Production control method, device, equipment and storage medium for hot rolling production line

Abstract

The application discloses a hot rolling production line production control method, device, equipment and storage medium, and the hot rolling production line comprises a heating furnace; the method comprises the following steps: in the running process of the hot rolling production line, if it is detected that the hot rolling production line is abnormal or after an interval preset period, running data of the hot rolling production line is acquired; the running data is processed based on a multi-objective optimization algorithm to obtain optimized control parameters of the hot rolling production line; wherein optimization objectives of the multi-objective optimization algorithm comprise minimization of total fuel consumption, minimization of deviation between actual in-furnace time of a billet in the heating furnace and a preset optimal in-furnace time, maximization of in-furnace temperature uniformity of the heating furnace and maximization of upstream and downstream process matching degree of the hot rolling production line; optimization variables of the multi-objective optimization algorithm comprise predetermined step time of the billet and multi-section set temperature of the heating furnace; and the production of the hot rolling production line is controlled based on the optimized control parameters. The application solves the technical problem of high energy consumption of the hot rolling production line.

Description

Technical Field

[0001] This invention belongs to the field of hot rolling technology, and particularly relates to a production control method, device, equipment, and storage medium for a hot rolling production line. Background Technology

[0002] In hot rolling production lines, hot charging and hot delivery (HCR / DHCR) is a key technology for steel companies to achieve energy conservation, reduce consumption, shorten production cycles, and improve production efficiency. In this process, the heating furnace, as a buffer and coupling link connecting continuous casting and rolling, directly affects the smoothness of the entire process and the level of energy consumption. Traditional heating furnace control modes are mostly "static" scheduling based on fixed rhythms or empirical rules, that is, after the steel billet enters the furnace, it is heated according to a preset step rhythm and heating curve.

[0003] However, in actual production, the upstream continuous casting process can experience changes in billet output rhythm due to events such as tundish replacement, casting speed fluctuations, or casting interruptions, while the downstream rolling process can also experience interruptions in rolling rhythm due to roll changes, malfunctions, and other reasons. Traditional static scheduling models cannot adapt to such strong dynamic disturbances, often leading to the following problems: (1) Increased energy consumption: When the downstream rolling mill is delayed, the billet in the furnace is overheated, resulting in energy waste; when the upstream billet arrives faster, the billet is underheated, affecting product quality.

[0004] (2) Production blockage: The management of billet queues in the furnace is chaotic, which may lead to "bill collision" or uneven utilization of space in the furnace, affecting the normal entry of continuous casting billets into the furnace or the normal output of rolled steel.

[0005] (3) Quality risks: If the billet is in the furnace for too long or too short a time, or if the furnace temperature is uneven, it will directly affect the structure and properties of the rolled products. Summary of the Invention

[0006] This invention provides a production control method, apparatus, equipment, and storage medium for a hot rolling production line, which solves the technical problem of high energy consumption in hot rolling production lines.

[0007] In a first aspect, embodiments of the present invention provide a production control method for a hot rolling production line, the hot rolling production line including a heating furnace; the method includes: during the operation of the hot rolling production line, if an abnormality is detected in the hot rolling production line or after a preset interval, acquiring the operating data of the hot rolling production line; processing the operating data based on a multi-objective optimization algorithm to obtain optimized control parameters for the hot rolling production line; wherein, the optimization objectives of the multi-objective optimization algorithm include minimizing total fuel consumption, minimizing the deviation between the actual furnace time of the billet and the preset optimal furnace time, maximizing the furnace temperature uniformity of the heating furnace, and maximizing the matching degree between the upstream and downstream processes of the hot rolling production line; the optimization variables of the multi-objective optimization algorithm include the predetermined stepping time of the billet and the multi-stage set temperature of the heating furnace; the boundary constraints of the multi-objective optimization algorithm include the furnace time constraint of the billet, the furnace exit temperature constraint of the billet, and the action frequency constraint of the stepping beam of the heating furnace; and controlling the production of the hot rolling production line based on the optimized control parameters.

[0008] In conjunction with the first aspect of the present invention, in some embodiments, it further includes: if a roll changing or equipment failure is detected in the hot rolling production line, it is determined that the hot rolling production line is abnormal.

[0009] In conjunction with the first aspect of the present invention, in some embodiments, the calculation index of the temperature uniformity inside the heating furnace includes the temperature uniformity of the steel billet in the length direction, the temperature uniformity of the steel billet in the width direction, and the temperature uniformity of the steel billet in the thickness direction when the steel billet exits the heating furnace.

