Metal casting cooling control method and system

Abstract

The invention discloses a metal casting cooling control method and system, and relates to the related field of metal casting. The method comprises the steps that basic casting information is collected; constructing a first screening constraint; constructing a second screening constraint based on a cooling acceptance standard; performing data screening in the cooling record database according to the first screening constraint; performing qualification screening on the memory database according to the second screening constraint to generate a qualified memory database and an abnormal memory database; cooling control parameter fine screening is carried out, and a target cooling control parameter adjustable interval set is generated; performing control parameter target optimization to obtain a target cooling control parameter set; and synchronizing to a control unit to execute cooling control. The technical problems that existing metal casting cooling control is low in control precision and cannot meet the high-precision requirement are solved, and the technical effects that high-precision cooling control is achieved, and the high-precision requirement is met are achieved.

Description

Technical Field

[0001] The present application relates to the field of metal casting, and in particular to a metal casting cooling control method and system. Background Art

[0002] After casting, metal castings need to go through a precise cooling process to achieve the expected physical and mechanical properties. The cooling process of metal castings is affected by many factors, such as casting material, geometric structure and geometric dimensions, which together determine the cooling rate and temperature distribution, thus affecting the quality and performance of the castings. Traditional metal casting cooling control methods are mostly based on fixed control parameters or empirical formulas. These methods cannot accurately reflect the real-time status of the castings during the cooling process, and are difficult to adapt to the differences between different castings.

[0003] In the current related technologies, the cooling control of metal castings has the technical problem of low control accuracy and cannot meet the high-precision requirements. Summary of the invention

[0004] The present application provides a metal casting cooling control method and system, which adopts the following technical means: constructing a first screening constraint according to basic casting information of a target metal casting, constructing a second screening constraint according to cooling acceptance criteria of the target metal casting, using the first screening constraint and the second screening constraint to perform qualified screening on a cooling record database and a memory database respectively, performing fine screening of cooling control parameters according to a qualified memory database and an abnormal memory database, and optimizing control parameter targets in a set of adjustable intervals of target cooling control parameters, thereby achieving a technical effect of realizing high-precision cooling control and meeting high-precision requirements.

[0005] The present application provides a metal casting cooling control method, comprising: Collect basic casting information of the target metal casting, wherein the basic casting information includes casting material data, casting geometry and casting geometry; construct a first screening constraint based on the casting material data, casting geometry and casting geometry; construct a second screening constraint based on the cooling acceptance standard of the target metal casting; retrieve a cooling record database, perform data screening in the cooling record database according to the first screening constraint, and obtain a memory database; perform qualified screening on the memory database according to the second screening constraint, and generate a qualified memory database and an abnormal memory database; perform fine screening of cooling control parameters according to the qualified memory database and the abnormal memory database, and generate a target cooling control parameter adjustable interval set; perform control parameter target optimization in the target cooling control parameter adjustable interval set to obtain a target cooling control parameter set; synchronize the target cooling control parameter set to a control unit, and execute cooling control of the target metal casting.

[0006] In a possible implementation, the following processing is performed: Perform tolerance interval screening on K qualified cooling control parameter sets among the K qualified cooling record data in the qualified memory database to generate a cooling control parameter tolerance interval set; perform abnormal interval screening on L abnormal cooling control parameter sets among the L abnormal cooling record data in the abnormal memory database to generate an abnormal control parameter tolerance interval set; use the abnormal control parameter tolerance interval set to perform parameter fine screening on the cooling control parameter tolerance interval set to generate a target cooling control parameter adjustable interval set.

[0007] In a possible implementation, K qualified cooling control parameter sets in the K qualified cooling record data in the qualified memory database are screened by tolerance intervals to generate a cooling control parameter tolerance interval set, and the following processing is performed: The K qualified cooling record data are retrieved with the cooling control parameter as the index to obtain a plurality of qualified cooling control parameter cluster sets, wherein each qualified cooling control parameter cluster set corresponds to a cooling control parameter; a plurality of qualified box plots are constructed based on the plurality of qualified cooling control parameter cluster sets; the interquartile ranges of the plurality of qualified box plots are calculated, and the calculated results are multiplied by a preset filtering step to obtain a plurality of tolerance filtering steps; based on the plurality of tolerance filtering steps, the plurality of qualified cooling control parameter cluster sets are retrieved to obtain a plurality of qualified cooling control parameter cluster intervals; the plurality of qualified cooling control parameter cluster intervals are used as a cooling control parameter tolerance interval set.

[0008] In a possible implementation, based on the multiple tolerance screening steps, searching is performed in the multiple qualified cooling control parameter clustering sets to obtain multiple qualified cooling control parameter clustering intervals, and the following processing is performed: Respectively calculate multiple cluster centers of the multiple qualified cooling control parameter cluster sets; take the multiple cluster centers as starting points, and construct multiple first search intervals according to the multiple tolerance screening steps as search radius; again take the multiple cluster centers as starting points, and expand the multiple first search intervals according to the multiple tolerance screening steps to generate multiple second search intervals; respectively perform interval density transition authentication on the multiple first search intervals and the multiple second search intervals, and when the authentication is passed, stop expanding, and use the multiple search intervals corresponding to the multiple interval density maximum values ​​as multiple qualified cooling control parameter cluster intervals.

