Roll quenching process operation parameter setting method, device, equipment and medium

Abstract

This application discloses a method, apparatus, equipment, and medium for setting operating parameters in a roller quenching process, relating to the field of industrial data processing technology. The method includes: acquiring the quenching operating parameters of the target steel plate; selecting a first candidate case group from a production case database; if the parameters meet the criteria, using a high-frequency historical parameter group as the target parameters; otherwise, determining a second candidate case; combining the parameter difference with an expert rule database to obtain the adjustment amount; and after correction calculation to obtain the target parameters, sending them to the quenching control system for execution. This automates parameter setting, improves the accuracy of quenching process parameter setting, reduces manual intervention, lowers the plate shape defect rate, and increases production efficiency and yield.

Description

Technical Field

[0001] This invention relates to the field of industrial data processing technology, and in particular to a method, apparatus, equipment and medium for setting operating parameters of a roller quenching process. Background Technology

[0002] Currently, the setting of operating parameters for the roller quenching process mainly relies on three manual methods: First, the manual experience-based method, where operators, based on their long-term accumulated production experience, manually set the process operating parameters directly from memory, taking into account the specifications of the steel plate, such as thickness, width, length, and steel grade, combined with actual working conditions such as cooling water temperature and current plate shape feedback. Second, the table lookup method, where enterprises establish process parameter tables based on historical production experience, dividing the range by steel grade and steel plate specifications, and operators look up and select the corresponding parameter values ​​from the table according to the current production conditions. Third, the trial-and-error adjustment method, where operators first set initial process parameters, monitor the plate shape defects of the steel plate in real time using a flatness meter, and then manually and repeatedly adjust the parameters according to the location and degree of defects until the steel plate shape passes inspection.

[0003] The aforementioned parameter setting methods all have significant technical flaws. First, the entire parameter setting and adjustment process is highly dependent on manual intervention, requiring operators to monitor production conditions in real time and repeatedly modify parameters. This not only significantly increases the operator's workload but also reduces the continuity and overall efficiency of roller quenching production. Second, the manual experience-based method is limited by the operator's individual experience level. The adjustment skills of excellent operators are difficult to quantify and pass on, and new operators find it difficult to quickly get started. Furthermore, the parameter settings of operators on different shifts vary greatly, leading to significant fluctuations in product quality. Third, the preset parameters of the lookup table method are based on limited historical production cases and cannot fully cover complex working conditions such as water temperature fluctuations, equipment aging, and minor differences in steel plate specifications in actual production. The matching degree between parameters and actual production needs is low. Fourth, the parameter optimization process of the trial-and-error adjustment method is time-consuming, which can easily cause many steel plates to become defective products in the early stages of production. This not only affects the normal production rhythm but also reduces the steel yield and increases production energy consumption.

[0004] Therefore, how to automate and intelligently set the operating parameters of the roller quenching process and improve the accuracy of parameter setting has become an urgent problem to be solved. Summary of the Invention

[0005] The main purpose of this application is to provide a method, apparatus, equipment and medium for setting operating parameters of a roller quenching process, aiming to solve the technical problem of how to improve the accuracy of quenching process parameter setting.

[0006] To achieve the above objectives, this application proposes a method for setting operating parameters for a roller quenching process, comprising: The quenching operation parameters of the target steel plate are obtained, wherein the quenching operation parameters include dimensional characteristics and actual environmental parameters. The dimensional characteristics include length, width, thickness and steel type, and the actual environmental parameters include cooling water temperature. Based on the specified characteristics, a first candidate case group that meets the preset matching conditions is selected from the preset production case library, wherein the preset production case library contains historical production cases, and each historical production case includes historical specified characteristics, historical environmental parameters, historical operating parameter groups and historical flatness detection results; When the number of cases in the first candidate case group reaches the preset case number threshold, the historical operation parameter group with the highest frequency is selected from the first candidate case group as the target operation parameter group. When the number of cases in the first candidate case group does not reach the preset case number threshold, a second candidate case is determined from the preset production case library, and the preset expert rule library is queried according to the difference between the quenching operation parameter and the corresponding quenching operation parameter in the second candidate case to obtain the first parameter adjustment amount; The target operation parameters are obtained by performing parameter correction calculations on the historical operation parameter group of the second candidate case and the first parameter adjustment amount; The target operating parameters are sent to the roller quenching control system so that the roller quenching control system executes the roller quenching process according to the target operating parameters.

[0007] In one embodiment, the step of selecting a first candidate case group that meets preset matching conditions from a preset production case library based on the specification characteristics includes: The historical production cases in the preset production case library are divided into a first preset duration and a second preset duration based on production time, and the case subset with the first preset duration is retrieved first. Historical production cases that match the target steel plate type are selected from the priority subset of cases to form a steel type matching case set; In the steel type matching case set, cases whose thickness deviation from the target steel plate thickness is within a preset thickness range are selected to form a thickness matching case set; Cases whose width is within a preset width range of the target steel plate width and whose length is within a preset length range of the target steel plate length are selected from the thickness matching case set to form a dimension matching case set; Extract all historical production cases from the dimension-matching case set and integrate them to determine the first candidate case group; When the first preset duration subset of cases fails to filter out the dimension-matching case set, the second preset duration subset of cases is retrieved and the filtering steps for steel type, thickness, width, and length are repeated to obtain the first candidate case group.

[0008] In one embodiment, the step of selecting the most frequent historical operation parameter group from the first candidate case group as the target operation parameter group includes: Extract the historical operation parameter groups and corresponding historical flatness detection results for all historical production cases in the first candidate case group; Count the frequency of occurrence of each historical operation parameter group in the first candidate case group, and generate a parameter group statistical list with the occurrence frequency; The parameter group statistics list is sorted in descending order of frequency of occurrence. The historical operation parameter group with the highest frequency is selected as the initial parameter group. The historical flatness detection results of all historical production cases corresponding to the initial parameter set are verified to obtain a parameter set that passes the verification. When there are multiple parallel cases with the same frequency in the initial parameter group, the historical operation parameter group with the latest production time is selected as the candidate parameter group. The parameter group or candidate parameter group that passes the verification is determined as the target operation parameter group.

[0009] In one embodiment, the step of determining a second candidate case from the preset production case library and querying a preset expert rule library based on the difference between the quenching operation parameters and the corresponding quenching operation parameters in the second candidate case to obtain the first parameter adjustment amount includes: Differentiated weighting coefficients are assigned to the length, width, thickness, and cooling water temperature of the target steel plate specifications and actual environmental parameters to form a weighted calculation system; Based on the weighted calculation system, the weighted Euclidean distance algorithm is used to calculate the quenching operation parameters of the target steel plate and the corresponding parameters of all historical production cases in the preset production case library to obtain the similarity distance value. All similarity distance values ​​are sorted in ascending order, and the historical production case with the smallest distance value is selected as the second candidate case. Calculate the deviation values ​​between the quenching operation parameters of the target steel plate and the corresponding parameters of the second candidate case to form a structured parameter deviation set; The parameter deviation set is input into a preset expert rule base for matching to obtain the parameter adjustment rules and adjustment coefficients corresponding to each parameter deviation. The specific adjustment values ​​corresponding to the quenching operation parameters are calculated based on the parameter adjustment rules and adjustment coefficients, and integrated to form the first parameter adjustment amount.

[0010] In one embodiment, before the step of inputting the parameter deviation set into a preset expert rule base for matching to obtain the parameter adjustment rules and adjustment coefficients corresponding to each parameter deviation, the method includes: Historical data on manual adjustment of process parameters during the roller quenching production process were collected, and the working condition deviation conditions triggered by the adjustment and the corresponding parameter adjustment amount were extracted to form the original adjustment dataset. The original adjusted dataset is preprocessed to obtain a standardized adjusted dataset; The deviation dimensions of steel grade, specification, and cooling water temperature, as well as the corresponding adjustment rules for roller conveyor, roller gap, and spray flow rate, are extracted from the standardized adjustment dataset to form a basic rule set. By combining the experience of process engineers, parameter adjustment coefficients are configured for each deviation dimension in the basic rule set to obtain the optimized basic rule set. The optimized basic rule set is classified and stored according to the type of operating condition deviation to construct an initial expert rule base; The initial expert rule base is put into production trial operation, and the rules and adjustment coefficients are iteratively optimized according to the process effect adjusted by actual parameters to form a preset expert rule base.

[0011] In one embodiment, the step of performing parameter correction calculations on the historical operation parameter group of the second candidate case and the first parameter adjustment amount to obtain the target operation parameters includes: The historical operation parameter group of the second candidate case is split to obtain the historical parameter values ​​of each process dimension, and then integrated to form a set of historical parameter dimensions; The adjustment amount of the first parameter is broken down to obtain the adjustment value of each process dimension corresponding to the historical parameter dimension set, and then integrated to form the adjustment value dimension set. The historical parameter values ​​in the historical parameter dimension set and the corresponding adjustment values ​​in the adjustment value dimension set are subjected to dimensional correction operations according to the process dimension to obtain the corrected parameter values ​​for each process dimension. The corrected parameter values ​​for each process dimension and the preset threshold ranges for each parameter in the roller quenching process are verified to obtain the verification results. When the verification result shows that the corrected parameter value does not exceed the corresponding parameter threshold range, a compliant parameter value is obtained; When the verification result indicates that the corrected parameter value exceeds the corresponding parameter threshold range, the parameter value is corrected according to the parameter threshold range to obtain the corrected parameter value. The corrected parameter values ​​and compliant parameter values ​​are integrated into a target operating parameter group.