[0010] In conjunction with the first aspect of the present invention, in some embodiments, the calculation indicators for the matching degree of the upstream and downstream processes of the hot rolling production line include time coordination matching degree, capacity adaptation matching degree, and process parameter compatibility matching degree.

[0011] In conjunction with the first aspect of the present invention, in some embodiments, the furnace time constraint of the billet is that the furnace time of the billet is within the allowable range of the furnace time of the billet; the furnace exit temperature constraint of the billet is that the furnace exit temperature of the billet is within the allowable range of the furnace exit temperature of the billet; and the operating frequency constraint of the walking beam of the heating furnace is that the operating frequency of the walking beam is less than a preset operating frequency threshold.

[0012] In conjunction with the first aspect of the present invention, in some embodiments, the step of processing the operating data based on a multi-objective optimization algorithm to obtain the optimized control parameters of the hot rolling production line includes: initializing the hyperparameters and initial solution group of the multi-objective optimization algorithm; the initial solution group includes multiple sets of candidate solutions, each set of candidate solutions including a predetermined step time for the billet and multiple set temperatures of the heating furnace; processing the operating data through the multi-objective optimization algorithm to obtain the index prediction results corresponding to each set of candidate solutions; the index prediction results include total fuel consumption, the deviation between the actual furnace time of the billet in the heating furnace and the preset optimal furnace time, the furnace temperature uniformity of the heating furnace, and the matching degree of upstream and downstream processes of the hot rolling production line; determining the fitness value of each set of candidate solutions based on the index prediction results corresponding to each set of candidate solutions; and iteratively optimizing the solution group of the multi-objective optimization algorithm based on the fitness values ​​of each set of candidate solutions until a preset iteration termination condition is met to obtain the optimized control parameters.

[0013] In conjunction with the first aspect of the present invention, in some embodiments, the preset cycle is 5 min to 10 min.

[0014] Secondly, embodiments of the present invention provide a production control device for a hot rolling production line, the hot rolling production line including a heating furnace; the device includes: a data acquisition unit, used to acquire operating data of the hot rolling production line if an abnormality is detected in the hot rolling production line or after a preset interval during the operation of the hot rolling production line; an optimization unit, used to process the operating data based on a multi-objective optimization algorithm to obtain optimized control parameters for the hot rolling production line; wherein, the optimization objectives of the multi-objective optimization algorithm include minimizing total fuel consumption, minimizing the deviation between the actual furnace time of the billet and the preset optimal furnace time, maximizing the furnace temperature uniformity of the heating furnace, and maximizing the matching degree between the upstream and downstream processes of the hot rolling production line; the optimization variables of the multi-objective optimization algorithm include the predetermined stepping time of the billet and the multi-stage set temperature of the heating furnace; the boundary constraints of the multi-objective optimization algorithm include the furnace time constraint of the billet, the furnace exit temperature constraint of the billet, and the action frequency constraint of the stepping beam of the heating furnace; and a control unit, used to control the production of the hot rolling production line based on the optimized control parameters.

[0015] Thirdly, embodiments of the present invention provide 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 method described in any of the first aspects.

[0016] Fourthly, embodiments of the present invention provide a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in any one of the first aspects.

[0017] The one or more technical solutions provided in the embodiments of the present invention achieve at least the following technical effects or advantages: This invention, in its embodiments, acquires operational data of the hot rolling production line during operation if an anomaly is detected or after a preset interval. The operational data is then processed using a multi-objective optimization algorithm to obtain optimized control parameters for the hot rolling production line. The optimization objectives of the multi-objective optimization algorithm include minimizing total fuel consumption, minimizing the deviation between the actual furnace time of the billet and the preset optimal furnace time, maximizing the uniformity of the furnace temperature, and maximizing the matching degree between upstream and downstream processes of the hot rolling production line. The optimization variables of the multi-objective optimization algorithm include the predetermined stepping time of the billet and the multiple set temperatures of the furnace. The boundary constraints of the multi-objective optimization algorithm include constraints on the billet's furnace time, the billet's exit temperature, and the operating frequency of the furnace's walking beam. Based on these optimized control parameters, the production of the hot rolling production line is controlled. After detecting an anomaly in the hot rolling production line or after a preset interval, the operating data of the hot rolling production line will be reacquired and processed based on a multi-objective optimization algorithm to optimize the control strategy of the hot rolling production line. This realizes the adjustment of the control strategy according to the real-time status of the hot rolling production line, which meets the actual needs and avoids energy waste caused by overheating of steel billets in the furnace. Therefore, it reduces the energy consumption of the hot rolling production line.

