entity, a cooling bed intelligent entity, and a collection bed intelligent entity. The simulation module is used to complete the simulation of continuous casting billet production based on the continuous casting billet production simulation model.

[0015] Thirdly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the multi-agent-based continuous casting billet simulation method.

[0016] Thirdly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the multi-agent-based continuous casting billet simulation method.

[0017] As can be seen from the above technical solution, this application provides a multi-agent-based continuous casting billet simulation method and device, which models the continuous casting billet stage, improving the efficiency of continuous casting billet simulation while ensuring its reliability. Specifically, it can achieve an accurate description of continuous casting billet in a short time, featuring fast model building speed, high efficiency, strong universality, and high reusability. It can effectively reduce the manpower and material resources invested in the verification process of new or modified technical solutions. The continuous casting billet simulation model established by this method can effectively verify and optimize new or modified continuous casting billet technical solutions, reducing design errors that may be overlooked or difficult to detect during the design process, such as design errors in the capacity of new or modified continuous casting billet and logistics conflicts. By changing parameters to simulate various schemes, a better solution can be sought, providing strong support for the rational planning and market development of continuous casting design schemes, providing steel enterprises with reusable simulation tools, and reducing the trial and error costs of new production line design and existing production line modification. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 This is a schematic diagram of the first process of the multi-agent-based continuous casting billet simulation method in the embodiments of this application; Figure 2 is a schematic diagram of a typical billet production process; Figure 3 This is a schematic diagram of the second process of the multi-agent-based continuous casting billet simulation method in the embodiments of this application; Figure 4 This is a schematic diagram of the second process of the multi-agent-based continuous casting billet simulation method in the embodiments of this application; Figure 5 This is a schematic diagram of a three-dimensional simulation of continuous casting billet production in an embodiment of this application; Figure 6 This is a schematic diagram showing the relationship between the interactive interface, the main interface, each module, and the main interface in the embodiments of this application. Figure 7 This is a schematic diagram of the structure of the multi-agent-based continuous casting billet simulation device in the embodiments of this application; Figure 8 This is a schematic block diagram of the system configuration of an electronic device according to an embodiment of this application. Detailed Implementation

[0019] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0020] The characteristics of a square-round billet continuous casting machine are a large number of flows, complex cross-sections, and high casting speeds. At high casting speeds, the distance between billets shortens. If the roller conveyor length is not designed for synchronization of multiple flows and high casting speeds, the next billet may enter before the previous one has left the roller conveyor, leading to billet stacking and congestion. When multiple-flow billets need to be temporarily stored, the cooling bed's capacity and cooling efficiency must match the multi-flow output. If the cooling bed area is insufficient or the cooling rate is slow (e.g., uneven coverage by the spray system), billets will accumulate on the cooling bed, pushing back to the billet discharge roller conveyor and causing blockage. Furthermore, depending on the production cross-section, various billet discharge processes are designed to match the billet discharge rhythm, based on different plant conditions and process requirements, matching and combining different billet discharge equipment. Therefore, a core issue of square-round billet continuous casting machines is the design of the billet discharge method and rhythm in the billet discharge area.

[0021] For multi-strand (generally 6 or more strands) continuous casting machines, the high number of strands leads to a fast billet discharge rate. The billet discharge system needs to promptly transport the produced billets off the line to ensure normal operation. The same problem exists when producing short-length billets; the short length also results in a fast billet discharge rate, posing a significant challenge to the billet discharge system. Furthermore, when producing small cross-section billets, the high casting speed leads to a fast billet discharge rate, requiring the billet discharge system to have rapid processing capabilities. Given the current trend, multi-strand, especially 8-strand or higher, continuous casting machines and high-speed continuous casting machines are becoming increasingly mainstream. Therefore, calculating the billet discharge rate for square and round billet continuous casting machines is particularly crucial in the design of continuous casting machines.

[0022] Existing steelmaking-continuous casting process modeling typically only extends to the continuous casting pouring stage, neglecting the subsequent billet unloading stage. The billet unloading stage is a crucial link in the steel production process, connecting continuous casting with rolling or heat treatment. Its core task is to efficiently and systematically deliver the billets produced by the continuous casting machine to the next process through a series of dynamic processes including cutting, transportation, temporary storage, and transfer. This process is characterized by strong dynamism (e.g., fluctuations in billet generation rhythm and changes in equipment status), tight system interrelationships (coupling of multiple links such as the continuous casting machine, cutting equipment, transport rollers, lifting equipment, and stacking area), and high uncertainty (process parameter adjustments, priority changes, etc.). With the increasing demand for flexible production of multiple varieties and small batches in steel enterprises, the continuous casting billet unloading process requires frequent adjustments. Existing technologies suffer from high actual trial-and-error costs in design and optimization, low efficiency in scheme verification, and an inability to predict problems during the dynamic operation of billet unloading and the matching of subsequent stages. This is precisely the core motivation for this invention to focus on the continuous casting billet unloading system and construct a targeted logistics simulation method.

[0023] The "multi-flow" characteristic of multi-flow, high-speed continuous casting machines necessitates the simultaneous processing of multiple billets moving in parallel. The high casting speed further increases the billet output density per unit time, leading to a dual challenge in terms of both spatial and temporal capacity of the material flow path. This study simulates different scheduling strategies (such as marking time and conveyor speed) for the billet's material flow path from cutting to hot delivery, identifying bottlenecks in the billet exiting process, reducing waiting time, and improving production continuity. Existing steelmaking-continuous casting process modeling in the market typically only covers the continuous casting pouring stage, lacking simulation of the subsequent billet exiting process.

[0024] This invention proposes a multi-agent-based simulation method and apparatus for continuous casting billet production. It can rapidly establish a simulation model of continuous casting billet production, providing strong support for the rational planning and market development of continuous casting design schemes. It offers steel companies a reusable simulation tool, reducing the trial-and-error costs of new production line design and existing production line modification, and helping companies transform from experience-driven to data-driven production models. Furthermore, the simulation modeling method improves safety and mitigates risks. Simulation modeling can reproduce real-world scenarios in a virtual environment without incurring actual risks. It can be repeatedly run by adjusting model parameters, significantly reducing physical resource consumption, making it particularly suitable for scenarios requiring multiple iterations of optimization, such as design and process improvement. Simulation modeling can strictly isolate variables through preset parameters, precisely controlling the influence of single factors. Simulation results under the same parameter settings can be repeatedly verified, facilitating comparative analysis and pattern summarization. Simulation modeling can also quickly obtain long-term evolution results or precisely capture instantaneous dynamics by accelerating or slowing down the time process, thereby identifying potential problems in the solution. Simulation modeling supports multi-scheme pre-playing and optimization. Before decision implementation, simulation modeling can simulate the effects of different strategies, predict potential risks by comparing results, and thus select the optimal solution without actual implementation, thereby improving decision-making efficiency.

[0025] The following examples illustrate this in detail.

[0026] To improve the efficiency of continuous casting billet production simulation while ensuring its reliability, this embodiment provides a multi-agent-based continuous casting billet production simulation method, where the execution subject is a multi-agent simulation device. Figure 1 As shown, this method specifically includes the following: Step 100: Obtain continuous casting billet output process information.

[0027] Specifically, the continuous casting billet production process information may include: key process parameters, multiple processing steps, duration of each processing step, equipment list, equipment static attributes, equipment execution steps, and connection relationships between equipment, etc.

[0028] Specifically, the continuous casting billet exit process can be analyzed to extract relevant information, such as key process parameters, processing steps, and timeframes. A simulation model of the equipment and processes (i.e., a continuous casting billet exit simulation model) can be established based on this process, along with internal simulation logic rules. The parameter ranges and input / output content for the simulation calculation platform interface can be defined. Relevant indicators for evaluating the simulation results can be set.

[0029] Specifically, the continuous casting billet removal process refers to the process from when the billet is pulled out of the continuous casting machine to when it enters the next process (such as the heating furnace before rolling). The continuous casting billet removal process involves the coordination of multiple devices and the interaction of multiple parameters, requiring analysis combining physical processes and logical rules. For example... Figure 2 As shown, the cut continuous casting billet is fed into the cutting and conveying track. The main equipment involved in the typical square and round billet output process includes: the cutting and conveying track, the lifting baffle, the transverse zone roller conveyor, the marking machine, the steel lifting machine, the steel pushing machine, the cooling bed, the collecting bed, and the overhead crane. The main equipment is set as intelligent agents. Through the interaction and cooperation between intelligent agents, the rational allocation of resources can be achieved. When the logistics system needs to be expanded or upgraded, it is only necessary to add or modify the corresponding intelligent agents.

[0030] The main process is as follows: the billet enters the cutting and conveying track, and as the lifting baffle is lowered, it enters the transverse zone roller conveyor. Here, the marking machine, steel lifting machine, and steel pushing machine complete the marking, steel lifting, and steel pushing processes. Then, it enters the cooling bed, is cooled, and then enters the collection bed.