[0012] In one embodiment, the step of sending the target operating parameters to the roller quenching control system so that the roller quenching control system executes the roller quenching process according to the target operating parameters includes: The target operation parameter group is associated and bound with the steel plate identification information of the target steel plate to generate a process execution instruction package, wherein the process execution instruction package includes the target roller speed, the target roller acceleration, the target roller gap parameters, the target high pressure zone spray flow rate, the target low pressure zone spray flow rate, and the target upper and lower nozzle flow rate ratio; Based on the current position information of the target steel plate, determine whether the target steel plate has reached the preset quenching preparation position; When the target steel plate reaches the preset quenching preparation position, the process execution instruction package is sent to the roller quenching control system so that the roller quenching control system performs the roller quenching process on the target steel plate according to the process execution instruction package. Receive real-time process execution data fed back by the roller quenching control system, wherein the real-time process execution data includes actual roller speed, actual roller acceleration, actual roller gap parameters of each section, actual high-pressure zone spray flow rate, actual low-pressure zone spray flow rate, and actual upper and lower nozzle flow rate ratio; The real-time process execution data is compared and analyzed with the target operating parameter set to obtain the parameter execution deviation value; The parameter execution deviation value and the steel plate identification information are associated and stored in the process execution log database.

[0013] Furthermore, to achieve the above objectives, this application also proposes an operating parameter setting device for a roller quenching process, the operating parameter setting device for the roller quenching process comprising: The acquisition module is used to acquire the quenching operation parameters of the target steel plate, wherein the quenching operation parameters include dimensional characteristics and actual environmental parameters. The dimensional characteristics include length, width, thickness and steel type, and the actual environmental parameters include cooling water temperature. The filtering module is used to filter out a first candidate case group that meets the preset matching conditions from the preset production case library according to the specification characteristics. The preset production case library contains historical production cases, and each historical production case includes historical specification characteristics, historical environmental parameters, historical operating parameter groups and historical flatness detection results. The first parameter determination module is used to select the most frequent historical operation parameter group from the first candidate case group as the target operation parameter group when the number of cases in the first candidate case group reaches a preset case number threshold. The second parameter determination module is used to determine a second candidate case from the preset production case library when the number of cases in the first candidate case group does not reach the preset case number threshold, and to query the preset expert rule library according to the difference between the quenching operation parameter and the corresponding quenching operation parameter in the second candidate case to obtain the first parameter adjustment amount; The correction module is used to perform parameter correction calculations on the historical operation parameter group of the second candidate case and the first parameter adjustment amount to obtain the target operation parameters; The sending module is used to send the target operating parameters to the roller quenching control system, so that the roller quenching control system executes the roller quenching process according to the target operating parameters.

[0014] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the operation parameter setting method for the roller quenching process as described above.

[0015] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the operation parameter setting method for the roller quenching process as described above.

[0016] This application obtains the quenching operation parameters of the target steel plate, then selects the first candidate case group from the production case database. If the parameters meet the criteria, the high-frequency historical parameter group is used as the target parameters; otherwise, a second candidate case is determined. The adjustment amount is obtained by consulting an expert rule database based on the parameter difference. After correction calculation, the target parameters are obtained and sent to the quenching control system for execution. This automates parameter setting, improves the accuracy of quenching process parameter setting, reduces manual intervention, lowers the plate shape defect rate, and increases production efficiency and yield. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating the first embodiment of the method for setting operating parameters for the roller quenching process of this application; Figure 2 This is a flowchart illustrating the second embodiment of the method for setting operating parameters for the roller quenching process in this application. Figure 3 This is a schematic diagram of the module structure of the operating parameter setting device for the roller quenching process in this application. Figure 4 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the method for setting the operating parameters of the roller quenching process in the embodiments of this application.

[0019] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0021] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0022] Currently, the setting of operating parameters for the roller quenching process mainly relies on three manual methods: First, the manual experience-based method, where operators, based on their long-term accumulated production experience, manually set the process operating parameters directly from memory, taking into account the specifications of the steel plate, such as thickness, width, length, and steel grade, combined with actual working conditions such as cooling water temperature and current plate shape feedback. Second, the table lookup method, where enterprises establish process parameter tables based on historical production experience, dividing the range by steel grade and steel plate specifications, and operators look up and select the corresponding parameter values ​​from the table according to the current production conditions. Third, the trial-and-error adjustment method, where operators first set initial process parameters, monitor the plate shape defects of the steel plate in real time using a flatness meter, and then manually and repeatedly adjust the parameters according to the location and degree of defects until the steel plate shape passes inspection.

[0023] The aforementioned methods for setting operating parameters all have significant technical flaws. First, the entire parameter setting and adjustment process is highly dependent on manual intervention, requiring operators to monitor production conditions in real time and repeatedly modify parameters. This not only significantly increases the operator's workload but also reduces the continuity and overall efficiency of roller quenching production. Second, the manual experience-based method is limited by the operator's individual experience level. The adjustment skills of excellent operators are difficult to quantify and pass on, new operators find it difficult to quickly get started, and the parameter settings of operators on different shifts vary greatly, leading to significant fluctuations in product quality. Third, the preset parameters of the lookup table method are based on limited historical production cases and cannot fully cover complex working conditions such as water temperature fluctuations, equipment aging, and minor differences in steel plate specifications in actual production, resulting in a low degree of matching between parameters and actual production needs. Fourth, the parameter optimization process of the trial-and-error adjustment method is time-consuming, easily causing multiple steel plates to become defective products in the early stages of production. This not only affects the normal production rhythm but also reduces the steel yield and increases production energy consumption. Therefore, how to automate and intelligently set the operating parameters for the roller quenching process and improve the accuracy of parameter setting has become an urgent problem to be solved.

[0024] Based on the above, this application also provides a method for setting operating parameters for a roller quenching process, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the method for setting operating parameters for the roller quenching process of this application.

[0025] In this embodiment, the method for setting the operating parameters of the roller quenching process includes steps S10 to S60: Step S10: Obtain the quenching operation parameters of the target steel plate.

[0026] It should be noted that the quenching operation parameters include dimensional characteristics and actual environmental parameters. The dimensional characteristics include length, width, thickness and steel type, while the actual environmental parameters include cooling water temperature.

[0027] Specifically, firstly, production order data for the target steel plate is read from the Manufacturing Execution System (MES) or Enterprise Resource Planning (ERP) system via a data interface. The length, width, thickness, and steel type of the target steel plate are extracted as specification features. The reason for reading from the MES or ERP system is that these systems store the original production order information for the steel plate, ensuring the accuracy and authority of the specification parameters and avoiding human input errors. Secondly, the cooling water temperature in the quenching tank is collected as an actual environmental parameter through the real-time data interface of the distributed control system. Real-time collection from the distributed control system is necessary because the cooling water temperature fluctuates dynamically with the season, production rhythm, and the status of the circulating water system. Real-time collection ensures that the water temperature data is obtained under the current actual operating conditions, rather than relying on historical records or manual transcription. Finally, the specification features and actual environmental parameters are associated and bound together to generate a target steel plate feature data package, which is then stored in a temporary cache. This association and caching are performed to uniformly identify the inherent properties of the steel plate with the current environmental conditions, facilitating rapid retrieval in subsequent case matching steps and avoiding delays caused by repeatedly reading data from various systems.

[0028] Step S20: Select the first candidate case group that meets the preset matching conditions from the preset production case library according to the specification characteristics.

[0029] It should be noted that the preset production case library is a collection of historical successful production cases accumulated during the roll quenching process, and only includes production cases where the flatness index is qualified after quenching. The preset production case library contains historical production cases, which are single qualified quenching production records stored in the preset production case library. Each historical production case includes historical specification characteristics, historical environmental parameters, historical operating parameter groups, and historical flatness test results. Historical specification characteristics are the length, width, thickness, and steel type of the corresponding steel plate in the historical production case, and are the same type of parameters as the specification characteristics of the target steel plate. Historical environmental parameters are the actual working environment parameters during quenching in the historical production case, with the cooling water temperature being the core. The historical operating parameter group is the set of core operating parameters of roll quenching actually executed in the historical production case, including key parameters such as roller speed, roller acceleration, roller gap of each section, and water volume of high and low pressure nozzles. Historical flatness test results are plate shape-related data obtained by flatness testers after steel plates have been quenched in historical production cases. These data include defect type, defect degree, and flatness index, and serve as the basis for determining whether a case should be included in the database.

[0030] Further, step S20 includes: dividing historical production cases in the preset production case library into a first preset duration and a second preset duration subset based on production time, and prioritizing the retrieval of the first preset duration subset; selecting historical production cases consistent with the target steel plate type from the prioritized subset to form a steel type matching case set; selecting cases whose thickness deviation from the target steel plate thickness is within a preset thickness range from the steel type matching case set to form a thickness matching case set; selecting cases whose width is within a preset width range of the target steel plate width and whose length is within a preset length range of the target steel plate length from the thickness matching case set to form a dimension matching case set; extracting all historical production cases from the dimension matching case set and integrating them to determine the first candidate case group; when no dimension matching case set is selected from the first preset duration subset, retrieving the second preset duration subset and repeating the steel type, thickness, width, and length selection steps to obtain the first candidate case group.