[0018] Furthermore, the optimized control strategy for the hot rolling production line can avoid billet collisions or uneven utilization of furnace space, thus reducing the possibility of production blockages. Simultaneously, the optimized control strategy can prevent billets from spending too much or too little time in the furnace, and avoid uneven exit temperatures, thereby improving product quality. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0020] Figure 1 This is a flowchart of the production control method for a hot rolling production line in an embodiment of the present invention; Figure 2 This is a functional block diagram of the production control device for the hot rolling production line in an embodiment of the present invention; Figure 3This is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0022] In this invention, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature. Furthermore, the technical solutions of the various embodiments can be combined with each other, but only on the basis of being achievable by those skilled in the art. If the combination of technical solutions is contradictory or impossible to implement, such a combination of technical solutions should be considered non-existent and not within the scope of protection claimed by this invention.

[0023] This invention provides a production control method for a hot rolling production line, which includes a heating furnace; see reference. Figure 1 As shown, the method includes the following steps S101 to S103: S101: During the operation of the hot rolling production line, if an abnormality is detected in the hot rolling production line or after a preset interval, the operation data of the hot rolling production line is obtained.

[0024] In some embodiments, the production control method for hot rolling production lines further includes: if a roll changing or equipment failure is detected in the hot rolling production line, it is determined that there is an abnormality in the hot rolling production line.

[0025] In some implementations, the preset cycle is 5 min to 10 min.

[0026] S102: The operating data is processed based on a multi-objective optimization algorithm to obtain the optimized control parameters of the hot rolling production line. The optimization objectives of the multi-objective optimization algorithm include minimizing total fuel consumption, minimizing the deviation between the actual time the billet spends in the furnace and the preset optimal time, maximizing the uniformity of the furnace temperature, and maximizing the matching degree between the upstream and downstream processes of the hot rolling production line. The optimization variables of the multi-objective optimization algorithm include the predetermined stepping time of the billet and the multi-stage set temperature of the furnace. The boundary constraints of the multi-objective optimization algorithm include the billet's time in the furnace, the billet's exit temperature, and the operating frequency constraint of the furnace's walking beam.

[0027] It should be noted that optimizing control parameters may include the predetermined stepping time of the billet and the multi-stage set temperature of the heating furnace.

[0028] In some implementations, the calculation indicators for the temperature uniformity inside the heating furnace include the temperature uniformity of the billet in the length direction, the temperature uniformity of the billet in the width direction, and the temperature uniformity of the billet in the thickness direction when the billet exits the heating furnace.

[0029] It should be noted that the temperature uniformity of the billet in the length direction can be characterized by the temperature deviation at each point in the length direction, the temperature uniformity of the billet in the width direction can be characterized by the temperature deviation at each point in the width direction, and the temperature uniformity of the billet in the thickness direction can be characterized by the temperature deviation at each point in the thickness direction.

[0030] In some implementations, the calculation indicators for the matching degree of upstream and downstream processes of the hot rolling production line include time coordination matching degree, capacity adaptation matching degree, and process parameter compatibility matching degree.

[0031] Specifically, the calculation of the matching degree of upstream and downstream processes in the hot rolling production line can refer to formula (1), where M is the matching degree of upstream and downstream processes, and the value range is [0, 1]. The closer M is to 1, the higher the matching degree of upstream and downstream processes and the better the scheduling and coordination. The closer M is to 0, the lower the matching degree and the easier it is for processes to disconnect (such as downstream equipment being idle after the billet is taken out of the furnace, or downstream equipment waiting for the billet). This represents the weighting coefficient, which can be adjusted according to actual production priorities. The default value is 1 / 3, but a more reasonable weight can be determined through analytic hierarchy process (AHP) or genetic algorithm optimization. t For time-coordination matching degree, M c To ensure a good match between production capacity and performance, M p For process parameter compatibility and matching degree.