[0031] Step 200: Based on the continuous casting billet discharge process information and the preset model library, establish a continuous casting billet discharge simulation model. The continuous casting billet discharge simulation model includes: billet module, billet discharge track module, transverse transfer zone module, cooling bed module, hot delivery module and their respective simulation logic rules. The preset model library includes: cutting and conveying track intelligent body, lifting baffle intelligent body, transverse transfer zone roller intelligent body, marking machine intelligent body, steel lifting machine intelligent body, steel pushing machine intelligent body, cooling bed intelligent body and collection bed intelligent body.

[0032] Specifically, the preset model library can be used to establish a simulation model for continuous casting billet production, enabling an accurate description of continuous casting billet production in a relatively short time.

[0033] Specifically, the simulation logic rules can include triggering conditions and execution actions. An intelligent agent corresponding to the continuous casting billet exiting process information can be selected from the preset model library, and combined with the continuous casting billet exiting process information to form a continuous casting billet exiting simulation model. The billet module can be used to simulate the casting of billets; the billet exiting track module can be used to simulate the process of the billet entering, transporting, and exiting the billet on the exiting track; the transverse movement zone module can be used to simulate the process of the billet performing transverse movement zone operations, including: marking, lifting, and pushing; the cooling bed module can be used to simulate the process of the billet entering, storing, cooling, and exiting the billet in the cooling bed; and the hot delivery module can be used to simulate the process of secondary marking, billet collection, rotation, and furnace loading of the billet.

[0034] Specifically, the process of establishing a continuous casting billet simulation model based on the continuous casting billet discharge process information and a preset model library may include: 1) Constructing the billet module. The billet is the initial billet formed during the continuous casting production process. In the continuous casting billet simulation, it is the core circulation element throughout the entire process, and a key carrier connecting the billet output stage of the continuous casting machine with subsequent transportation, processing, and storage processes. From a characteristic perspective, the billet has specific dimensional parameters such as length, width, and thickness. These attributes directly affect its circulation path, processing method, and interaction logic with other equipment in the logistics system. In the simulation scenario, the dynamic behavior of the entire process—including billet generation (corresponding to the billet output rhythm of the continuous casting machine), transportation (via roller conveyors, overhead cranes, etc.), temporary storage (in cooling beds, buffer zones, etc.), and subsequent processing (such as length cutting and marking)—is the core element for constructing the continuous casting billet simulation model. Its circulation efficiency and state changes directly reflect the operational performance of the entire logistics system.

[0035] Specifically, the core of continuous casting production is to continuously cast molten steel into billets, and all subsequent processing steps are based on the billets. Therefore, in the simulation of continuous casting billet production, the billet naturally becomes the link connecting all the steps. In the simulation, the movement, waiting, and processing behaviors of the billet are transformed into events in the model through time axis, path changes, etc., and the position of the billet is displayed in real time in the simulation interface to help users intuitively understand the system's operating status.

[0036] The dimensions and other attributes of the cast billet directly determine the selection of transportation equipment, the planning of storage areas, and the parameters of processing technology. These are essential data for the logical connections between various devices in the simulation model. The length attribute of the cast billet is converted into a quantifiable parameter, v_fixed length, which serves as the input to the equipment interaction logic. The width of the cast billet is then linked to other processes.

[0037] The billet can be configured with parameters for entry and exit times (ventry and vexit), which record the time it takes to enter and exit a particular piece of equipment. This data can be used to calculate the total time required for a specific process. If the billet remains stuck in a certain stage for an extended period, the simulation model can pinpoint that stage as a system bottleneck, providing a basis for optimization.

[0038] The v-number parameter of the billet records which stream of the continuous casting machine the billet is connected to on the roller table. This parameter can be used for sorting and is an important parameter when the billet position changes.

[0039] 2) Construction of the billet exit track module. The billet exit track is the core infrastructure for billet transportation, serving as the artery network connecting key links such as the continuous casting machine, cutting equipment, and cooling bed. Its design and operation directly affect the continuity, efficiency, and equipment coordination of billet flow. The billet exit track module primarily generates the cut continuous casting billets based on user requirements. Users can adjust the billet exit track length, speed, etc. The cut billets are placed on the post-cutting and conveyor rollers and move with them to the exit point to wait. Its length covers from the post-cutting roller area to the entrance of the transverse transfer area. Multi-strand continuous casting machines connect to multiple billet exit tracks, and the simulation should be able to change the number of billet exit tracks. The billet exit track does not exist in isolation; it needs to be deeply coordinated with the billet and subsequent processes. Each billet exit roller is independent, therefore, the casting speed, billet production time interval, and billet length can be adjusted individually. Inputting relevant parameters into the simulation model will generate the billet and begin its transportation on the track.

[0040] Specifically, the billet discharge track is a core transportation link connecting the continuous casting machine and subsequent processing equipment. Its design rationality directly affects billet discharge efficiency, billet flow continuity, and workshop space utilization. Supporting dynamic adjustment of track length, speed, and flow rate is key to enabling simulation models to closely resemble actual production and achieve optimized decision-making.

[0041] The billet exit track length, exit track speed, and number of billet exit tracks can be adjusted. It can generate 1-12 billet exit tracks, and the drawing speed (bill production time interval) and billet length of each stream can be adjusted individually. By inputting the relevant parameters, this module will generate billets and start transporting them on the track.

[0042] Track length refers to the effective transport distance of a single track from the starting point (end of billet cutting) to the end point (exit of the billet roller conveyor). It provides temporary storage space for steel billets. When the billet length is long, a longer track or other methods are needed to avoid overlapping of the billet ends. When the billet exit interval of the continuous casting machine is short, a longer track is needed to temporarily store billets awaiting processing. The length of the billet exit track is set by the parameter v_length.

[0043] Track speed refers to the rate at which the billet is transported on the track. The speed of the roller conveyor directly affects the efficiency of billet flow. If the speed is too fast, it may cause collisions between billets or make it impossible to brake in time due to excessive inertia. If the speed is too slow, it will prolong the transportation time and cause billets to accumulate at the exit of the track. The parameter v speed is used to set the speed at which the billet moves on the billet exit track.

[0044] The continuous casting speed determines the billet generation frequency, which needs to be converted into the billet generation interval in the simulation model. The billet generation time interval (v) is set to indicate how long it takes for each roller to generate a new billet in the simulation. This parameter is calculated from parameters such as the continuous casting machine speed. Converting the actual parameters into simulation model parameters requires logical calculations to transform the actual process indicators into executable parameters for the model.

[0045] Each billet exit track is a smart agent. The agent c records the billet on the exit track, the billet height c is the distance of the billet from the ground on the exit track, and the departure time v is the time it takes for the billet to leave the exit track. Sourcecreate generates billets according to the calculated billet production time interval. After entering the queue, the length of the billet is modified to the fixed length of the corresponding number of billets. After entering the queue, it moves on the track at a set speed. Here, the exit track is set to be stationary while the billet moves to achieve the effect of transporting the billet. After reaching the destination, it enters the queue to wait. The queue waiting capacity is set to 1. Each time, the billet closest to the exit enters. When billet exiting begins, hold is opened, and the billets in the queue enter the delay. Hold is closed. When the billet leaves the delay, the exit time is recorded. At the same time, the remaining billets in the queue (if they exist) will move forward one position, and the first one enters the queue to wait. The above billet exiting action is repeated.

[0046] Billet discharge logic: A logical judgment is performed every second to check if there is a billet waiting in the queue and if the billet is moving. If there is a billet in the queue and the billet has stopped moving, it means that the billet has reached the end of the track and is waiting to be discharged. Continue to the next judgment. When the lifting baffle 1 is above, the function fbaffle1 is run. If the lifting baffle 1 is below, it is checked whether the subsequent steel lifting machine is empty. When the subsequent steel lifting machine is empty, hold is opened to allow the billet to pass through. When the subsequent steel lifting machine is not empty, the billet is allowed to wait at the exit.

[0047] The inputs to the billet exit track module can be: the number of continuous casting machines, the billet pulling speed per flow, the fixed length of the billet, the number of billets exiting per flow, the distance from the cutting endpoint to the lifting baffle 1, and the linear speed of the conveyor track after cutting; the outputs of the billet exit track module can be: the generated initial billet and the billet exit time interval distribution diagram.

[0048] 3) Construction of the transverse transfer zone module. In this zone, after the billet enters, it stops for a series of processes including marking, lifting, and pushing. The marking machine primarily marks the billet, which is then moved to the next process via lifting and pushing. The billet enters the transverse transfer zone via lifting baffle 1, moves forward, and stops before lifting baffle 2. After lifting baffle 2 descends, the marking machine starts. There are multiple marking machines, distributed as evenly as possible according to the number of billets and the number of marking machines, minimizing the total marking time for a batch of billets. After each billet is marked, it is lifted by the lifting machine and placed on the upper storage track. Once all billets in a batch have been marked and lifted onto the storage track, the pushing machine begins pushing the billets out for storage, preparing them for the cooling bed. The lifting machine cannot lift billets while the pushing machine is moving in the lifting machine area. The transverse transfer zone may include: lifting baffle 1, transverse transfer zone roller conveyor, lifting baffle 2, marking machine, steel lifting machine, and transverse steel transfer car. When lifting baffle 1 descends, the billet passes through and reaches the front of lifting baffle 2 along with the transverse transfer zone roller conveyor. Then lifting baffle 2 descends, and the marking machine starts marking operations in sequence. After marking is completed, the billet is lifted to the upper roller conveyor by the steel lifting machine. After a certain number are reached, the transverse steel transfer car pushes it onto the transition slide rail.