[0031] Specifically, firstly, the production timestamps of each historical production case in the preset production case library are read. Historical production cases with production times within the first preset duration (the last 7 days) are grouped into the first case subset, and historical production cases with production times within the second preset duration (the last 30 days) but exceeding the first preset duration are grouped into the second case subset. The first case subset is prioritized for subsequent screening. The reason for prioritizing the case subset within the last 7 days is that recent cases better reflect the current equipment status, water temperature conditions, and process habits, and their parameter settings have higher reference value and timeliness for current production. Secondly, in the prioritized case subset, historical production cases whose historical steel type is completely consistent with the target steel plate steel type are selected to form a steel type matching case set. The reason for prioritizing steel type matching is that the heat treatment process characteristics of different steel types are significantly different, and the quenching cooling curves and microstructure transformation laws are completely different. Cases with inconsistent steel types are not of reference value. Then, in the steel grade matching case set, the thickness deviation between the historical thickness and the target steel plate thickness of each historical production case is calculated. Historical production cases with thickness deviation values ​​within a preset thickness range (±0.1 mm) are selected to form a thickness matching case set. The reason for performing thickness screening after steel grade matching is that the steel plate thickness directly determines the heat capacity and cooling rate. Excessive thickness deviation will lead to mismatch in cooling intensity, resulting in plate shape defects. Next, in the thickness matching case set, the width deviation between the historical width and the target steel plate width, as well as the length deviation between the historical length and the target steel plate length of each historical production case, are calculated. Historical production cases with width deviation values ​​within a preset width range (±50 mm to ±200 mm) and length deviation values ​​within a preset length range (±3000 mm) are selected to form a dimension matching case set. The reason for performing width and length screening after thickness matching is that width and length mainly affect the boundary conditions of plate shape control and roller conveyor running time, and their allowable deviation range is relatively large. Screening them later can expand the range of selectable cases while ensuring the core matching accuracy. Next, all historical production cases in the dimensional matching case set are extracted. The historical specifications, environmental parameters, operational parameter groups, and flatness detection results of these historical production cases are integrated to determine the first candidate case set. Finally, if the case subset of the first preset time period fails to form a dimensional matching case set after the above screening steps, the case subset of the second preset time period is retrieved, and the steel type screening, thickness deviation screening, width deviation, and length deviation screening steps are repeated to obtain the first candidate case set. The second preset time period is set as a supplement because when there are no similar specifications of steel plates in the recent production plan, it is necessary to appropriately expand the time range to ensure the success rate of case matching and avoid directly entering the approximate calculation process due to insufficient cases.

[0032] Step S30: When the number of cases in the first candidate case group reaches the preset case number threshold, select the historical operation parameter group with the highest frequency from the first candidate case group as the target operation parameter group.

[0033] It should be noted that the preset case quantity threshold is a quantitative standard for determining whether the matching cases in the first candidate case group have reference value. It is a pre-set numerical limit, and reaching this value means that there are enough cases in the group to support the subsequent parameter selection. The highest frequency means that among all historical production cases in the first candidate case group, a certain set of historical operating parameters appears the most times in the cases, which represents the universality and effectiveness of the application of that parameter set in similar working conditions.

[0034] Further, step S30 includes: extracting the historical operation parameter groups and corresponding historical flatness detection results for all historical production cases in the first candidate case group; counting the frequency of occurrence of each historical operation parameter group in the first candidate case group to generate a parameter group statistical list with occurrence frequency; sorting the parameter group statistical list in descending order of occurrence frequency and selecting the historical operation parameter group with the highest frequency as the initial parameter group; verifying the historical flatness detection results of all historical production cases corresponding to the initial parameter group to obtain the verified parameter group; when there are multiple cases with the same frequency in the initial parameter group, selecting the historical operation parameter group with the latest production time as the candidate parameter group; and determining the verified parameter group or candidate parameter group as the target operation parameter group.

[0035] It's important to understand that frequency of occurrence refers to the specific number of times a historical operating parameter group appears in all historical production cases within the first candidate case group. The frequency reflects the application prevalence and practical validation of that parameter group in similar operating conditions. The parameter group statistics list integrates all historical operating parameter groups in the first candidate case group and their corresponding frequencies, clearly presenting the occurrence of each parameter group. Descending order sorting arranges the historical operating parameter groups in the parameter group statistics list according to their frequency of occurrence from highest to lowest, facilitating quick identification of the parameter group with the most frequent application. The initial parameter group is the historical operating parameter group with the highest frequency selected from the descendingly sorted parameter group statistics list; it is the preliminary candidate for the target operating parameter group and requires subsequent verification. A qualified parameter group is the parameter group whose flatness index in all its corresponding historical production cases meets the qualified standard after verification by historical flatness testing results, thus possessing the basic conditions to become a target parameter group. A tie occurs when, after the parameter group statistics list is sorted in descending order, there are two or more historical operating parameter groups with the exact same and highest frequency of occurrence; further screening using additional rules is required. Candidate parameter groups are historical operation parameter groups selected according to the latest production time when the frequency of occurrence of the initial parameter groups is the same. They are candidate target parameter groups to replace the initial parameter groups.

[0036] Specifically, the historical operating parameter sets and corresponding historical flatness test results for all historical production cases in the first candidate case group are extracted. The reason for extracting both historical operating parameter sets and historical flatness test results is that the quality of operating parameters needs to be verified through actual plate shape quality; only by associating parameter settings with quality results can the effectiveness of recommended parameters be ensured. Secondly, all historical production cases in the first candidate case group are traversed, and historical operating parameter sets with identical parameter values ​​are identified as belonging to the same parameter category. The frequency of each parameter category in the first candidate case group is counted, generating a parameter group statistical list with frequency of occurrence. Frequency statistics are performed because frequently occurring parameter groups represent process settings that have been successfully verified multiple times in recent production, exhibiting higher reliability and stability. Then, the parameter group statistical list is sorted in descending order of frequency of occurrence, and the historical operating parameter set with the highest frequency is selected as the initial parameter group. The highest frequency parameter group is chosen because it represents the solution that has been verified most extensively in production practice, maximizing the plate shape qualification rate. Next, the historical flatness test results of all historical production cases corresponding to the initial parameter group are obtained. It is determined whether each historical flatness test result falls within the preset acceptable threshold range. Initial parameter groups with all historical flatness test results falling within the acceptable range are selected as qualified parameter groups. Flatness verification is necessary because high frequency does not equate to high quality; parameter groups that have been used multiple times but have caused plate shape defects need to be removed to ensure the reliability of the recommended parameters. Then, when multiple initial parameter groups have the same frequency, the production timestamps of the historical production cases corresponding to each parallel parameter group are compared. The historical operation parameter group with the most recent production time is selected as the candidate parameter group. The reason for prioritizing the parameter group with the most recent production time in parallel cases is that this parameter group better reflects the current equipment status and water temperature conditions, and has stronger timeliness. Finally, the qualified parameter group or candidate parameter group is determined as the target operation parameter group. Both are considered as the final output because the qualified parameter group has undergone quality verification, while the candidate parameter group has undergone timeliness screening in parallel cases; both meet reliability requirements.

[0037] Step S40: When the number of cases in the first candidate case group does not reach the preset case number threshold, a second candidate case is determined from the preset production case library, and the first parameter adjustment amount is obtained by querying the preset expert rule library based on the difference between the quenching operation parameters and the corresponding quenching operation parameters in the second candidate case.

[0038] It should be noted that the second candidate case is a historical production case in the preset production case library that has the highest similarity to the quenching operation parameters of the target steel plate. It serves as a single qualified historical case to provide a basic reference for parameter setting when there are insufficient first candidate cases. The difference is the parameter value difference calculated after comparing the quenching operation parameters of the target steel plate with the corresponding quenching operation parameters in the second candidate case one by one. This is the core basis for triggering parameter adjustments in the expert rule library. The preset expert rule library is a set of rules established based on manual adjustment experience of the roller quenching process. It stores parameter adjustment criteria corresponding to different working condition deviations, enabling intelligent fine-tuning of basic parameters. The first parameter adjustment amount is the process parameter adjustment value calculated after matching the difference in quenching operation parameters with the preset expert rule library. This is the specific basis for correcting the historical operation parameter group of the second candidate case.