[0032]

[0033] Specifically, the calculation of the time coordination matching degree can be referred to formula (2). The core of the time coordination matching degree is to solve the connection problem between the billet tapping time and the downstream process readiness time, while taking into account the coordination between the upstream steel charging rhythm and the furnace scheduling, so as to avoid "blockage at the front and emptiness at the back". n is the total number of billets to be scheduled in the furnace (consistent with the optimization object). The theoretical tapping time for the i-th billet (calculated by the furnace scheduling model, which is related to the billet's time in the furnace and the heating rhythm); The ready time for the downstream process (such as the rolling mill) corresponding to the i-th billet is calculated by combining the processing cycle of the downstream equipment, the processing end time of the previous billet, and the upstream loading time to ensure the rhythm coordination of the entire process. The time coordination matching degree adopts "relative time difference" instead of the traditional "absolute time difference" to avoid quantitative deviations caused by different billet specifications and processing cycle differences. At the same time, through averaging, it takes into account the time matching effect of all billets, rather than a single billet.

[0034]

[0035] Specifically, the capacity matching degree can be calculated by referring to formula (3). The capacity matching degree breaks through the traditional limitation of only considering time, and combines the capacity supply and demand of upstream and downstream processes to avoid the situation of "mismatch between furnace capacity and downstream processing capacity" (such as the batch of steel billets coming out of the furnace and the downstream equipment being unable to process them in time, resulting in accumulation; or insufficient furnace capacity and idle downstream equipment). The effective steel output capacity of the heating furnace per unit time (calculated based on billet specifications, furnace time, and furnace loading, i.e., the total weight / quantity of billets that can be output per unit time). This refers to the effective processing capacity per unit time of downstream processes (such as rolling lines) (related to the number of downstream equipment, processing speed, and equipment failure rate). The capacity deviation penalty coefficient is set at 0.05 to 0.1 (empirical values ​​range from 0.05 to 0.1; the larger the deviation, the stronger the penalty, ensuring a rapid decrease in capacity matching). The capacity matching degree introduces a combination of "capacity ratio" and "deviation penalty item," which not only reflects the relative compatibility of upstream and downstream capacity but also strictly punishes capacity deviation. At the same time, it is linked to the capacity output of furnace scheduling to achieve capacity synergy between "furnace scheduling and downstream processing," avoiding overall inefficiency caused by local optimization.

[0036]

[0037] Specifically, the calculation of the process parameter compatibility can be referenced by formula (4). The process parameter compatibility considers the process parameters (core is the furnace temperature) after the billet is taken out of the furnace and the process requirements of the downstream process to avoid rework and increased energy consumption due to incompatibility of process parameters, while also considering the uniformity constraint of furnace temperature. The actual furnace exit temperature of the i-th steel billet; The optimal process temperature required for the downstream process (such as rolling) of the i-th billet (determined based on the billet material and rolling process); , These are the upper and lower limits of the allowable range of billet tapping temperature, respectively. Let be the furnace temperature uniformity coefficient of the i-th steel billet ( The more uniform the temperature, The closer it is to 1, the better (calculated from the uniformity of temperature inside the furnace); the process parameter compatibility matching degree links "furnace outlet temperature matching" and "furnace temperature uniformity", which not only ensures the compatibility of upstream and downstream process parameters, but also echoes the existing temperature constraints in the model, avoiding isolated optimization of each objective; at the same time, through the normalization of the allowable temperature range, the quantitative deviation caused by the difference in process requirements of different steel billets is eliminated.

[0038]

[0039] In some implementations, the billet's furnace dwell time is constrained to be within the allowable range; the billet's furnace exit temperature is constrained to be within the allowable range; and the walking beam's operating frequency in the heating furnace is constrained to be less than a preset operating frequency threshold.

[0040] In some implementations, the operating data is processed based on a multi-objective optimization algorithm to obtain optimized control parameters for the hot rolling production line. This includes: initializing the hyperparameters and initial solution group of the multi-objective optimization algorithm; the initial solution group includes multiple candidate solutions, each including a predetermined step time for the billet and multiple set temperatures for the heating furnace; processing the operating data using the multi-objective optimization algorithm to obtain the index prediction results corresponding to each candidate solution in the multiple candidate solutions; the index prediction results include total fuel consumption, the deviation between the actual furnace time of the billet and the preset optimal furnace time, the furnace temperature uniformity, and the matching degree of upstream and downstream processes of the hot rolling production line; determining the fitness value of each candidate solution in the multiple candidate solutions based on the index prediction results corresponding to each candidate solution in the multiple candidate solutions; and iteratively optimizing the solution group of the multi-objective optimization algorithm based on the fitness values ​​of each candidate solution in the multiple candidate solutions until a preset iteration termination condition is met to obtain the optimized control parameters.