[0049] The pause and processing of the billet after it enters the transverse transfer zone serves three functions: information identification, position conversion, and orientation adjustment. The coordination of this series of marking, lifting, and pushing processes directly affects the accuracy and efficiency of subsequent logistics scheduling. Its simulation modeling needs to recreate the physical operation details, dynamic parameter relationships, and anomaly response logic, which can be broken down into the following stages: Precise billet positioning is a prerequisite for the transverse transfer zone process. After the billet enters the transverse transfer zone via the roller conveyor, it must first complete a positioning stop to provide a stable operating reference for subsequent processes. Lifting baffles are installed at the entrance and end of the transverse transfer zone. When the billet touches the lifting baffle 2, the system issues a stop command, and the transport equipment immediately brakes. After the stop is completed, the transverse transfer zone control system sends a billet ready signal back to the subsequent connected processes.

[0050] Marking is a process of marking the steel grade, furnace number, specifications and other information on the surface of the billet with high-temperature corrosion-resistant coating. In the simulation, multiple marking machines need to work together. When there are multiple billets queuing in the transverse movement area, they are marked in the order of their stopping positions.

[0051] Steel lifting is a process of raising the billet from the transport plane (such as a roller conveyor) to the height of the transverse track using a hydraulic or mechanical lifting device. This provides a height reference for subsequent steel pushing. Each billet can be lifted individually. The timing of steel lifting and the connection with the marking signal must wait for the marking signal to be completed before starting the lifting. In the simulation, a signal interlock is set. If the marking signal is not completed, the steel lifting device remains in standby mode.

[0052] Pushing billets is a process in which a pusher rod propels the lifted billet along a transverse track to a designated position (such as the cooling bed inlet or buffer zone). This process transforms the billet's path from linear transport to transverse distribution. When the front end of the billet reaches the target position, the pusher rod automatically resets, awaiting the next batch of billets. If the target space is already occupied by other processes (e.g., a billet lifting machine is lifting billets), the simulation needs to set the waiting logic for the pusher rod. Similarly, if the billet lifting machine is in the process of pushing billets or returning, the simulation also needs to set the waiting logic for other equipment to avoid collisions between the operating spaces of different equipment.

[0053] In continuous casting billet production simulation, the processes of marking, lifting, and pushing the billet after it enters the transverse transfer zone are the fusion nodes of information interaction and physical action. By accurately modeling the parameters, logic, and coordination relationships of each process, the time-series optimization space, equipment bottlenecks, and potential risks can be quantitatively analyzed. This provides data support for transverse transfer zone layout design (such as adding backup lifting devices) and scheduling rule upgrades (such as dynamically adjusting pushing priority), ultimately improving the stability and efficiency of the continuous casting billet production process.

[0054] Specifically, the billet enters the transverse movement zone through lifting baffle 1, moves forward and stops in front of lifting baffle 2. After lifting baffle 2 descends, the marking machine starts. There are 1-3 marking machines, and all billets are evenly distributed among them. For example, if there are 8 billets and 3 marking machines, they will be distributed to the 3 marking machines in a 3:3:2 ratio. Each marking machine starts from the bottom of the screen and marks the assigned billets in sequence. After each marking machine finishes its work on a billet, the billet is lifted up by the steel lifting machine and waits on the upper storage track. After all billets have been marked and lifted onto the storage track, the steel pushing machine starts its pushing operation, pushing the billets out and preparing them for entering the cooling bed.

[0055] Among them, the lifting baffle 1 is: The `v` indicator represents the current state of the lifting baffle 1, indicating whether it is rising or falling. The `v` indicator duration is the time the lifting baffle takes to rise or fall, and the `v` indicator distance is the distance the lifting baffle travels. Upon receiving "down1", it begins to move downwards. After descending, the `v` indicator changes, and simultaneously, it continuously checks the status of all billet exit tracks. When a prepared billet is available at a certain outlet, it is allowed to exit directly. Upon receiving "up1", it begins to move upwards, simultaneously changing the `v` indicator. Billets are not allowed to pass through during either the descent or ascent.

[0056] The marking machine is: The `vstart` and `vdetection` parameters, specifically the descaling and marking reset times, are user-input parameters. `vquantity` records the number of billets allocated to each marking machine. `vspark` controls the on / off state of the marking spark. `vflow` records the flow number of the track corresponding to the marking machine's position. `i` indicates the current billet's position among all allocated billets. The `vstatus` parameter displays the marking machine's status in real-time: 0 for standby, 1 for start, 2 for marking, and 3 for movement. The `dataset` parameter records the values ​​of the `vstatus` parameters for output. The `event` parameter reads the `vstatus` values ​​every second and records them in the `collection` state dataset. The `function` parameter analyzes the contents of the `collection` state dataset, calculating the percentage of each marking machine state and outputting the results to `vstandby`, `vstart`, and `vmarking` respectively.

[0057] After receiving "pok", the marking machine sets i to 1, indicating that it is preparing to process the first billet. The marking machine then starts, determining the current number of billets being processed, i. When i is less than or equal to the allocated number of billets, it begins marking, illuminating the area with a spark. The spark extinguishes after a set time, indicating the marking process is complete and the machine is ready to move. When all allocated billets have been marked, the marking machine remains stationary; otherwise, it moves upwards to the previous flow. Next, it loops through the billets in the delay marking section of main, finding and releasing the billets corresponding to the number of flows just completed. Then, it checks the relationship between i and the allocated number of billets. When i is less than or equal to the allocated number of billets, it repeats the above process. When i is greater than the allocated number of billets, it indicates that all allocated billets have been marked, the marking machine moves downwards to its original position, the v-state and v-flow data are restored to their initial values, and "up2" is sent to the lifting baffle 2 to raise it.

[0058] The main input can be the initial casting billet, and the output can be the casting billet after marking and the marking machine's operating rate.

[0059] Among them, the lifting baffle 2 is: v_lifting_time is the time it takes for the lifting baffle to rise or fall, v_lifting_plate_distance is the distance the lifting baffle moves as it rises or falls, and num is a counting parameter. Upon receiving "down2", it begins to move downwards. After descending, it sends "pok" to all marking machines to start marking. Then, it initializes the num parameter to zero and begins waiting for 1. Each time a marking machine finishes marking a billet, it sends "up2" to lifting baffle 2. Upon receiving this, lifting baffle 2 increments the count num by 1. It then checks the relationship between num and the number of marking machines. If num is less than the number of marking machines, it continues the waiting process of 1 minus the count. When num equals the number of marking machines, it indicates that all billets have been marked, and lifting baffle 2 begins to rise. After rising, it stops and waits for the next command.

[0060] Among them, the steel lifting machine is: `v_lift_height` represents the distance the steel lifting machine lifts, `v_lift_time` represents the time it takes for the steel lifting machine to rise, and `v_fall_time` represents the time it takes for the steel lifting machine to return to its original position. The `v_status` displays the real-time status of the marking machine: 0 indicates standby, 1 indicates judgment (waiting), and 2 indicates steel lifting operation. The `dataset` records the value of the `v_status` over time for output. The `event` reads the value of the `v_status` once per second and records it in the `collection` state dataset. The `function` analyzes the contents of the `collection` state dataset, calculates the proportion of each state of the steel lifting machine, and outputs the results to `v_standby`, `v_waiting`, and `v_lift`, respectively.

[0061] Upon receiving the "Liftsteel" message, the system checks every second whether the pusher is operating. If the pusher is active, the lifting machine waits in place until the pusher finishes its work. When the pusher is stationary, the lifting machine prepares to rise. First, it uses a loop to find the corresponding billet on the lifting machine from the `main`'s `collection`, places the billet on the lifting machine, and modifies its coordinates. The billet will then rise with the lifting machine. If no corresponding billet is found on the lifting machine, a message will appear: "Lifter cannot find billet."

[0062] After the ascent is complete, the billet is placed in the main process and its coordinates are adjusted. At this point, the billet can leave the lifting machine and enter the pushing process. The main process's delay lifting machine releases the billet, and the billet is deleted from the main process's collection lifting machine, allowing it to enter the next process. If the corresponding billet is not found on the lifting machine, a "lifting machine cannot find billet" message will appear. After placement, the lifting machine moves downwards to its original position, and efficiency is calculated.