[0039] Furthermore, firstly, it is determined whether the number of cases in the first candidate case group reaches the preset case number threshold (e.g., 3). If the threshold is not reached, all historical production cases in the preset production case library are read, and the specification similarity between each historical production case and the target steel plate is calculated. The specification similarity calculation includes: calculating the length difference between the target steel plate length and the historical length and multiplying it by the preset length weight coefficient; calculating the width difference between the target steel plate width and the historical width and multiplying it by the preset width weight coefficient; calculating the thickness difference between the target steel plate thickness and the historical thickness and multiplying it by the preset thickness weight coefficient; calculating the water temperature difference between the target steel plate cooling water temperature and the historical cooling water temperature and multiplying it by the preset water temperature weight coefficient; and taking the square root of the sum of the squares of the four weighted differences to obtain the weighted distance value. The reason for using weighted Euclidean distance to calculate specification similarity is that different specification parameters have different degrees of influence on the quenching process. Thickness directly affects the cooling intensity and needs to be given the highest weight, while length and width affect the plate shape control boundary and are given medium weight, and water temperature affects the cooling rate and is given a certain weight. Secondly, the historical production cases were sorted in ascending order of weighted distance value, and the historical production case with the smallest weighted distance value was selected as the second candidate case. The reason for selecting the case with the smallest weighted distance value is that this case is closest to the target steel plate in terms of specifications and operating conditions. Then, the first temperature difference between the target steel plate's cooling water temperature and the historical cooling water temperature of the second candidate case was calculated, the first thickness difference between the target steel plate's thickness and the historical thickness of the second candidate case was calculated, and the first width difference between the target steel plate's width and the historical width of the second candidate case was calculated. The reason for calculating these three differences is that cooling water temperature, thickness, and width are core variables affecting quenching cooling intensity and plate shape control. Next, the first water temperature difference, the first thickness difference, and the first width difference are used as input conditions to query a preset expert rule base. This base stores adjustment rules derived from expert experience, including water temperature adjustment rules, thickness adjustment rules, and width adjustment rules. The water temperature adjustment rules define the direction and magnitude of spray flow rate adjustment for different water temperature difference ranges; the thickness adjustment rules define the direction and magnitude of roller speed and roller gap adjustment for different thickness difference ranges; and the width adjustment rules define the direction and magnitude of the upper and lower nozzle flow ratio adjustment for different width difference ranges. Then, the water temperature adjustment rule is queried based on the first water temperature difference to obtain the spray flow rate adjustment component; the thickness adjustment rule is queried based on the first thickness difference to obtain the roller speed and roller gap adjustment components; and the width adjustment rule is queried based on the first width difference to obtain the upper and lower nozzle flow ratio adjustment component. These adjustment components are then combined to generate the first parameter adjustment amount.Finally, the first parameter adjustment amount and the historical operation parameter group of the second candidate case are superimposed on the corresponding components to obtain the target operation parameter group. The reason for using superposition is that the historical operation parameter group of the second candidate case provides the basic process framework, and the first parameter adjustment amount provides the correction amount for the specific deviation of the target steel plate. The superposition of the two can achieve personalized adaptation based on successful cases.

[0040] Furthermore, the steps for establishing a pre-set expert rule base include: collecting historical data on manual adjustment of process parameters during the roll quenching production process, and extracting the working condition deviation conditions triggered by the adjustment and the corresponding parameter adjustment amounts to form an original adjustment dataset; performing data preprocessing on the original adjustment dataset to obtain a standardized adjustment dataset; extracting the deviation dimensions of steel grade, specification, and cooling water temperature from the standardized adjustment dataset, as well as the corresponding adjustment rules for roller conveyor, roller gap, and spray flow rate for each dimension, to form a basic rule set; configuring parameter adjustment coefficients for each deviation dimension in the basic rule set based on the experience of process personnel to obtain an optimized basic rule set; classifying and storing the optimized basic rule set according to the type of working condition deviation to construct an initial expert rule base; and putting the initial expert rule base into production trial operation, iteratively optimizing the rules and adjustment coefficients based on the actual process effects of parameter adjustments to form a pre-set expert rule base.

[0041] It is important to understand that, firstly, historical data on manual adjustments of process parameters during the roll quenching production process is collected. The operator's manual adjustment operation log recorded in the distributed control system is read. The deviation values ​​of the target steel plate specifications, actual environmental parameters, and the case before adjustment at the time of each adjustment trigger are extracted as working condition deviation conditions. At the same time, the changes in roller speed, roller acceleration, roller gap, high-pressure zone spray flow rate, low-pressure zone spray flow rate, and upper and lower nozzle flow ratio before and after adjustment are extracted as parameter adjustment quantities. The working condition deviation conditions and the corresponding parameter adjustment quantities are combined to form the original adjustment dataset. The reason for collecting historical data on manual adjustments is that excellent operators have accumulated rich experience in parameter fine-tuning in long-term practice. This data contains coping strategies for different working condition deviations and is the factual basis for building the expert rule base. Secondly, the original adjustment dataset undergoes data preprocessing to remove invalid records with zero parameter adjustments or missing operating condition deviation conditions. The remaining operating condition deviation conditions and parameter adjustments are then subjected to outlier detection and noise reduction. The processed data is standardized and encoded according to a preset format to obtain a standardized adjustment dataset. This preprocessing is necessary because production site records may contain abnormal data due to sensor malfunctions, misoperations, or communication interference; cleaning and standardization are essential to ensure the accuracy of subsequent rule extraction. Next, steel type deviation, thickness deviation, width deviation, and cooling water temperature deviation are extracted from the standardized adjustment dataset as deviation dimensions. The correlation between each deviation dimension and the adjustment amounts of each parameter is analyzed, and the distribution patterns and median values ​​of each parameter adjustment amount within different deviation intervals are statistically analyzed. This leads to the formulation of rules for adjusting roller speed corresponding to steel type deviation, roller gap corresponding to thickness deviation, upper and lower nozzle flow ratio corresponding to width deviation, and spray flow rate corresponding to water temperature deviation. These rules are combined to form a basic rule set. The reason for extracting rules from data rather than directly using verbal experience is that data-driven rule extraction can quantify the mapping relationship between deviations and adjustments, avoiding the subjectivity and ambiguity of experience-based descriptions. Next, process engineers were invited to review the basic rule set. Based on the special working conditions and boundary conditions in actual production, parameter adjustment coefficients were configured for each deviation dimension in the basic rule set, including steel grade sensitivity coefficient, thickness influence coefficient, width correction coefficient, and water temperature compensation coefficient, to obtain the optimized basic rule set. The reason for introducing the experience of process engineers to configure the coefficients is that the rules extracted from the data may have insufficient samples or incomplete coverage of extreme working conditions. The experience of process engineers can improve the completeness and safety of the rules.Next, the optimized basic rule set is categorized and stored according to the type of operating condition deviation. Branches for water temperature deviation, thickness deviation, width deviation, and steel grade difference are established. Each branch is further segmented and stored according to deviation value ranges, constructing an initial expert rule base. Categorized storage and segmented management are necessary because actual queries require quickly locating the corresponding adjustment rule based on the specific deviation type and value, improving query efficiency and rule application accuracy. Finally, the initial expert rule base is put into production trial operation. After the recommended parameters are generated, the actual parameter adjustments and corresponding plate shape quality results are recorded. The rule application effect is analyzed regularly, rules whose adjustment range deviates from the actual optimal value are corrected, new rules are added for missing deviation ranges, and adjustment coefficients are iteratively optimized to form a preset expert rule base. Trial operation and iterative optimization are necessary because the initial rules are built based on historical data and may deviate from the current equipment status. Continuous improvement through actual application feedback is needed to ensure the timeliness and accuracy of the rules.

[0042] Step S50: Perform parameter correction calculation on the historical operation parameter group of the second candidate case and the first parameter adjustment amount to obtain the target operation parameters.

[0043] It should be noted that step S50 includes: splitting the historical operation parameter group of the second candidate case to obtain the historical parameter values ​​of each process dimension, and integrating them to form a historical parameter dimension set; splitting the first parameter adjustment amount to obtain the adjustment values ​​of each process dimension corresponding to the historical parameter dimension set, and integrating them to form an adjustment value dimension set; performing dimensional correction operations on the historical parameter values ​​in the historical parameter dimension set and the corresponding adjustment values ​​in the adjustment value dimension set according to the process dimension to obtain the corrected parameter values ​​of each process dimension; verifying the corrected parameter values ​​of each process dimension with the preset parameter threshold range of the roller quenching process to obtain the verification result; when the verification result is that the corrected parameter value does not exceed the corresponding parameter threshold range, a compliant parameter value is obtained; when the verification result is that the corrected parameter value exceeds the corresponding parameter threshold range, it is corrected according to the parameter threshold range to obtain the corrected parameter value; integrating the corrected parameter value and the compliant parameter value as the target operation parameter group.