[0041] S103: Control the production of the hot rolling production line based on optimized control parameters.

[0042] It should be noted that the embodiments of the present invention can solve the problems of high energy consumption, low efficiency, and high quality risk caused by the inability of traditional static scheduling modes to adapt to dynamic changes in production. The production control method for hot rolling production lines provided by the embodiments of the present invention can be applied to the dynamic load scheduling system of heating furnaces under hot charging and hot delivery conditions of steel billets. The system can include a data interaction interface, a central processing unit, and an instruction issuance module. The system constructs a multi-objective optimization scheduling model and dynamically calculates the optimal scheduling scheme for each steel billet in the furnace based on a rolling time-domain optimization mechanism to adapt to dynamic changes in production. Regarding the data interaction interface, it is implemented by acquiring the operating data of the hot rolling production line in real time from the continuous casting secondary system and the rolling line secondary system through a standard industrial communication protocol (such as OPC UA). The operating data includes continuous casting speed, slab number, slab temperature, slab position, rolling rhythm, and mill status. When an abnormality occurs in the upstream continuous casting (such as speed reduction or interruption of casting) or a fault occurs in the downstream rolling mill, the system can respond quickly, trigger a recalculation process, and issue an updated scheduling scheme to the lower-level control system. The system acquires data in real time from the MES, continuous casting L2 system, and rolling line L2 system via data interaction interfaces. More specifically, the operational data includes: from continuous casting: planned casting number, flow number, slab ID, steel grade, cross-sectional dimensions, casting speed, cutting length, actual billet exit time, and slab surface temperature (if available); from the rolling line: information from the rolling planning unit, the ID of the next slab to be rolled, rolling rhythm, and the current status of the rolling mill (running / fault / roll change); from the heating furnace: the current position of all steel billets in the furnace, measured temperature values ​​(if multiple temperature measurements are used), and the status of the walking beam. Furthermore, the aforementioned rolling time-domain optimized dynamic rescheduling mechanism operates as follows: the system does not calculate the entire scheduling plan for all steel billets at once, but instead adopts a rolling time-domain control strategy. Every fixed period (e.g., 5 minutes), based on the latest actual production status, the scheduling plan for a predetermined time window (e.g., 1 hour) is re-optimized and adjusted to effectively cope with various random disturbances during the production process.

[0043] This invention, in its embodiments, acquires operational data of the hot rolling production line during operation if an anomaly is detected or after a preset interval. The operational data is then processed using a multi-objective optimization algorithm to obtain optimized control parameters for the hot rolling production line. The optimization objectives of the multi-objective optimization algorithm include minimizing total fuel consumption, minimizing the deviation between the actual furnace time of the billet and the preset optimal furnace time, maximizing the uniformity of the furnace temperature, and maximizing the matching degree between upstream and downstream processes of the hot rolling production line. The optimization variables of the multi-objective optimization algorithm include the predetermined stepping time of the billet and the multiple set temperatures of the furnace. The boundary constraints of the multi-objective optimization algorithm include constraints on the billet's furnace time, the billet's exit temperature, and the operating frequency of the furnace's walking beam. Based on these optimized control parameters, the production of the hot rolling production line is controlled. After detecting an anomalies in the hot rolling production line or after a preset interval, the operating data of the hot rolling production line is reacquired and processed based on a multi-objective optimization algorithm to optimize the control strategy of the hot rolling production line. This allows the control strategy to be adjusted according to the real-time status of the hot rolling production line, meeting actual needs and avoiding energy waste caused by overheating of steel billets in the furnace, thus reducing the energy consumption of the hot rolling production line. In addition, the optimized control strategy of the hot rolling production line can avoid "bill collision" or uneven utilization of furnace space, thus reducing the possibility of production blockage. At the same time, the optimized control strategy of the hot rolling production line can avoid excessively long or short billet time in the furnace and uneven exit temperature, thus improving product quality.