[0063] Among them, the steel pusher is: `v_pushing_time` is the one-way time for the steel pusher to push steel once. `i` is a loop counter parameter, `collection` is a sorted set, and `v_state` displays the real-time status of the marking machine: 0 indicates standby, 1 indicates return, and 2 indicates steel pushing operation. The `dataset` records the value of `v_state` over time for output. The `event` function reads the value of `v_state` once per second and records it into the `collection` state dataset. The `function` calculates the efficiency by analyzing the contents of the `collection` state dataset, determining the percentage of each state of the steel pusher, and outputting the results to `v_standby`, `v_return`, and `v_pushing` respectively.

[0064] When a billet enters the pusher, it first enters the delay sorting process, where its entry is recorded in the collection. Once the set quantity is reached, it leaves the delay sorting process and enters the delay pusher process. When leaving the delay sorting process, the billet is re-sorted in the collection starting from 0 based on its flow number. After all billets in the delay sorting process have entered the delay pusher process, the delay pusher sends an "ok" signal to itself, thus advancing the process.

[0065] The initial state (v) of the pusher is 0. Upon receiving "ok", the value of i is set to 1. The relationship between i and the number of billets in the delay pusher is checked. If i is less than the number of billets in the delay pusher, the pusher enters the pushing state, and the v state changes to 2. The pusher moves towards the billets at a set speed. Once it reaches the billets, it places them on the pusher rod and modifies the corresponding coordinates, causing the billets to move with the pusher rod. The i value increases by 1. This process repeats until the pusher rod has pushed all the billets. At this point, the i value is also greater than the number of billets in the delay pusher. The pusher rod pushes all the billets downwards. After reaching the desired position, all the billets on the pusher rod are placed in the main function, and the corresponding coordinates are updated. The pusher rod prepares to return to its original position, and simultaneously, the delay pusher releases all the billets, the collection is cleared, and the v state changes to 1. When the pusher rod returns to its original position, the efficiency data is recorded using a function.

[0066] The input is the sprayed billet, and the output is the operating rate of the sprayed billet, steel lifting machine, and transverse steel moving car.

[0067] 4) Construction of the cooling bed module. The cooling bed is the core equipment connecting the continuous casting machine and the subsequent rolling process. Its core functions are billet cooling, length buffering, and material transfer. The cooling bed is used to transport and turn the billets, ensuring uniform cooling and preventing deformation. After entering the cooling bed, the billets move forward at a set distance via fixed and movable plates. Once they reach their destination, they leave the cooling bed and are collected in groups by an overhead crane and transferred to the collection bed. Billets on the transition slide rail enter the cooling bed, where they are cooled stepwise. After leaving the cooling bed, they enter the collection bed, and several billets are lifted off in groups by an overhead crane.

[0068] In logistics simulation software, the core components of the cooling bed must be recreated according to the actual structure to ensure accurate motion logic. The modeling of the stepping beam's rising → translating → falling → retracting cyclical motion trajectory must be matched with the billet length to avoid billet collisions.

[0069] The core of the cooling bed model is to simulate the entire process of billet entering, storing, cooling, and exiting the cooling bed, and the following logical rules need to be configured: Bed entry logic: Defines the triggering conditions for the billet to enter the cooling bed. When the inlet roller conveyor detects the billet and there is available space on the cooling bed, the bed entry conveyor is started; if the cooling bed is fully loaded, the billet is temporarily stored on the roller conveyor. In-bed logic: The billet is moved according to the step cycle to avoid overlapping of the same row of billets; after the billet enters the bed, it begins to circulate and cool until it reaches the outlet after cooling is complete. Outgoing Billet Logic: Defines the triggering conditions for billet exiting the cooling bed. When the exit roller conveyor is idle and the billet has cooled to the required standard and reaches the exit point, the outgoing conveyor is activated. Billets leaving the cooling bed are temporarily stored together and transported to the collection bed after a specified quantity is reached.

[0070] Specifically, `vslab quantity` refers to the number of slabs stored before entering the cooling bed; `vcycle` is the time it takes for the cooling bed to return to its original position after one cycle; `vstep distance` is the length of the cooling bed's step; and `vup / down movement distance` is the distance the cooling bed moves up and down. `collection` sorting, `collection stepping`, and `collection storage` refer to the collection of slabs stored during the cooling bed's movement.

[0071] The castings first enter the delay sorting process. All castings are then sorted by flow count in ascending order using the collection sorting method and recorded in the collection sorting. Once the required quantity is reached, the castings enter the delay storage. In the delay storage, the castings from the collection sorting are placed in reverse order and stored in the collection storage. When a casting leaves the delay storage, it is deleted from the collection sorting one by one, and the quantity stored in the v castings storage is updated synchronously. Then, they enter the delay storage to wait.

[0072] When the cooling bed changes to a delayed storage release state, the last billet stored in the collection will be released. The released billet is moved to the cooling bed entrance via moveTo2 and enters the delayed stepping mechanism. At the same time, this billet is added to the collection stepping mechanism. Then, the cooling bed enters the billet picking state, allowing the billet to move upwards with the cooling bed. The billet position is then determined. When the billet reaches the cooling bed exit, the delayed stepping mechanism releases the billet, allowing it to leave the cooling bed and recording the time. The remaining billets continue to move downwards with the cooling bed and return to their original positions, repeating the stepping process.

[0073] After leaving the cooling bed, the billets enter the delay collection bed inlet and wait. Once a certain number are reached (the number can be adjusted via the `v` collection bed group quantity), the delay collection bed inlet is released, and the billets enter `moveTo1` to move to the delay collection bed outlet. A crane is then invoked to move this group of billets away. Since the crane can only transport one set of agents, a new agent is generated via the `source` crane anchor point. All the billets in the delay collection bed crane are placed on the new agent. The crane lifts the new agent while simultaneously lifting this group of billets, achieving the effect of the crane transporting a group of billets.

[0074] The input is the billet after the spraying is completed, and the output is the cooling bed cycle, etc.

[0075] 5) Construct a hot conveying module. The hot conveying section involves complex processes, often including double cutting, secondary marking, rotation, billet collection, and billet separation. This part can be appropriately simplified or components from the transverse transfer zone can be reused.

[0076] Specifically, the hot delivery module involves complex processes, often including a series of operations such as secondary cutting, secondary marking, rotation, billet collection, and billet separation. The model simplifies some processes, demonstrating secondary marking, billet collection, rotation, and furnace loading of the cast billet. The process is as follows: the cast billet hoisted by the overhead crane is temporarily stored in the queue. When needed, it is moved via moveTo and enters the delay secondary marking queue. After marking, it enters the pusher 1, and its marking and pushing process is similar to that of the billet unloading module. After pushing, it is temporarily stored in queue 1, and then moved one by one onto the conveyor belt, rotating with the belt before being moved into the heating furnace.

[0077] Specifically, existing modeling and simulation tools can be used to establish the continuous casting billet simulation model. These tools are widely applicable, capable of modeling and simulating discrete, system dynamics, multi-agent, and hybrid systems, with broad applications. Using them for simulation can achieve visualization, save money and time, improve design accuracy, and handle uncertainties. A billet logistics simulation model can be established through secondary programming of the software's built-in toolbox, effectively combining commercial software-based simulation with self-developed software simulation. This allows for accurate description of complex continuous casting billet processes in a short time, enabling rapid construction of a continuous casting billet simulation model.

[0078] Furthermore, from one perspective, the continuous casting billet exit simulation model may include: a billet casting module, a billet exit track module, a transverse movement zone module, a cooling bed module, a hot conveying module, and their respective corresponding simulation logic rules; from another perspective, the continuous casting billet exit simulation model is constructed from a multi-agent-based continuous casting billet exit process model and a multi-agent-based continuous casting billet exit streamline model. The multi-agent-based continuous casting billet exit process model is input with equipment and process parameters; the multi-agent-based continuous casting billet exit streamline model is input with logistics and transportation parameters; the continuous casting billet exit simulation model is run to obtain simulation data. This allows for a focus on logistics smoothness, reducing waiting times, eliminating bottlenecks, and assessing congestion and connection issues in the logistics process. A simulation model of equipment and processes can be established by selecting intelligent agents corresponding to the continuous casting billet output process information from a preset model library and combining them with the continuous casting billet output process information. Based on the equipment and processes simulation model, simulation logic rules (i.e., internal simulation logic rules of the equipment / process), logistics relationship control algorithms between processes, and transportation equipment scheduling algorithms are established. Based on the equipment and processes simulation model and the internal simulation logic rules of the equipment / process, a continuous casting billet output process model is established. Based on the logistics relationship control algorithms between processes and the transportation equipment scheduling algorithms, a continuous casting billet output streamline model is established. The continuous casting billet output simulation model can be constructed from the continuous casting billet output process model and the continuous casting billet output streamline model. The continuous casting billet output simulation model can represent the continuous casting billet output logistics simulation model.

[0079] Step 300: Based on the continuous casting billet simulation model, complete the continuous casting billet simulation.