[0044] Specifically, the historical operation parameter group of the second candidate case is first read. The roller speed, roller acceleration, roller gap parameters, high-pressure zone spray flow rate, low-pressure zone spray flow rate, and upper and lower nozzle flow ratio in the historical operation parameter group are split according to the process dimension. The specific values ​​of each parameter are extracted. The split parameter values ​​are then classified and integrated according to parameter type to form a historical parameter dimension set containing six process dimensions. The reason for parameter splitting and classification is that the roller quenching process involves multiple independent control dimensions. The physical meaning and adjustment rules of each dimension are different. Dimensional processing facilitates subsequent targeted correction calculations and threshold verification. Secondly, the adjustment amount of the first parameter is read, and the roller speed adjustment component, acceleration adjustment component, roller gap adjustment component, high-pressure zone spray flow adjustment component, low-pressure zone spray flow adjustment component, and upper and lower nozzle flow ratio adjustment component in the first parameter adjustment amount are split according to the process dimension corresponding to the historical parameter dimension set. The specific value and positive and negative direction of each adjustment component are extracted, and the split adjustment components are classified and integrated according to the corresponding parameter type to form an adjustment value dimension set containing six process dimensions. The reason for dimensional splitting and corresponding integration is that the parameter adjustment amount needs to be superimposed with the historical parameter value dimension by dimension to ensure that the adjustment direction and magnitude of each process dimension can accurately act on the corresponding historical parameter. Then, according to the process dimension, the historical parameter values ​​in the historical parameter dimension set and the corresponding adjustment values ​​in the adjustment value dimension set are read one by one. The historical parameter values ​​and adjustment values ​​of the same process dimension are algebraically superimposed. For the roller speed dimension, the historical roller speed is added to the roller speed adjustment component. For the roller acceleration dimension, the historical roller acceleration is added to the acceleration adjustment component. For each section of the roller gap dimension, the historical parameters of each section of the roller gap are added to the corresponding roller gap adjustment component. For the high-pressure zone spray flow dimension, the historical high-pressure zone spray flow is added to the high-pressure zone spray flow adjustment component. For the low-pressure zone spray flow dimension, the historical low-pressure zone spray flow is added to the low-pressure zone spray flow adjustment component. For the upper and lower nozzle flow ratio dimension, the historical upper and lower nozzle flow ratio is added to the upper and lower nozzle flow ratio adjustment component. The corrected parameter values ​​of each process dimension are obtained. The reason for using algebraic superposition is that the parameter adjustment represents the direction and magnitude of the correction for the deviation of the working condition. Superimposing it with the historical parameter values ​​can achieve personalized adaptation while maintaining the original process framework.Next, the preset threshold ranges of various parameters for the roller quenching process are read, including the threshold ranges of roller speed, roller acceleration, roller gap, high-pressure zone spray flow rate, low-pressure zone spray flow rate, and upper and lower nozzle flow ratio. The corrected parameter values ​​for each process dimension are then compared with the corresponding parameter threshold ranges to determine whether the corrected parameter values ​​are within the corresponding parameter threshold ranges, and a verification result is generated. The reason for threshold range verification is that the equipment has mechanical structure limitations and safe operating boundaries. The parameter values ​​after superposition and calculation may exceed the allowable operating range of the equipment. Threshold verification is necessary to ensure the feasibility and safety of parameter settings. Subsequently, when the verification result indicates that the corrected parameter value is within the corresponding parameter threshold range, the corrected parameter value is directly determined as the compliant parameter value. When the verification result indicates that the corrected parameter value is lower than the corresponding lower parameter threshold, the lower parameter threshold is determined as the corrected parameter value. When the verification result indicates that the corrected parameter value is higher than the corresponding upper parameter threshold, the upper parameter threshold is determined as the corrected parameter value. The reason for boundary correction when exceeding the limit is that the equipment cannot execute parameter settings beyond physical limits. Boundary correction can approach the theoretical optimal value as closely as possible while ensuring the safe operation of the equipment. Finally, the compliant parameter values ​​and corrected parameter values ​​obtained from each process dimension are integrated according to parameter type. They are combined and packaged in the order of roller speed, roller acceleration, roller gap parameters of each section, high-pressure zone spray flow rate, low-pressure zone spray flow rate, and upper and lower nozzle flow ratio to generate the target operation parameter group. The reason for integration and packaging is that the roller quenching control system needs to receive the complete parameter group to execute the process. The integrated target operation parameter group contains all process parameters that have undergone working condition adaptation and boundary verification and can be directly sent to the control system for execution.

[0045] Step S60: Send the target operating parameters to the roller quenching control system so that the roller quenching control system executes the roller quenching process according to the target operating parameters.

[0046] It should be noted that step S60 includes: associating and binding the target operation parameter group with the steel plate identification information of the target steel plate to generate a process execution instruction package, wherein the process execution instruction package includes the target roller speed, the target roller acceleration, the parameters of each section of the roller gap, the spray flow rate of the target high-pressure zone, the spray flow rate of the target low-pressure zone, and the flow rate ratio of the upper and lower nozzles; determining whether the target steel plate has reached the preset quenching preparation position based on the current position information of the target steel plate; when the target steel plate reaches the preset quenching preparation position, sending the process execution instruction package to the roller quenching control system so that the roller quenching control system performs the roller quenching process on the target steel plate according to the process execution instruction package; receiving the real-time process execution data fed back by the roller quenching control system, wherein the real-time process execution data includes the actual roller speed, the actual roller acceleration, the actual parameters of each section of the roller gap, the actual spray flow rate of the high-pressure zone, the actual spray flow rate of the low-pressure zone, and the actual flow rate ratio of the upper and lower nozzles; comparing and analyzing the real-time process execution data with the target operation parameter group to obtain the parameter execution deviation value; and associating and storing the parameter execution deviation value and the steel plate identification information in the process execution log database.

[0047] It's important to understand that the steel plate identification information is unique to each target steel plate, including batch number, serial number, and production order number. It serves as the core identifier linking the target operating parameter set to the corresponding steel plate. The process execution instruction package is a standardized set of instructions generated by integrating the target operating parameter set and the steel plate identification information. It covers the core control parameters of the entire roll quenching process and can be directly identified and executed by the roll quenching control system. The current position information is the real-time position data of the target steel plate obtained through the position detection device of the roll quenching production line. It is the direct basis for determining whether the steel plate has reached the quenching preparation position. The parameter execution deviation value is the numerical difference calculated by comparing the real-time process execution data with the target operating parameter set one by one. It is the core indicator reflecting the accuracy of process instruction execution. The process execution log database is a database specifically used to store data related to the roll quenching process execution. It can retain parameter execution deviation values ​​and steel plate identification information long-term, providing data support for subsequent process optimization.

[0048] Specifically, the steel plate identification information of the target steel plate is read, and the target roller speed, target roller acceleration, target roller gap parameters, target high-pressure zone spray flow rate, target low-pressure zone spray flow rate, and target upper and lower nozzle flow ratio in the target operation parameter group are associated and bound with the steel plate identification information to generate a process execution instruction package containing parameter data and identification information. This association and binding is necessary because multiple steel plates exist on the production line simultaneously, and a unique identifier must be used to ensure the correspondence between parameters and steel plates, preventing quality accidents caused by mismatched process parameters. Secondly, the current position information of the target steel plate is obtained through the position tracking module of the distributed control system. The position difference between the current position and the preset quenching preparation position is calculated, and it is determined whether the position difference is within the preset arrival threshold range. Position determination is necessary because the roller quenching process can only be triggered when the steel plate reaches a specific position; issuing parameters too early or too late will lead to incorrect process execution timing. Then, when the position difference is within the preset positioning threshold range, the process execution instruction packet is sent to the roller quenching control system via industrial Ethernet. The roller quenching control system then parses the process execution instruction packet and extracts the target roller speed, target roller acceleration, target roller gap parameters, target high-pressure zone spray flow rate, target low-pressure zone spray flow rate, and target upper and lower nozzle flow rate ratio. The system controls the roller operation according to the target roller speed and target roller acceleration, adjusts the roller gap opening according to the target roller gap parameters, controls the cooling water spray according to the target high-pressure zone spray flow rate and target low-pressure zone spray flow rate, and adjusts the cooling intensity of the upper and lower surfaces according to the target upper and lower nozzle flow rate ratio, thereby performing the roller quenching process on the target steel plate. Next, the real-time process execution data uploaded by the roller quenching control system is received through the data feedback interface of the distributed control system. The actual roller speed, actual roller acceleration, actual roller gap parameters of each section, actual high-pressure zone spray flow rate, actual low-pressure zone spray flow rate, and actual upper and lower nozzle flow ratio are read from the real-time process execution data. The reason for receiving real-time feedback data is that the actual execution value of the control system may deviate from the target value due to equipment response delay or mechanical error, and it is necessary to monitor the actual execution status. Next, the difference between the actual roller conveyor speed and the target roller conveyor speed is calculated to obtain the roller speed deviation value; the difference between the actual roller conveyor acceleration and the target roller conveyor acceleration is calculated to obtain the acceleration deviation value; the difference between the actual roller gap parameters of each section and the target roller gap parameters of each section is calculated segment by segment to obtain the roller gap deviation value set; the difference between the actual high-pressure zone spray flow rate and the target high-pressure zone spray flow rate is calculated to obtain the high-pressure flow deviation value; the difference between the actual low-pressure zone spray flow rate and the target low-pressure zone spray flow rate is calculated to obtain the low-pressure flow deviation value; the difference between the actual upper and lower nozzle flow rate ratio and the target upper and lower nozzle flow rate ratio is calculated to obtain the flow ratio deviation value. All deviation values ​​are integrated to form the parameter execution deviation value. The reason for comparing each item is that the execution deviation of different process dimensions has different degrees of impact on the plate shape quality. Recording each item separately facilitates subsequent analysis of the source of deviation and optimization of control accuracy.Finally, the parameter execution deviation value is associated with the steel plate identification information and written into the corresponding storage area of ​​the process execution log database in the order of timestamps. The reason for the associated storage is that the parameter execution deviation reflects the equipment control accuracy and process stability. The data accumulated over a long period of time can be used for equipment maintenance early warning and control system parameter tuning and optimization.