[0044] Based on the same inventive concept, and referring to Figure 2 As shown, this embodiment of the invention provides a production control device 10 for a hot rolling production line, which includes a heating furnace. The production control device 10 includes: a data acquisition unit 110, used to acquire the operating data of the hot rolling production line if an abnormality is detected or after a preset interval during the operation of the hot rolling production line; an optimization unit 120, used to process the operating data based on a multi-objective optimization algorithm to obtain optimized control parameters for the hot rolling production line; wherein, the optimization objectives of the multi-objective optimization algorithm include minimizing total fuel consumption, minimizing the deviation between the actual furnace time of the billet and the preset optimal furnace time, maximizing the uniformity of the furnace temperature, and maximizing the matching degree of the upstream and downstream processes of the hot rolling production line; the optimization variables of the multi-objective optimization algorithm include the predetermined stepping time of the billet and the multi-stage set temperature of the heating furnace; the boundary constraints of the multi-objective optimization algorithm include the furnace time constraint of the billet, the furnace exit temperature constraint of the billet, and the action frequency constraint of the stepping beam of the heating furnace; and a control unit 130, used to control the production of the hot rolling production line based on the optimized control parameters.

[0045] It is understandable that the production control device 10 of the hot rolling production line also includes: a judgment unit, used to determine that there is an abnormality in the hot rolling production line if a roll changing or equipment failure is detected.

[0046] The calculation indicators for the furnace temperature uniformity include the temperature uniformity of the billet along its length, width, and thickness when the billet exits the furnace. The calculation indicators for the matching degree of upstream and downstream processes in the hot rolling production line include time coordination matching degree, capacity adaptation matching degree, and process parameter compatibility matching degree. The billet's furnace dwell time constraint is that it falls within the allowable furnace dwell time range; the billet's exit temperature constraint is that it falls within the allowable exit temperature range; and the walking beam's operating frequency constraint is that its operating frequency is less than a preset operating frequency threshold. The preset cycle time is 5 to 10 minutes.

[0047] Understandably, the optimization unit 120 is specifically used for: initializing the hyperparameters and initial solution group of the multi-objective optimization algorithm; the initial solution group includes multiple sets of candidate solutions, each set of candidate solutions including the predetermined step time of the billet and multiple set temperatures of the heating furnace; processing the running data through the multi-objective optimization algorithm to obtain the index prediction results corresponding to each set of candidate solutions; the index prediction results include total fuel consumption, the deviation between the actual furnace time of the billet and the preset optimal furnace time, the furnace temperature uniformity, and the matching degree of upstream and downstream processes of the hot rolling production line; determining the fitness value of each set of candidate solutions based on the index prediction results corresponding to each set of candidate solutions; and iteratively optimizing the solution group of the multi-objective optimization algorithm based on the fitness value of each set of candidate solutions until the preset iteration termination condition is met to obtain the optimized control parameters.

[0048] It should be understood that further implementation details of the production control device 10 for the hot rolling production line in the embodiments of the present invention are described in the aforementioned production control method for the hot rolling production line, and will not be repeated here for the sake of brevity.

[0049] Based on the same inventive concept, embodiments of the present invention also provide an electronic device, such as... Figure 3 As shown, it includes a memory 304, a processor 302, and a computer program stored in the memory 304 and capable of running on the processor 302. The processor 302 executes the program to implement the steps described in any embodiment of the production control method for the hot rolling production line.

[0050] Among them, Figure 3In this document, a bus architecture (represented by bus 300) is used. Bus 300 may include any number of interconnected buses and bridges, linking various circuits including one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 may be the same element, i.e., a transceiver, providing a unit for communicating with various other devices over a transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 can be used to store data used by processor 302 during operation.

[0051] Based on the same inventive concept, embodiments of the present invention also provide a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps described in any embodiment of the production control method for a hot rolling production line.

[0052] The functions described herein can be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions can be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and embodiments are within the scope and spirit of this invention and the appended claims. For example, due to the nature of software, the functions described above can be implemented using software executed by a processor, hardware, firmware, hardwired, or any combination thereof. Furthermore, the functional units can be integrated into a single processing unit, or each unit can exist physically separately, or two or more units can be integrated into a single unit.