[0080] Specifically, the entire process flow of continuous casting billet output simulation based on multi-agent systems can include: the billet enters the cutting and conveying track, and as the lifting baffle descends, it enters the transverse zone roller conveyor. Here, the marking machine, steel lifting machine, and steel pushing machine complete the marking, lifting, and pushing processes. Then, it enters the cooling bed, cools, and finally enters the collection bed. The main objects, such as the billet output roller conveyor, lifting baffle, marking machine, steel lifting machine, steel pushing machine, and cooling bed, are set as intelligent agents. Each intelligent agent has its own attributes and internal logic, which are encapsulated in a model library. The model library can be quickly called for continuous casting billet output simulation model construction in different scenarios without repeated development. When a new business module is added, only the corresponding intelligent agent needs to be added and the interaction rules defined; the entire continuous casting billet output simulation model does not need to be reconstructed.

[0081] Specifically, the continuous casting billet discharge simulation model can have two functions: billet discharge design and billet discharge optimization. Billet discharge design is divided into billet discharge module and hot conveying module design, allowing adjustments to the size, position, and quantity of some components within the model. Focusing on the cast billet, it realizes the entire process of the billet from the discharge track to the heating furnace. Billet discharge optimization involves adjusting relevant production parameters to change the billet discharge rhythm, ensuring a smooth discharge process. The billet discharge module can include: a cast billet module, a billet discharge track module, a transverse movement zone module, and a cooling bed module.

[0082] Furthermore, simulation platform interfaces can be designed, input and output parameters and databases can be built; simulation platform result analysis tools can be designed, simulation result evaluation indicators can be set, and comprehensive analysis tools can be developed.

[0083] Specifically, the process flow for designing the simulation platform interface may include: Based on the design drawings in the new / renovation technical scheme for continuous casting billet production, the physical space layout of the continuous casting billet production workshop is carried out using the process and logistics line models in the model library. Based on the logistics operation plan in the new / renovated continuous casting billet production technology scheme, a logistics control scheme for continuous casting billet production is set up using scheduling rule models in the model library. The model library can include modular intelligent agent models of processes, logistics lines, and scheduling rules. Specifically, the intelligent agent models can include: intelligent agents for the cutting and conveying track, intelligent agents for the lifting baffle, intelligent agents for the transverse transfer zone roller conveyor, intelligent agents for the marking machine, intelligent agents for the steel lifting machine, intelligent agents for the steel pushing machine, intelligent agents for the cooling bed, and intelligent agents for the collecting bed, etc.

[0084] The above steps can be coupled to establish a simulation model for continuous casting billet production.

[0085] The interface design of the simulation model needs to be closely integrated with the continuous casting production process to achieve digital simulation, optimized scheduling, and result analysis of the continuous casting billet output process. Its interface design must satisfy the closed-loop logic of data input, simulation calculation, and result output.

[0086] Based on the interactive requirements of continuous casting billet simulation, four types of core interfaces are designed to cover all data interaction scenarios: Data input interface: Receives user-inputted basic data, planning data, process parameters, etc. Input from external sources into the simulation model enables the initialization of the simulation environment.

[0087] Input parameters include: number of billets, billet drawing speed, fixed length, number of billets produced, distance from the cutting endpoint to lifting baffle 1, linear speed of the post-cutting and conveyor rollers, descent time of lifting baffle 1, descent time of lifting baffle 2, billet feeding time, number of marking machines, start-up time of marking machines, detection and descaling marking reset time, pushing time of the steel pusher, lifting time of the steel lifter, descent time of the steel lifter, cooling bed stepping distance, cooling bed up and down movement distance, cooling bed cycle, collection bed length, and collection bed translation distance. The specific design is shown in Table 1 below. Table 1

[0088] Control command interface: Receives externally triggered control commands, such as pausing, restarting the simulation, and adjusting parameters. Input is sent from external sources to the simulation model.

[0089] The simulation software interface includes operation buttons such as "Run," "Stop," "Accelerate / Decelerate," "Full Screen," and "Switch Development Layout." In addition, the simulation model also includes buttons to switch between 2D and 3D perspectives, view model data, and modify parameters. In the 3D view, users can left-click and drag, and scroll using the mouse wheel to rotate the angle.

[0090] Results output interface: Pushes simulation results to the user. Outputs simulation results to external systems.

[0091] When the state of the device changes, it is recorded in the v state using numbers such as 0, 1, 2, 3, 4, etc. Usually, 0 indicates standby, 1 indicates startup, 2 indicates working, and 3 indicates waiting or return. The design concept is the same in different devices, but the specific values ​​are different.

[0092] The status values ​​of the steel lifting machine, marking machine, and steel pushing machine are recorded once per second by the event and stored in the collection status dataset. When needed, the efficiency of the collection status dataset is analyzed and processed by the function to calculate the proportion of each state of the equipment and output it to their respective output variables. Through this data, the efficiency of the equipment can be accurately observed.

[0093] After the simulation, each module imports its statistical dataset into the main interface. After calculation and processing, the output is presented as charts, including a table showing the percentage of waiting time for the lifting machine, pushing machine, marking machine, and overhead crane; a line graph showing the billet output time interval; a line graph showing the billet's residence time on the walking beam cooling bed; and a status diagram of the overhead crane. These charts are also displayed in real-time, allowing for both real-time viewing and viewing after the simulation.

[0094] The billet exit time interval line graph is an intuitive and crucial visualization tool in the analysis of continuous casting billet exit simulation results. Its core function is to help analysts quickly identify the operating rules, potential bottlenecks, and matching with the continuous casting rhythm of the logistics system by continuously recording and displaying the changing trend of the billet exit time interval between two adjacent billets.

[0095] If the time interval in the line graph fluctuates slightly around the theoretical value, it indicates that the billet output rhythm is stable and the logistics system and continuous casting machine are working smoothly. If the line graph shows large fluctuations, it indicates that the billet output rhythm is chaotic, which may be due to equipment failure, scheduling errors or poor logistics connection. Further investigation is needed to find the cause.

[0096] If the actual interval in the line graph is consistently greater than the theoretical interval, it indicates that the logistics system's processing capacity is insufficient and cannot keep up with the billet output speed of the continuous casting machine. This may lead to billet accumulation at the continuous casting machine outlet, affecting the continuity of continuous casting production. If the actual interval is consistently less than the theoretical interval and there is no significant fluctuation, it indicates that the logistics system's processing capacity is redundant. This can be combined with indicators such as equipment utilization rate to determine whether there is a waste of equipment resources.

[0097] The line graph of the residence time of the billet on the walking beam cooling bed is a visualization tool for analyzing the operation status of the cooling bed in continuous casting billet simulation. It continuously records the actual residence time of each billet on the cooling bed and presents it in the form of a line graph, which intuitively reflects the cooling efficiency, logistics connection and resource matching of the cooling bed.

[0098] Abnormal changes in the residence time of the cooling bed can directly reflect its load status. If the residence time in the line graph continues to increase from a certain point, and the residence time of subsequent billets shows a cumulative increasing trend, it indicates that the cooling bed may be congested, and the cooling bed exit link needs to be checked. If the residence time is consistently shorter than the standard and the line graph is flat, while the actual occupancy rate of the cooling bed is low, it indicates that the cooling bed is idle. This may be due to the previous billet output rhythm being too slow or the cooling bed design capacity being too large, resulting in resource waste.

[0099] If the billet continues to accumulate at the cooling bed inlet, and the previous billet exit interval is normal, but the cooling bed dwell time suddenly increases, it indicates that the cooling bed processing capacity cannot match the billet exit speed of the continuous casting machine, which may become a logistics bottleneck. If the dwell time of most billets is close to the maximum design duration of the cooling bed, and congestion occurs frequently, it indicates that the cooling bed length or stepping frequency is insufficient, and it is necessary to consider extending the cooling bed or increasing the stepping speed.

[0100] The time-shading chart of each piece of equipment's operating status is a visualization tool used in continuous casting billet production simulation to intuitively display the equipment's operating status over time. Its core is to use different colors to encode the equipment's operating status, forming a matrix chart with the time axis as the horizontal axis and the equipment status data as the vertical axis. Through the continuous distribution of colors, the busy / idle level of the equipment within the simulation cycle can be quickly determined, thus clearly presenting the dynamic behavior of the equipment.

[0101] Equipment utilization assessment evaluates the rationality of resource utilization for key equipment such as marking machines and steel pushers, avoiding idle waste or overload congestion. Equipment involved includes: overhead cranes for hoisting, cold beds for storage, and marking machines for operation.

[0102] Equipment utilization rate is defined as the proportion of actual equipment operating time (such as the time spent by the marking machine marking the billet) to the total simulation time. A low utilization rate indicates equipment redundancy; a high utilization rate can lead to overload, requiring increased waiting time. Equipment idle time percentage is the proportion of time the equipment spends in an unprocessed billet state to the total time. Excessive idle time indicates wasted equipment resources, requiring optimized scheduling. In addition, there are the proportions of the marking machine's start-up time and the pusher's reset time to the total time.

[0103] The system aims to collect, process, and visualize data to support business decisions. The simulation model displays line graphs of billet time intervals, billet residence time on the walking beam cooling bed, time-shaded graphs of each piece of equipment's operating status, and a table showing the percentage of each piece of equipment's status. Users can use these charts to determine billet production rhythm and equipment utilization.