[0049] This embodiment obtains the quenching operation parameters of the target steel plate, then selects the first candidate case group from the production case library. If the parameters meet the standard, the high-frequency historical parameter group is used as the target parameters; otherwise, a second candidate case is determined. The adjustment amount is obtained by consulting the expert rule library based on the parameter difference. After correction calculation, the target parameters are obtained and sent to the quenching control system for execution. This automates parameter setting, improves the accuracy of quenching process parameter setting, reduces manual intervention, lowers the plate shape defect rate, and improves production efficiency and yield.

[0050] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 The method for setting the operating parameters of the roller quenching process, step S40, further includes steps S201 to S206: Step S201: Assign differentiated weighting coefficients to the length, width, thickness and cooling water temperature of the target steel plate specifications and actual environmental parameters to form a weighted calculation system.

[0051] Specifically, the specifications and environmental parameters of the target steel plate are read, and the length, width, and thickness are extracted from the specifications. The cooling water temperature is extracted from the environmental parameters. The influence mechanism of each parameter on the roll quenching process is analyzed. The reason for conducting the influence mechanism analysis is that different parameters have significantly different sensitivities to the quenching cooling process and plate shape quality. It is necessary to determine the weight allocation principle based on physical mechanisms rather than simple averaging. Secondly, based on the core role of steel plate thickness in directly determining heat capacity and cooling rate, a first weight coefficient is assigned to thickness. The first weight coefficient is higher than the weight coefficients of other parameters. The reason for assigning the highest weight to thickness is that for every 0.1 mm change in thickness, the required cooling intensity and roll gap adjustment range will change significantly. The thickness matching accuracy directly determines the sufficiency of the quenching microstructure transformation and is the most critical dimension in the case similarity calculation. Then, based on the significant impact of cooling water temperature on the heat transfer coefficient, a second weighting coefficient is assigned to cooling water temperature. This second weighting coefficient is lower than the first but higher than the weighting coefficients for length and width. The reason for assigning water temperature the second highest weight is that for every 1 degree Celsius fluctuation in water temperature, the convective heat transfer coefficient between the cooling water and the steel plate surface changes accordingly, thus affecting the cooling rate and plate shape control. Furthermore, water temperature fluctuates dynamically with the seasons and equipment conditions, making it a crucial matching dimension. Next, based on the impact of width on the plate shape control boundary conditions and lateral cooling uniformity, a third weighting coefficient is assigned to width. This third weighting coefficient is lower than the second. The reason for assigning width a moderate weight is that width primarily affects the roller support spacing and nozzle coverage. Width deviations within the allowable range can be compensated for through flow distribution adjustments, making it less sensitive than thickness and water temperature. Finally, based on the impact of length on roller running time and longitudinal cooling uniformity, a fourth weighting coefficient is assigned to length. This fourth weighting coefficient is lower than the third. The reason for assigning length the lowest weight is that length primarily affects the residence time of the steel plate in the quenching zone, while the roller speed can be adaptively adjusted according to the thickness. Length deviations within a certain range have a relatively small impact on the final plate shape quality. Finally, the first, second, third, and fourth weighting coefficients are combined in the order of thickness, water temperature, width, and length to form a weighted calculation system. The weighted calculation system is stored in the parameter configuration library for use in the specification similarity calculation step.

[0052] Step S202: Based on the weighted calculation system, the quenching operation parameters of the target steel plate are calculated with the corresponding parameters of all historical production cases in the preset production case library using the weighted Euclidean distance algorithm to obtain the similarity distance value.

[0053] Specifically, the quenching operation parameters of the target steel plate are read, and the first length, first width, first thickness, and first cooling water temperature are extracted from the specification features. The historical specification features corresponding to each historical production case in the preset production case library are read, and the second length, second width, second thickness, and second cooling water temperature are extracted from the historical specification features. These parameters are extracted because they are the four core dimensions in the weighted calculation system, used to quantify the degree of process similarity between the target steel plate and each historical case. Next, the weighted calculation system stored in the parameter configuration library is called to obtain the thickness weight coefficient corresponding to the first thickness, the water temperature weight coefficient corresponding to the first cooling water temperature, the width weight coefficient corresponding to the first width, and the length weight coefficient corresponding to the first length. Differential weight coefficients are used because the influence of each parameter on the quenching process is different, and their importance must be distinguished through weights. Then, based on the above data, the similarity distance value is obtained. The formula for calculating the similarity distance value is: in Represents the similarity distance value. This represents the length weighting coefficient. Indicates the first length. Indicates the second length. This represents the width weighting coefficient. Indicates the first width. Indicates the second width. This represents the thickness weighting coefficient. Indicates the first thickness. Indicates the second thickness. This represents the water temperature weighting coefficient. Indicates the first cooling water temperature. This represents the second cooling water temperature. The weighted Euclidean distance formula is used because this algorithm can simultaneously consider multi-dimensional deviations and differentiated weights. The smaller the calculation result, the closer the target steel plate is to the specifications and characteristics of historical cases, and the more similar the process conditions, thus providing a quantitative basis for selecting the second candidate case.

[0054] Step S203: Sort all similarity distance values ​​in ascending order and select the historical production case with the smallest distance value as the second candidate case.

[0055] Specifically, all calculated similarity distance values ​​between the target steel plate and each historical production case in the preset production case library are collected and summarized. This aims to provide a complete data foundation for subsequent screening and avoid overlooking any potential suitable cases. Then, all the summarized similarity distance values ​​are sorted in ascending order, from smallest to largest. This is because a smaller distance value indicates a higher degree of matching between the case and the target steel plate's operating conditions, and ascending order visually presents the degree of matching, facilitating rapid identification of the optimal case. Finally, among the ascending distance values, the smallest value is selected, and the corresponding historical production case is identified as the second candidate case. This ensures that the selected second candidate case is closest to the target steel plate's operating conditions, providing the most realistic basis for subsequent parameter adjustments and guaranteeing the accuracy of these adjustments.

[0056] Step S204: Calculate the deviation values ​​between the quenching operation parameters of the target steel plate and the corresponding parameters of the second candidate case to form a structured parameter deviation set.

[0057] Specifically, firstly, each quenching operation parameter of the target steel plate—length, width, thickness, and cooling water temperature—is extracted one by one. Then, each corresponding historical parameter from the second candidate case is extracted. Secondly, the target parameter and the second candidate case parameter of the same dimension are numerically calculated to obtain the deviation value of that parameter. This process is repeated for all dimensions. Finally, the deviation values ​​obtained from all dimensions are categorized and organized according to the corresponding parameter dimensions to form a standardized and orderly set of parameter deviations, providing a clear and accurate data foundation for subsequent matching of expert rules.

[0058] Step S205: Input the parameter deviation set into the preset expert rule library for matching to obtain the parameter adjustment rules and adjustment coefficients corresponding to each parameter deviation.

[0059] Specifically, firstly, the parameter deviation set is read, and the first water temperature difference, first thickness difference, and first width difference are extracted from the parameter deviation set. These first water temperature difference, first thickness difference, and first width difference are then classified according to deviation type, forming water temperature deviation items, thickness deviation items, and width deviation items. This classification is necessary because the preset expert rule base stores data in branches according to the type of operating condition deviation, and the classified deviation items can be directly mapped to the corresponding rule branches for querying. Secondly, the water temperature deviation items are input into the water temperature adjustment rule branch of the preset expert rule base. The water temperature adjustment rule branch stores data in segments according to the water temperature difference range. The target water temperature range where the first water temperature difference is located is determined, and the spray flow adjustment direction and spray flow adjustment amplitude corresponding to the target water temperature range are extracted. The spray flow adjustment amplitude is multiplied by the preset water temperature adjustment coefficient to obtain the water temperature-related adjustment component. The reason for querying the water temperature adjustment rule is that the cooling water temperature directly affects the heat transfer coefficient, and the direction of cooling intensity compensation needs to be determined based on the temperature difference. Then, the thickness deviation is input into the thickness adjustment rule branch of the preset expert rule base. The target thickness range where the first thickness difference lies is determined. The roller speed adjustment direction, roller speed adjustment range, roller gap adjustment direction, and roller gap adjustment range corresponding to the target thickness range are extracted. The roller speed adjustment range is multiplied by a preset speed adjustment coefficient to obtain the roller speed adjustment component. The roller gap adjustment range is multiplied by a preset roller gap adjustment coefficient to obtain the roller gap adjustment component. The thickness adjustment rule is queried because thickness determines heat capacity, and thickness deviation needs to be adjusted in conjunction with speed and roller gap to ensure sufficient cooling. Next, the width deviation is input into the width adjustment rule branch of the preset expert rule base. The target width range where the first width difference lies is determined. The upper and lower nozzle flow ratio adjustment direction and flow ratio adjustment range corresponding to the target width range are extracted. The flow ratio adjustment range is multiplied by a preset flow ratio adjustment coefficient to obtain the width-related adjustment component. The width adjustment rule is queried because width affects lateral cooling uniformity, and the upper and lower flow ratio adjustment is needed to suppress plate shape defects. Finally, the water temperature-related adjustment component, the roller speed adjustment component, the roller gap adjustment component, and the width-related adjustment component are integrated to form the first parameter adjustment amount, and the first parameter adjustment amount is output to the parameter superposition calculation step.

[0060] Step S206: Calculate the specific adjustment values ​​corresponding to the quenching operation parameters according to the parameter adjustment rules and adjustment coefficients, and integrate them to form the first parameter adjustment amount.