[0053] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0054] The units described as separate components may or may not be physically separate. Similarly, the components of the control device may or may not be physical units; they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0055] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0056] The above description is merely an embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A production control method for a hot rolling production line, characterized in that, The hot rolling production line includes a heating furnace; the method includes: During the operation of the hot rolling production line, if an abnormality is detected in the hot rolling production line or after a preset interval, the operation data of the hot rolling production line is acquired. The operating data is processed using a multi-objective optimization algorithm to obtain the optimized control parameters for the hot rolling production line. The optimization objectives of the multi-objective optimization algorithm include minimizing total fuel consumption, minimizing the deviation between the actual furnace time of the billet and the preset optimal furnace time, maximizing the temperature uniformity within the furnace, and maximizing the matching degree between upstream and downstream processes of the hot rolling production line. The optimization variables of the multi-objective optimization algorithm include the predetermined stepping time of the billet and the multiple set temperatures of the furnace. The boundary constraints of the multi-objective optimization algorithm include the furnace time constraint of the billet, the billet exit temperature constraint, and the operating frequency constraint of the walking beam of the furnace. The production of the hot rolling production line is controlled based on the optimized control parameters.

2. The production control method for a hot rolling production line according to claim 1, characterized in that, Also includes: If a roll changing or equipment malfunction is detected in the hot rolling production line, it is determined that the hot rolling production line is abnormal.

3. The production control method for a hot rolling production line according to claim 1, characterized in that, The calculation indexes for the temperature uniformity inside the heating furnace include the temperature uniformity of the steel billet in the length direction, the temperature uniformity of the steel billet in the width direction, and the temperature uniformity of the steel billet in the thickness direction when the steel billet exits the heating furnace.

4. The production control method for a hot rolling production line according to claim 1, characterized in that, The calculation indicators for the matching degree of upstream and downstream processes of the hot rolling production line include time coordination matching degree, capacity adaptation matching degree, and process parameter compatibility matching degree.

5. The production control method for a hot rolling production line according to claim 1, characterized in that, The furnace time constraint for the steel billet is that the furnace time of the steel billet is within the allowable range of the furnace time of the steel billet; The furnace exit temperature constraint for the steel billet is that the furnace exit temperature of the steel billet is within the allowable range of the furnace exit temperature of the steel billet; The operating frequency constraint of the walking beam of the heating furnace is that the operating frequency of the walking beam is less than a preset operating frequency threshold.

6. The production control method for a hot rolling production line according to claim 1, characterized in that, The process of processing the operating data based on a multi-objective optimization algorithm to obtain the optimized control parameters of the hot rolling production line includes: The hyperparameters and initial solution group of the multi-objective optimization algorithm are initialized; the initial solution group includes multiple sets of candidate solutions, each set of candidate solutions including the predetermined step time of the billet and the multiple set temperatures of the heating furnace; The operational data is processed by the multi-objective optimization algorithm to obtain the index prediction results corresponding to each of the multiple candidate solutions. The index prediction results include total fuel consumption, the deviation between the actual furnace time of the steel billet and the preset optimal furnace time, the furnace temperature uniformity of the heating furnace, and the matching degree of the upstream and downstream processes of the hot rolling production line. Based on the index prediction results corresponding to each of the multiple candidate solutions, the fitness value of each of the multiple candidate solutions is determined. Based on the fitness value of each candidate solution in the multiple candidate solutions, the solution group of the multi-objective optimization algorithm is iteratively optimized until the preset iteration termination condition is met, so as to obtain the optimization control parameters.

7. The production control method for a hot rolling production line according to any one of claims 1-6, characterized in that, The preset cycle is 5 min to 10 min.

8. A production control device for a hot rolling production line, characterized in that, The hot rolling production line includes a heating furnace; the apparatus includes: The data acquisition unit is used to acquire the operating data of the hot rolling production line if an abnormality is detected in the hot rolling production line or after a preset interval during the operation of the hot rolling production line. An optimization unit is used to process the operating data based on a multi-objective optimization algorithm to obtain optimized control parameters for the hot rolling production line. The optimization objectives of the multi-objective optimization algorithm include minimizing total fuel consumption, minimizing the deviation between the actual furnace time of the billet and the preset optimal furnace time, maximizing the furnace temperature uniformity of the furnace, and maximizing the matching degree between upstream and downstream processes of the hot rolling production line. The optimization variables of the multi-objective optimization algorithm include the predetermined stepping time of the billet and the multiple set temperatures of the furnace. The boundary constraints of the multi-objective optimization algorithm include the furnace time constraint of the billet, the billet exit temperature constraint, and the operating frequency constraint of the walking beam of the furnace. A control unit is used to control the production of the hot rolling production line based on the optimized control parameters.

9. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method of any one of claims 1-7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 7.

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