[0104] Status query interface: Responds to user queries for the real-time status of the simulation process. Includes animation display, real-time chart display, and real-time display of the quantity of billets stored after steel pushing is completed.

[0105] like Figure 3 As shown, in one embodiment, step 300 includes: Step 301: Obtain input data, which includes: billet output variables, transverse shift zone variables, and other parameters.

[0106] Step 302: Input the input data into the continuous casting billet simulation model to obtain the output results of the continuous casting billet simulation model. The output results include: billet discharge time interval, billet residence time on the walking beam cooling bed, time of operation of each equipment, and the percentage of each equipment's status.

[0107] Specifically, input data can include: billet output variables, transverse zone variables, and other parameters. Billet output variables include: continuous casting machine flow rate, continuous casting machine billet pulling speed, continuous casting billet length, number of billets per flow, distance of the billet from the cutting endpoint to the lifting baffle, and the linear speed of the billet after cutting and on the conveyor rollers. Transverse zone variables include: the time required for the lifting baffle to descend, the time for the billet to enter the transverse zone from the billet output rollers, the number of marking machines, the start time of each marking machine, the marking machine detection, descaling, and marking reset time, the time required for the pusher to push the steel, and the time required for the lifting machine to lift the steel. Other parameters include: the distance of each step of the cooling bed, the time required for the cooling bed to return to its original position after one revolution, the distance the collecting bed moves, and the length of the collecting bed. Output data can be the billet output time interval displayed in the continuous casting billet output simulation model, the billet residence time on the walking beam cooling bed, the operating time of each piece of equipment, and a chart showing the status percentage of each piece of equipment. Users can use these charts to determine the billet output rhythm and equipment utilization, enabling data collection, processing, and visualization, providing data support for business decisions.

[0108] like Figure 4As shown, in one embodiment, after step 200, the method further includes: Step 400: Establish a three-dimensional model corresponding to the continuous casting billet simulation model, and display the three-dimensional model on the front end.

[0109] Step 500: Based on the continuous casting billet simulation model and the three-dimensional model, complete the continuous casting billet simulation.

[0110] Specifically, based on the constructed continuous casting billet simulation model, a 3D solid model of the equipment can be extracted using professional industrial design software. Lightweight model processing technology can then be used to convert the native 3D format into an intermediate format compatible with the simulation platform. After importing into the simulation environment, the model's accuracy can be adjusted to maintain visual animation expressiveness while ensuring simulation calculation efficiency, providing intuitive decision support. Furthermore, demonstrations can be conducted based on actual data, simulating various scenarios by changing parameters to seek a better solution.

[0111] Specifically, based on the previously constructed continuous casting billet simulation model, in order to achieve a more intuitive visualization and accurate decision support, it is necessary to complete the simulation environment adaptation of the model through multi-stage technical processing to establish the three-dimensional model. The specific process can be as follows: First, using professional industrial design software, 3D solid models were created and extracted from core equipment in the continuous casting billet output process, such as roller conveyors, pushers, and cooling beds. During model processing, it was crucial to accurately reproduce the physical dimensions, structure, and moving parts of the equipment to ensure consistency between the model and the actual equipment's form and functional attributes, thus laying the foundation for the realism of subsequent 3D simulations.

[0112] The roller conveyor shown here is a segment of a unit length; the actual roller conveyor is composed of several unit-length roller conveyors spliced ​​together. In logistics simulation, disassembling the roller conveyor into unit-length modules and reconstructing the actual roller conveyor by splicing them together is a common simplification strategy that balances simulation efficiency and model realism, achieving a balance between accuracy and efficiency while ensuring consistency between physics and logic.

[0113] In reality, the length of roller conveyors can range from several meters to tens of meters. If each roller is modeled according to its actual dimensions (e.g., setting parameters individually for each roller), the complexity and computational load will increase significantly. By using unit lengths (e.g., 1 meter, 2 meters) as basic modules, repetitive modeling work can be reduced, and the simulation speed can be improved.

[0114] Since the size, length, and other parameters of each unit module are consistent, there is no need to set connection rules between modules during simulation, thus avoiding the breakage of material conveying logic due to module splitting.

[0115] This method is particularly suitable for roller conveyor lines composed of standardized components, which are ideal for billet exit roller conveyors. It allows for the rapid construction of multiple roller conveyors, and the length of the exit roller conveyor can be adjusted by adding or removing unit length modules. If the actual roller conveyor has other special designs, it can be spliced ​​together by combining customized unit modules and standardized modules, retaining the advantages of simplification while covering special scenarios.

[0116] The three-dimensional model of the cooling bed consists of a static part and a dynamic part, which correspond to the fixed structure and motion execution parts of the cooling bed, respectively. The two work together to realize the functions of cooling, conveying and temporarily storing the billet.

[0117] The static part serves as the fixed support and positioning structure of the cooling bed, and does not participate in movement. Its main functions are load-bearing, guiding, protection, and providing a motion reference for the dynamic parts. The modeling accuracy of the static part directly affects the accuracy of the dynamic component's motion boundaries and the realism of the billet's material flow path. Attention must be paid to the dimensions and coordinates of the static part to ensure that the static boundaries do not conflict with the dynamic component's motion trajectory, that the coordinates of the static part match those of other equipment on the production line, and that the billet's material flow path is continuous.

[0118] The dynamic component is the core of the cooling bed, enabling the movement, cooling, and conveying of the billet. Through periodic motion, it shifts the billet, ensuring uniform cooling and ultimately conveying it to the next process. Its motion parameters, such as speed, stroke, and cycle time, directly affect the cooling bed's material flow efficiency and cooling effect.

[0119] The static and dynamic parts of the 3D model of the cooling bed need to be separated and then reassembled to achieve independent movement of the dynamic part. In the existing modeling and simulation tools, the dynamic part of the cooling bed can be set as a new intelligent agent, while the static part can be directly placed in the model.

[0120] Subsequently, to address the issues of large file sizes and incompatibility with simulation platforms associated with the native 3D model in STEP and IGES formats, a lightweight model processing technique was employed to optimize the model and convert it into a DAE intermediate format compatible with the simulation platform. This process required significantly compressing the model file size while preserving the key 3D structural information of the equipment, thereby reducing the loading pressure on the simulation environment.

[0121] After the model is imported into the simulation environment, its accuracy needs to be dynamically adjusted according to actual requirements: the position and height of the billet being ejected must be consistent with the billet ejection roller conveyor, and the coordinate position of the steel pusher must also be precisely set. Appropriately increasing the model accuracy ensures the accuracy of the simulation data. For visualization scenarios such as overall layout display and overall process demonstration, the model and animation accuracy of non-critical parts can be appropriately reduced to decrease the loading pressure on the simulation environment and avoid redundant data consuming computing resources. This on-demand adjustment method ensures both simulation calculation efficiency and maintains the visual animation expressiveness of the equipment movement trajectory and billet flow process, allowing users to clearly and intuitively observe the operating status of the logistics system. The effect is as follows: Figure 5 The three-dimensional simulation view of the continuous casting billet is shown in the figure.

[0122] Ultimately, the optimized visualization simulation model (i.e., the 3D model) can present some key indicators in real time, providing an intuitive and data-supported basis for decisions such as billet optimization, equipment configuration adjustment, and work process improvement, effectively reducing decision-making risks and improving the overall operational efficiency of billet logistics.

[0123] In one embodiment, step 500 includes: Receive input data from the front end; The input data is input into the continuous casting billet simulation model to obtain the output result of the continuous casting billet simulation model, and the running state of the three-dimensional model is adjusted based on the output result.

[0124] In one embodiment, after step 300, the method further includes: The output results of the continuous casting billet simulation are evaluated for abnormality based on the preset simulation result evaluation index.

[0125] To further illustrate this solution, this application provides an application example of a multi-agent-based continuous casting billet simulation method. In this application example, the method includes: S1: Continuous casting process mechanism model analysis. Analyze the continuous casting billet output process, key processes, and process routes; set simulation indicators.

[0126] S2: Simulation platform model and process algorithm construction. Based on the continuous casting process flow, establish equipment and process simulation models, establish internal simulation logic rules for equipment / processes, establish logistics relationship control algorithms between processes, and establish transportation equipment scheduling algorithms.

[0127] S3: Construction of 3D Models for Simulation Platform. Establish 3D models of continuous casting billet conveyors, transverse conveyors, baffles, marking machines, cooling beds, etc., and create simulation animation processes.

[0128] S4: Simulation platform interface design. Input / output parameters and database construction.

[0129] S5: Design of simulation platform result analysis tools. This includes setting simulation result evaluation metrics and developing comprehensive analysis tools.

[0130] Step S1 includes: This paper analyzes the continuous casting billet removal process and extracts relevant information, including key process parameters, processing steps, and timeframes. Based on the continuous casting process flow, simulation models of the equipment and processes are established, along with internal simulation logic rules. The parameter ranges and input / output content for the simulation calculation platform interface are defined. Relevant indicators and ranges for evaluating the simulation results are set.