[0061] Specifically, firstly, the parameter adjustment rules and adjustment coefficients are read. The spray flow rate adjustment direction, spray flow rate adjustment amplitude, and preset water temperature adjustment coefficient are extracted from the water temperature adjustment rules. Similarly, the roller speed adjustment direction, roller speed adjustment amplitude, roller gap adjustment direction, roller gap adjustment amplitude, preset speed adjustment coefficient, and preset roller gap adjustment coefficient are extracted from the thickness adjustment rules. Finally, the upper and lower nozzle flow ratio adjustment direction, flow ratio adjustment amplitude, and preset flow ratio adjustment coefficient are extracted from the width adjustment rules. These rules and coefficients are read because they are the direct basis for calculating specific adjustment values. The direction and amplitude define the nature and magnitude of the adjustment, while the coefficients are used to correct the amplitude based on actual working conditions. Secondly, the positive or negative adjustment is determined based on the spray flow rate adjustment direction. The spray flow rate adjustment amplitude is multiplied by the preset water temperature adjustment coefficient to obtain the spray flow rate adjustment values ​​for the high-pressure zone and the low-pressure zone. The high-pressure and low-pressure zones are distinguished because the cooling intensity differs between the high-pressure and low-pressure zones in the roller quenching process, requiring separate calculations of flow compensation for each zone based on the water temperature deviation. Then, the adjustment direction of the roller conveyor speed is determined to be positive or negative. The roller conveyor speed adjustment range is multiplied by the preset speed adjustment coefficient to obtain the roller conveyor speed adjustment value. Similarly, the adjustment direction of the roller gap is determined to be positive or negative. The roller gap adjustment range is multiplied by the preset roller gap adjustment coefficient to obtain the roller gap adjustment value for each section. The reason for calculating the speed and roller gap adjustment values ​​separately is that thickness deviations require controlling the residence time of the steel plate in the quenching zone through speed control and controlling the cooling water spray distance through roller gap control. The combined effect of the two is necessary to ensure the cooling effect of steel plates of different thicknesses. Next, the adjustment direction of the upper and lower nozzle flow ratio is determined to be positive or negative. The flow ratio adjustment range is multiplied by the preset flow ratio adjustment coefficient to obtain the upper and lower nozzle flow ratio adjustment value. The reason for calculating the flow ratio adjustment value is that width deviations can lead to uneven transverse temperature distribution of the steel plate. It is necessary to adjust the cooling intensity ratio of the upper and lower surfaces to suppress warping and wave defects. Next, the corresponding roller conveyor acceleration adjustment value is calculated based on the roller conveyor speed adjustment value. The roller conveyor acceleration adjustment value is the ratio of the roller conveyor speed adjustment value to the preset acceleration time threshold. The reason for calculating the acceleration adjustment value is that speed changes need to be smoothly transitioned through acceleration to avoid sudden speed changes impacting the stability and shape quality of the steel plate. Finally, the high-pressure zone spray flow adjustment value, low-pressure zone spray flow adjustment value, roller conveyor speed adjustment value, roller conveyor acceleration adjustment value, roller gap adjustment value for each section, and upper and lower nozzle flow ratio adjustment value are integrated according to the process dimension to form the first parameter adjustment value, which includes six parameter components.

[0062] This embodiment constructs a weighted calculation system by configuring differentiated weights for specification features and cooling water temperature, uses a weighted Euclidean distance algorithm to obtain similarity distance values, selects the historical case with the smallest distance as the second candidate case, calculates parameter deviations and forms a structured set, matches it with an expert rule base to obtain adjustment rules and coefficients, and finally calculates and generates the first parameter adjustment amount. This improves the case matching accuracy, realizes parameter deviation quantification and intelligent adjustment, ensures accurate and reliable parameter settings, and improves the stability of the quenching process and production efficiency.

[0063] Based on the first embodiment of this application, this application also provides an operating parameter setting device for a roller quenching process. Please refer to... Figure 3 The device includes: The acquisition module 10 is used to acquire the quenching operation parameters of the target steel plate. The quenching operation parameters include dimensional characteristics and actual environmental parameters. The dimensional characteristics include length, width, thickness and steel type, and the actual environmental parameters include cooling water temperature.

[0064] The filtering module 20 is used to filter the first candidate case group that meets the preset matching conditions from the preset production case library according to the specification characteristics. The preset production case library contains historical production cases, and each historical production case includes historical specification characteristics, historical environmental parameters, historical operating parameter groups and historical flatness test results.

[0065] The first parameter determination module 30 is used to select the historical operation parameter group with the highest frequency from the first candidate case group as the target operation parameter group when the number of cases in the first candidate case group reaches the preset case number threshold.

[0066] The second parameter determination module 40 is used to determine a second candidate case from the preset production case library when the number of cases in the first candidate case group does not reach the preset case number threshold, and to query the preset expert rule library according to the difference between the quenching operation parameters and the corresponding quenching operation parameters in the second candidate case to obtain the first parameter adjustment amount.

[0067] The correction module 50 is used to perform parameter correction calculations on the historical operation parameter group of the second candidate case and the first parameter adjustment amount to obtain the target operation parameters.

[0068] The sending module 60 is used to send the target operating parameters to the roller quenching control system so that the roller quenching control system can execute the roller quenching process according to the target operating parameters.

[0069] The roller quenching process operation parameter setting device provided in this application adopts the roller quenching process operation parameter setting method in the above embodiments, which can solve the technical problem of how to improve the accuracy of quenching process parameter setting. Compared with the prior art, the beneficial effects of the roller quenching process operation parameter setting device provided in this application are the same as the beneficial effects of the roller quenching process operation parameter setting method provided in the above embodiments, and other technical features in the roller quenching process operation parameter setting device are the same as the features disclosed in the above embodiments, and will not be repeated here.

[0070] This application provides an operating parameter setting device for a roller quenching process. The operating parameter setting device for the roller quenching process includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the operating parameter setting method for the roller quenching process in the above embodiment 1.

[0071] The following is for reference. Figure 4 The diagram illustrates a structural schematic of an operating parameter setting device suitable for implementing the roller quenching process in the embodiments of this application. The operating parameter setting device for the roller quenching process in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 4 The operating parameter setting device for the roller quenching process shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0072] like Figure 4As shown, the operation parameter setting device for the roller quenching process may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1002 or the program loaded from the storage device 1003 into the random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the roller quenching process operation parameter setting device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the roller quenching process operation parameter setting device to wirelessly or wiredly communicate with other devices to exchange data. Although various roller quenching process operation parameter setting devices are shown in the figures, it should be understood that it is not required to implement or possess all of them. More or fewer may be implemented alternatively.

[0073] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0074] The roller quenching process operation parameter setting device provided in this application adopts the roller quenching process operation parameter setting method in the above embodiments, which can solve the technical problem of how to improve the accuracy of quenching process parameter setting. Compared with the prior art, the beneficial effects of the roller quenching process operation parameter setting device provided in this application are the same as the beneficial effects of the roller quenching process operation parameter setting method provided in the above embodiments, and other technical features in the roller quenching process operation parameter setting device are the same as the features disclosed in the previous embodiment method, and will not be repeated here.

[0075] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0076] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0077] This application provides a computer-readable medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the operation parameter setting method for the roller quenching process in the above embodiments.

[0078] The computer-readable medium provided in this application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor devices, or any combination thereof. More specific examples of computer-readable media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable medium may be any tangible medium containing or storing a program that can be executed by instructions, used by a device, or used in conjunction with it. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0079] The aforementioned computer-readable medium may be included in the operating parameter setting device for the roller quenching process; or it may exist independently and not be assembled into the operating parameter setting device for the roller quenching process.

[0080] The aforementioned computer-readable medium carries one or more programs that, when executed by the roller quenching process operation parameter setting device, enable the roller quenching process operation parameter setting device to write computer program code for performing the operations of this application in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0081] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of this application. In this regard, all blocks in the flowcharts or block diagrams may represent a module, segment, or portion of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that all blocks in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using dedicated hardware-based implementations that perform the specified functions or operations, or using a combination of dedicated hardware and computer instructions.

[0082] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0083] The readable medium provided in this application is a computer-readable medium, which stores computer-readable program instructions (i.e., a computer program) for executing the above-described method for setting operating parameters for the roller quenching process, and can solve the technical problem of how to improve the accuracy of quenching process parameter settings. Compared with the prior art, the beneficial effects of the computer-readable medium provided in this application are the same as the beneficial effects of the method for setting operating parameters for the roller quenching process provided in the above embodiments, and will not be repeated here.

[0084] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method for setting operating parameters for the roller quenching process.

[0085] The computer program product provided in this application can solve the technical problem of how to improve the accuracy of quenching process parameter settings. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the operation parameter setting method for the roller quenching process provided in the above embodiments, and will not be repeated here.