[0131] The continuous casting process mechanism model analysis includes the entire dynamic flow of the billet from its generation on the continuous casting machine to its entry into the heating furnace. This process needs to be analyzed by combining physical processes and logical rules. The main equipment includes the cutting and conveying tracks, lifting baffles, transverse zone roller conveyors, marking machines, steel lifting machines, steel pushing machines, cooling beds, and collection beds. The main equipment is set as intelligent agents; through interaction and cooperation between these agents, resources are rationally allocated. When the logistics system needs to be expanded or upgraded, only the corresponding intelligent agents need to be added or modified.

[0132] Step S2 includes: Based on the continuous casting billet output process, the main parts of the model are analyzed and extracted, and internal simulation logic rules for billet casting, billet output track, transverse traverse zone, cooling bed, and hot conveying are constructed. Furthermore, the internal logic and overall relationship control of multiple intelligent agents such as the marking machine, steel lifting machine, and steel pushing machine in the transverse traverse zone are further subdivided.

[0133] The specific construction of the billet casting module is as follows: The billet has specific dimensional parameters such as length, width, and thickness, which directly affect its interaction logic with other equipment in the logistics system. In the simulation scenario, the entire dynamic process of billet generation (corresponding to the billet output rhythm of the continuous casting machine), transportation (through equipment such as roller conveyors and overhead cranes), temporary storage (in areas such as cooling beds and buffer zones), and subsequent processing (such as length cutting and marking) are the core elements for constructing the continuous casting billet output simulation model.

[0134] The specific construction of the billet production track module is as follows: The billet exit track section primarily generates the cut continuous casting billets according to user requirements. Users can adjust the billet exit track length, speed, and other parameters in this module. Its length covers the area from the post-cutting roller conveyor to the entrance of the transverse transfer zone. Multi-strand continuous casting machines connect to multiple billet exit tracks, and the simulation should be able to change the number of flows on each track. The billet exit track is not isolated; it needs to coordinate deeply with the casting billet and subsequent processes. Furthermore, each billet exit roller conveyor is independent, and the casting speed, billet production time interval, and billet length can be adjusted individually. Inputting relevant parameters into the simulation model will generate the casting billet and begin its transport on the track.

[0135] The construction of the transverse movement module is specifically as follows: After the billet enters the transverse transfer zone, it stops for a series of processes including marking, lifting, and pushing. The marking machine mainly marks the billet, and then the billet is moved to the next process by lifting and pushing. The billet enters the transverse transfer zone through lifting baffle 1, moves forward and stops in front of lifting baffle 2. After lifting baffle 2 descends, the marking machine starts. There are multiple marking machines. When there are multiple billets queuing in the transverse transfer zone, they are distributed as evenly as possible according to the number of billets and the number of marking machines, and the marking is done in the order of stopping positions to minimize the total marking time for a batch of billets. After the marking machine finishes working on a billet, the billet is lifted up by the lifting machine and placed on the upper storage track to wait. If the marking is not completed, the lifting device remains on standby. After all the billets in a batch have been marked and lifted onto the storage track, the pushing machine starts pushing the billets out for storage, ready to enter the cooling bed.

[0136] The pusher mechanism facilitates the transition of billet transportation from linear transport to lateral distribution. When the front end of the billet reaches the target position, the pusher automatically resets, awaiting the next batch of billets. If the target space is occupied by other processes (e.g., a steel lifting machine is lifting steel), the simulation needs to set the waiting logic for the pusher. Similarly, if the steel pushing machine is in the process of pushing steel or returning, the simulation also needs to set the waiting logic for other equipment to avoid collisions between the operating spaces of different devices.

[0137] The construction of the cooling bed module is specifically as follows: The cooling bed is the core equipment connecting the continuous casting machine and the subsequent steel rolling process. The cooling bed is used to transport and turn the billet, so that the billet is cooled evenly and to prevent the billet from deforming. After the billet enters the cooling bed, it moves forward at a set distance through the fixed plate and the movable plate. After reaching the end point, it leaves the cooling bed and is collected and transferred to the collection bed in groups by the overhead crane.

[0138] In logistics simulation software, the core components of the cooling bed must be reproduced according to the actual structure to ensure accurate motion logic. The modeling of the stepping beam's rising, translating, falling, and retracting cyclical motion trajectory must match the length of the casting billet to avoid billet collisions.

[0139] When the inlet roller conveyor detects the billet and there is available space on the cooling bed, the inlet conveyor is activated. If the cooling bed is at full load, the billet is temporarily stored on the roller conveyor, and the cooling bed moves the billet according to a stepping cycle. When the outlet roller conveyor is available and the billet has cooled to the required level and reaches the outlet, the outlet conveyor is activated. The billets leaving the cooling bed are temporarily stored together and transported to the collection bed after a specified quantity is reached.

[0140] Construct a hot conveying module. The hot conveying section involves complex processes, often including double cutting, secondary marking, rotation, billet collection, and billet separation. This part can be appropriately simplified or components from the transverse movement area can be reused.

[0141] Step S3 includes: Based on the constructed logistics simulation model, the 3D solid model of the equipment is extracted using professional industrial design software. The reusable components are broken down into unit formats. The native 3D format is converted into an intermediate format compatible with the simulation platform using model lightweighting technology. After being imported into the simulation environment, the units are arranged and combined in a cell-like manner. The size and position of all models are adjusted to adapt to the simulation. While ensuring the efficiency of simulation calculation, the visual animation expressiveness is maintained, providing intuitive decision support.

[0142] Step S4 includes: The inputs include billet output variables, transverse zone variables, and other parameters. Billet output variables include the number of continuous casting machine flows, continuous casting machine drawing speed, continuous casting billet length, number of billets per flow, distance of the billet from the cutting endpoint to the lifting baffle, and linear speed of the billet after cutting and on the conveyor rollers. Transverse zone variables include the time required for the lifting baffle to descend, the time for the billet to enter the transverse zone from the billet output rollers, the number of marking machines, the start time of each marking machine, the time for the marking machine to detect descaling and resetting, the time required for the pusher to push the steel, and the time required for the lifting machine to lift the steel. Other parameters include the distance of each step of the cooling bed, the time required for the cooling bed to return to its original position after one revolution, the distance the collecting bed moves, and the length of the collecting bed.

[0143] like Figure 6 As shown, once the data input for the interactive interface is complete, the model begins to run, and the parameters are passed to the main interface for display. At the same time, the parameters from the main interface are passed to modules such as the billet discharge track, lifting baffle 1, lifting baffle 2, marking machine, steel lifting machine, steel pushing machine, cooling bed, and collecting bed, and each part is initialized and modified.

[0144] After the simulation is complete, each module will input the statistical dataset into the main interface, perform calculations and processing, and then output the results.

[0145] Step S5 includes: The statistics include charts displaying the billet time interval, billet residence time on the walking beam cooling bed, operating time of each piece of equipment, and the percentage of each piece of equipment in operation, all presented in the simulation model. Users can use these charts to determine the billet rhythm and equipment utilization rate, enabling data collection, processing, and visualization, thus providing data support for business decisions.

[0146] The billet enters the cutting and conveying track, and as the lifting baffle descends, it enters the transverse roller conveyor. Here, the marking machine, steel lifting machine, and steel pushing machine complete the marking, lifting, and pushing processes. It then enters the cooling bed, cools, and finally enters the collection bed. The main objects, such as the billet exit roller conveyor, lifting baffle, marking machine, steel lifting machine, steel pushing machine, and cooling bed, are set as intelligent agents. Each intelligent agent has its own attributes and internal logic, encapsulated in a model library. Different scenarios allow for rapid invocation of library methods for simulation model construction, eliminating the need for repetitive development. When a new business module is added, only the corresponding intelligent agent needs to be added and interaction rules defined; the entire simulation model does not need to be rebuilt.

[0147] Compared to traditional software simulation, this method offers advantages such as faster model building, higher efficiency, greater versatility and reusability, effectively reducing the manpower and material resources required for verifying new or modified technical solutions. Furthermore, the logistics simulation model established by this method can effectively verify and optimize new or modified continuous casting billet production technologies, reducing design errors that may be overlooked or difficult to detect during the design process, such as design errors in the capacity of new or modified continuous casting billet production and logistics conflicts.

[0148] From a software perspective, in order to improve the efficiency of continuous casting billet simulation while ensuring its reliability, this application provides an embodiment of a multi-agent-based continuous casting billet simulation device for implementing all or part of the aforementioned multi-agent-based continuous casting billet simulation method. See [link to embodiment]. Figure 7 The multi-agent-based continuous casting billet simulation device specifically includes the following components: Module 01 is used to acquire information about the continuous casting billet exit process. Module 02 is used to build a continuous casting billet simulation model based on the continuous casting billet output process information and a preset model library. The continuous casting billet output simulation model includes: a billet module, a billet output track module, a transverse movement zone module, a cooling bed module, a hot delivery module, and their respective simulation logic rules. The preset model library includes: a cutting and conveying track intelligent body, a lifting baffle intelligent body, a transverse movement zone roller conveyor intelligent body, a marking machine intelligent body, a steel lifting machine intelligent body, a steel pushing machine intelligent body, a cooling bed intelligent body, and a collection bed intelligent body. Simulation module 03 is used to complete the simulation of continuous casting billet production based on the continuous casting billet production simulation model.

[0149] The embodiments of the multi-agent-based continuous casting billet simulation device provided in this specification can be used to execute the processing flow of the embodiments of the multi-agent-based continuous casting billet simulation method described above. Its functions will not be repeated here, but can be referred to the detailed description of the embodiments of the multi-agent-based continuous casting billet simulation method described above.

[0150] As described above, the multi-agent-based continuous casting billet simulation method and apparatus provided in this application constructs a continuous casting billet process, logistics line and scheduling rule model library by secondary programming development of the existing software built-in toolbox, and deeply integrates equipment constraints (such as conveyor belt path and conveyor belt speed) and process rules (such as process sequence and process equipment duration) in the continuous casting billet scenario to construct a simulation logistics model.

[0151] This invention reduces design errors that may be overlooked or difficult to detect during the design process, such as design errors and logistics conflicts in the construction or renovation of continuous casting billet production capacity. At the same time, because the method is based on multi-agent technology, it can quickly call model library methods for simulation model construction. Compared with commonly used self-developed software simulation, it has the characteristics of fast model building speed, high efficiency, strong universality and applicability, and high reusability, effectively reducing the human and material resources invested in the verification process of new or renovated technical solutions.

[0152] This invention relates to a multi-agent continuous casting billet discharge simulation system. It establishes simulation models of the billet, discharge track, lifting baffle, marking machine, lifting machine, pushing machine, and walking beam cooling bed based on multiple agents. Each individual device is composed of multiple components and possesses independence and autonomy, capable of autonomous reasoning, planning, and selecting appropriate strategies. Furthermore, the multi-agent system, through the coordination of these agents, can help solve problems such as blockage during continuous casting billet discharge. It offers advantages such as autonomy, distribution, and coordination.

[0153] Application scenarios can be quickly built using encapsulation modules as needed, requiring minimal technical expertise. Staff can easily construct simulation models of the continuous casting billet discharge process, significantly reducing time and manpower costs. Simulation technology analyzes the material flow system of multi-strand continuous casting machines, guiding billet discharge design and optimizing the billet discharge area. This greatly aids in the promotion and marketing of square and round billet continuous casting machines. Furthermore, for factory design projects, it streamlines and simplifies the overall logistics of the steelmaking workshop, improving management and ultimately enhancing production efficiency and capacity.

[0154] Figure 8 This is a schematic diagram of the physical structure of an electronic device provided in an embodiment of the present invention, such as... Figure 8 As shown, the electronic device includes: a memory 801, a processor 802, and a computer program stored in the memory 801 and executable on the processor 802. When the processor 802 executes the computer program, it implements the following method: Obtain information on the continuous casting billet exit process; Based on the continuous casting billet exit process information and the preset model library, a continuous casting billet exit simulation model is established. The continuous casting billet exit simulation model includes: billet module, billet exit track module, transverse transfer zone module, cooling bed module, hot delivery module and their respective simulation logic rules. The preset model library includes: cutting and conveying track intelligent body, lifting baffle intelligent body, transverse transfer zone roller conveyor intelligent body, marking machine intelligent body, steel lifting machine intelligent body, steel pushing machine intelligent body, cooling bed intelligent body and collection bed intelligent body. Based on the continuous casting billet simulation model, the continuous casting billet simulation was completed.

[0155] This embodiment discloses a computer program product, which includes a computer program that, when executed by a processor, implements the following method: Obtain information on the continuous casting billet exit process; Based on the continuous casting billet exit process information and the preset model library, a continuous casting billet exit simulation model is established. The continuous casting billet exit simulation model includes: billet module, billet exit track module, transverse transfer zone module, cooling bed module, hot delivery module and their respective simulation logic rules. The preset model library includes: cutting and conveying track intelligent body, lifting baffle intelligent body, transverse transfer zone roller conveyor intelligent body, marking machine intelligent body, steel lifting machine intelligent body, steel pushing machine intelligent body, cooling bed intelligent body and collection bed intelligent body. Based on the continuous casting billet simulation model, the continuous casting billet simulation was completed.

[0156] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the following method: Obtain information on the continuous casting billet exit process; Based on the continuous casting billet exit process information and the preset model library, a continuous casting billet exit simulation model is established. The continuous casting billet exit simulation model includes: billet module, billet exit track module, transverse transfer zone module, cooling bed module, hot delivery module and their respective simulation logic rules. The preset model library includes: cutting and conveying track intelligent body, lifting baffle intelligent body, transverse transfer zone roller conveyor intelligent body, marking machine intelligent body, steel lifting machine intelligent body, steel pushing machine intelligent body, cooling bed intelligent body and collection bed intelligent body. Based on the continuous casting billet simulation model, the continuous casting billet simulation was completed.

[0157] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0158] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0159] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0160] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0161] In the description of this specification, the references to terms such as "an embodiment," "a specific embodiment," "some embodiments," "for example," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0162] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A simulation method for continuous casting billet production based on multi-agent systems, characterized in that, include: Obtain information on the continuous casting billet exit process; Based on the continuous casting billet exit process information and the preset model library, a continuous casting billet exit simulation model is established. The continuous casting billet exit simulation model includes: billet module, billet exit track module, transverse transfer zone module, cooling bed module, hot delivery module and their respective simulation logic rules. The preset model library includes: cutting and conveying track intelligent body, lifting baffle intelligent body, transverse transfer zone roller conveyor intelligent body, marking machine intelligent body, steel lifting machine intelligent body, steel pushing machine intelligent body, cooling bed intelligent body and collection bed intelligent body. Based on the continuous casting billet simulation model, the continuous casting billet simulation was completed.

2. The simulation method for continuous casting billet production based on multi-agent technology according to claim 1, characterized in that, The step of simulating continuous casting billet production based on the continuous casting billet production simulation model includes: Acquire input data, which includes: billet output variables, transverse shift zone variables, and other parameters; The input data is input into the continuous casting billet simulation model to obtain the output results of the continuous casting billet simulation model. The output results include: billet discharge time interval, billet residence time on the walking beam cooling bed, time of operation of each equipment, and state percentage of each equipment.

3. The continuous casting billet simulation method based on multi-agent system according to claim 1, characterized in that, After establishing the continuous casting billet simulation model, the following is also included: Establish a three-dimensional model corresponding to the continuous casting billet simulation model, and display the three-dimensional model on the front end; Based on the continuous casting billet simulation model and the three-dimensional model, the continuous casting billet simulation is completed.

4. The simulation method for continuous casting billet production based on multi-agent technology according to claim 3, characterized in that, Also includes: Receive input data from the front end; The input data is input into the continuous casting billet simulation model to obtain the output result of the continuous casting billet simulation model, and the running state of the three-dimensional model is adjusted based on the output result.

5. The simulation method for continuous casting billet production based on multi-agent technology according to claim 1, characterized in that, Also includes: The output results of the continuous casting billet simulation are evaluated for abnormality based on the preset simulation result evaluation index.

6. The simulation method for continuous casting billet production based on multi-agent technology according to claim 1, characterized in that, The continuous casting billet output process information includes: key process parameters, multiple processing steps, and the duration of each processing step.

7. The simulation method for continuous casting billet production based on multi-agent technology according to claim 1, characterized in that, The billet module is used to simulate billet casting; The billet exit track module is used to simulate the process of the billet entering, transporting and exiting the billet in the billet exit track; The transverse movement module is used to simulate the process of the billet performing the transverse movement process, which includes: spraying marking, lifting steel and pushing steel; The cooling bed module is used to simulate the process of the billet entering, storing, cooling and exiting the cooling bed; The hot delivery module is used to simulate the process of secondary marking, billet collection, rotation, and furnace loading of the billet.

8. A simulation device for continuous casting billet unloading based on multi-agent technology, characterized in that, include: The acquisition module is used to acquire information about the continuous casting billet exit process. The construction module is used to establish a continuous casting billet simulation model based on the continuous casting billet exit process information and a preset model library. The continuous casting billet exit simulation model includes: a billet module, a billet exit track module, a transverse movement zone module, a cooling bed module, a hot delivery module, and their respective simulation logic rules. The preset model library includes: a cutting and conveying track intelligent entity, a lifting baffle intelligent entity, a transverse movement zone roller conveyor intelligent entity, a marking machine intelligent entity, a steel lifting machine intelligent entity, a steel pushing machine intelligent entity, a cooling bed intelligent entity, and a collection bed intelligent entity. The simulation module is used to complete the simulation of continuous casting billet production based on the continuous casting billet production simulation model.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the multi-agent-based continuous casting billet simulation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the multi-agent-based continuous casting billet simulation method according to any one of claims 1 to 7.

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