[0086] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method of setting operating parameters for a roll quenching process, characterized by, The method includes: The quenching operation parameters of the target steel plate are obtained, wherein the quenching operation parameters include dimensional characteristics and actual environmental parameters. The dimensional characteristics include length, width, thickness and steel type, and the actual environmental parameters include cooling water temperature. Based on the specified characteristics, a first candidate case group that meets the preset matching conditions is selected from the preset production case library, wherein the preset production case library contains historical production cases, and each historical production case includes historical specified characteristics, historical environmental parameters, historical operating parameter groups and historical flatness detection results; When the number of cases in the first candidate case group reaches the preset case number threshold, the historical operation parameter group with the highest frequency is selected from the first candidate case group as the target operation parameter group. When the number of cases in the first candidate case group does not reach the preset case number threshold, a second candidate case is determined from the preset production case library, and the preset expert rule library is queried according to the difference between the quenching operation parameter and the corresponding quenching operation parameter in the second candidate case to obtain the first parameter adjustment amount; The target operation parameters are obtained by performing parameter correction calculations on the historical operation parameter group of the second candidate case and the first parameter adjustment amount; The target operating parameters are sent to the roller quenching control system so that the roller quenching control system executes the roller quenching process according to the target operating parameters.

2. The method as described in claim 1, characterized in that, The step of selecting the first candidate case group that meets the preset matching conditions from the preset production case library based on the specification characteristics includes: The historical production cases in the preset production case library are divided into a first preset duration and a second preset duration based on production time, and the case subset with the first preset duration is retrieved first. Historical production cases that match the target steel plate type are selected from the priority subset of cases to form a steel type matching case set; In the steel type matching case set, cases whose thickness deviation from the target steel plate thickness is within a preset thickness range are selected to form a thickness matching case set; Cases whose width is within a preset width range of the target steel plate width and whose length is within a preset length range of the target steel plate length are selected from the thickness matching case set to form a dimension matching case set; Extract all historical production cases from the dimension-matching case set and integrate them to determine the first candidate case group; When the first preset duration subset of cases fails to filter out the dimension-matching case set, the second preset duration subset of cases is retrieved and the filtering steps for steel type, thickness, width, and length are repeated to obtain the first candidate case group.

3. The method as described in claim 1, characterized in that, The step of selecting the most frequent historical operation parameter group from the first candidate case group as the target operation parameter group includes: Extract the historical operation parameter groups and corresponding historical flatness detection results for all historical production cases in the first candidate case group; Count the frequency of occurrence of each historical operation parameter group in the first candidate case group, and generate a parameter group statistical list with the occurrence frequency; The parameter group statistics list is sorted in descending order of frequency of occurrence. The historical operation parameter group with the highest frequency is selected as the initial parameter group. The historical flatness detection results of all historical production cases corresponding to the initial parameter set are verified to obtain a parameter set that passes the verification. When there are multiple parallel cases with the same frequency in the initial parameter group, the historical operation parameter group with the latest production time is selected as the candidate parameter group. The parameter group or candidate parameter group that passes the verification is determined as the target operation parameter group.

4. The method as described in claim 1, characterized in that, The step of determining a second candidate case from the preset production case library and querying the preset expert rule library based on the difference between the quenching operation parameters and the corresponding quenching operation parameters in the second candidate case to obtain the first parameter adjustment amount includes: Differentiated weighting coefficients are assigned to the length, width, thickness, and cooling water temperature of the target steel plate specifications and actual environmental parameters to form a weighted calculation system; Based on the weighted calculation system, the weighted Euclidean distance algorithm is used to calculate the quenching operation parameters of the target steel plate and the corresponding parameters of all historical production cases in the preset production case library to obtain the similarity distance value. All similarity distance values ​​are sorted in ascending order, and the historical production case with the smallest distance value is selected as the second candidate case. Calculate the deviation values ​​between the quenching operation parameters of the target steel plate and the corresponding parameters of the second candidate case to form a structured parameter deviation set; The parameter deviation set is input into a preset expert rule base for matching to obtain the parameter adjustment rules and adjustment coefficients corresponding to each parameter deviation. The specific adjustment values ​​corresponding to the quenching operation parameters are calculated based on the parameter adjustment rules and adjustment coefficients, and integrated to form the first parameter adjustment amount.

5. The method as described in claim 4, characterized in that, Before the step of inputting the parameter deviation set into a preset expert rule base for matching to obtain the parameter adjustment rules and adjustment coefficients corresponding to each parameter deviation, the following steps are included: Historical data on manual adjustment of process parameters during the roller quenching production process were collected, and the working condition deviation conditions triggered by the adjustment and the corresponding parameter adjustment amount were extracted to form the original adjustment dataset. The original adjusted dataset is preprocessed to obtain a standardized adjusted dataset; The deviation dimensions of steel grade, specification, and cooling water temperature, as well as the corresponding adjustment rules for roller conveyor, roller gap, and spray flow rate, are extracted from the standardized adjustment dataset to form a basic rule set. By combining the experience of process engineers, parameter adjustment coefficients are configured for each deviation dimension in the basic rule set to obtain the optimized basic rule set. The optimized basic rule set is classified and stored according to the type of operating condition deviation to construct an initial expert rule base; The initial expert rule base is put into production trial operation, and the rules and adjustment coefficients are iteratively optimized according to the process effect adjusted by actual parameters to form a preset expert rule base.

6. The method as described in claim 1, characterized in that, The step of performing parameter correction calculations on the historical operation parameter group of the second candidate case and the first parameter adjustment amount to obtain the target operation parameters includes: The historical operation parameter group of the second candidate case is split to obtain the historical parameter values ​​of each process dimension, and then integrated to form a set of historical parameter dimensions; The adjustment amount of the first parameter is broken down to obtain the adjustment value of each process dimension corresponding to the historical parameter dimension set, and then integrated to form the adjustment value dimension set. The historical parameter values ​​in the historical parameter dimension set and the corresponding adjustment values ​​in the adjustment value dimension set are subjected to dimensional correction operations according to the process dimension to obtain the corrected parameter values ​​for each process dimension. The corrected parameter values ​​for each process dimension and the preset threshold ranges for each parameter in the roller quenching process are verified to obtain the verification results. When the verification result shows that the corrected parameter value does not exceed the corresponding parameter threshold range, a compliant parameter value is obtained; When the verification result indicates that the corrected parameter value exceeds the corresponding parameter threshold range, the parameter value is corrected according to the parameter threshold range to obtain the corrected parameter value. The corrected parameter values ​​and compliant parameter values ​​are integrated into a target operating parameter group.

7. The method as described in claim 1, characterized in that, The step of sending the target operating parameters to the roller quenching control system so that the roller quenching control system executes the roller quenching process according to the target operating parameters includes: The target operation parameter group is associated and bound with the steel plate identification information of the target steel plate to generate a process execution instruction package, wherein the process execution instruction package includes the target roller speed, the target roller acceleration, the target roller gap parameters, the target high pressure zone spray flow rate, the target low pressure zone spray flow rate, and the target upper and lower nozzle flow rate ratio; Based on the current position information of the target steel plate, determine whether the target steel plate has reached the preset quenching preparation position; When the target steel plate reaches the preset quenching preparation position, the process execution instruction package is sent to the roller quenching control system so that the roller quenching control system performs the roller quenching process on the target steel plate according to the process execution instruction package. Receive real-time process execution data fed back by the roller quenching control system, wherein the real-time process execution data includes actual roller speed, actual roller acceleration, actual roller gap parameters of each section, actual high-pressure zone spray flow rate, actual low-pressure zone spray flow rate, and actual upper and lower nozzle flow rate ratio; The real-time process execution data is compared and analyzed with the target operating parameter set to obtain the parameter execution deviation value; The parameter execution deviation value and the steel plate identification information are associated and stored in the process execution log database.

8. A device for setting operating parameters for a roller quenching process, characterized in that, The device includes: The acquisition module is used to acquire the quenching operation parameters of the target steel plate, wherein the quenching operation parameters include dimensional characteristics and actual environmental parameters. The dimensional characteristics include length, width, thickness and steel type, and the actual environmental parameters include cooling water temperature. The filtering module is used to filter out a first candidate case group that meets the preset matching conditions from the preset production case library according to the specification characteristics. The preset production case library contains historical production cases, and each historical production case includes historical specification characteristics, historical environmental parameters, historical operating parameter groups and historical flatness detection results. The first parameter determination module is used to select the most frequent historical operation parameter group from the first candidate case group as the target operation parameter group when the number of cases in the first candidate case group reaches a preset case number threshold. The second parameter determination module is used to determine a second candidate case from the preset production case library when the number of cases in the first candidate case group does not reach the preset case number threshold, and to query the preset expert rule library according to the difference between the quenching operation parameter and the corresponding quenching operation parameter in the second candidate case to obtain the first parameter adjustment amount; The correction module is used to perform parameter correction calculations on the historical operation parameter group of the second candidate case and the first parameter adjustment amount to obtain the target operation parameters; The sending module is used to send the target operating parameters to the roller quenching control system, so that the roller quenching control system executes the roller quenching process according to the target operating parameters.

9. A device for setting operating parameters for a roller quenching process, characterized in that, The device includes: a memory, a processor, and an operation parameter setting program for the roller quenching process stored in the memory and running on the processor, wherein the operation parameter setting program for the roller quenching process is configured to implement the steps of the operation parameter setting method for the roller quenching process as described in any one of claims 1-7.

10. A storage medium, characterized in that, The storage medium stores an operation parameter setting program for the roller quenching process. When the operation parameter setting program for the roller quenching process is executed by the processor, it implements the steps of the operation parameter setting method for the roller quenching process as described in any one of claims 1-7.

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