[0009] In a possible implementation, the following processing is performed: Perform similarity analysis on multiple cooling record data in the memory database to obtain a database consistency factor; determine whether the consistency factor meets the preset requirements, and if not, obtain a database expansion instruction; and supplement the memory database with data according to the database expansion instruction.

[0010] In a possible implementation, the following processing is performed: Construct a cooling record database, wherein the cooling record database includes multiple sample points; obtain a target constraint point in the cooling record database according to the first screening constraint; collect multiple neighboring sample points from the multiple sample points whose distance to the target constraint point is within a preset distance threshold, and obtain the memory database based on the multiple neighboring sample points.

[0011] In a possible implementation, the following processing is performed: Acquire a plurality of sample cooling record data, wherein the plurality of sample cooling record data include a plurality of casting material data, a plurality of casting geometric structures and a plurality of casting geometric dimensions; input the plurality of casting material data, the plurality of casting geometric structures and the plurality of casting geometric dimensions into a three-dimensional space coordinate system to generate a plurality of sample points; and construct the cooling record database according to the plurality of sample points.

[0012] The present application also provides a metal casting cooling control system, comprising: A basic casting information acquisition module, the basic casting information acquisition module is used to acquire basic casting information of a target metal casting, wherein the basic casting information includes casting material data, casting geometry and casting geometry; a first screening constraint construction module, the first screening constraint construction module is used to construct a first screening constraint according to the casting material data, casting geometry and casting geometry; a second screening constraint construction module, the second screening constraint construction module is used to construct a second screening constraint based on the cooling acceptance standard of the target metal casting; a memory database acquisition module, the memory database acquisition module is used to retrieve a cooling record database, perform data screening in the cooling record database according to the first screening constraint, and obtain a memory database; a qualified screening module, the qualified A grid screening module is used to perform qualified screening on the memory database according to the second screening constraint, and generate a qualified memory database and an abnormal memory database; a target cooling control parameter adjustable interval set generation module, the target cooling control parameter adjustable interval set generation module is used to perform fine screening of cooling control parameters according to the qualified memory database and the abnormal memory database, and generate a target cooling control parameter adjustable interval set; a target cooling control parameter set acquisition module, the target cooling control parameter set acquisition module is used to perform control parameter target optimization in the target cooling control parameter adjustable interval set, and obtain a target cooling control parameter set; a cooling control module, the cooling control module is used to synchronize the target cooling control parameter set to a control unit, and execute cooling control of the target metal casting.

[0013] A metal casting cooling control method and system proposed in the present application first collects basic casting information of the target metal casting, wherein the basic casting information includes casting material data, casting geometry and casting geometry, then constructs a first screening constraint based on the casting material data, casting geometry and casting geometry, and then constructs a second screening constraint based on the cooling acceptance standard of the target metal casting, and then retrieves the cooling record database, performs data screening in the cooling record database according to the first screening constraint, obtains a memory database, and then performs qualified screening on the memory database according to the second screening constraint, generates a qualified memory database and an abnormal memory database, and then performs fine screening of cooling control parameters based on the qualified memory database and the abnormal memory database, generates a target cooling control parameter adjustable interval set, and then performs control parameter target optimization in the target cooling control parameter adjustable interval set to obtain a target cooling control parameter set, and finally synchronizes the target cooling control parameter set to the control unit, executes cooling control of the target metal casting, and achieves the technical effect of realizing high-precision cooling control and meeting high-precision requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic flow chart of a metal casting cooling control method provided in an embodiment of the present application.

[0016] Figure 2 A schematic structural diagram of a metal casting cooling control system provided in an embodiment of the present application.

[0017] Explanation of the accompanying drawings: basic casting information acquisition module 10, first screening constraint construction module 20, second screening constraint construction module 30, memory database acquisition module 40, qualified screening module 50, target cooling control parameter adjustable interval set generation module 60, target cooling control parameter set acquisition module 70, cooling control module 80. DETAILED DESCRIPTION

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0019] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0020] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0021] The present application embodiment provides a method for controlling cooling of a metal casting, such as Figure 1 As shown, the method includes: Step S100, collecting basic casting information of the target metal casting, wherein the basic casting information includes casting material data, casting geometry and casting geometry. Specifically, the casting material data refers to the chemical composition, physical properties and other properties of the metal material used in the target metal casting; the casting geometry refers to the shape characteristics such as the appearance and internal structure of the target metal casting; the casting geometry refers to the specific dimensions of the length, width, height and other parts of the target metal casting. Specifically, confirm the target metal casting and prepare corresponding measuring tools and equipment, such as metal analyzers, calipers, gauges, 3D scanners, etc. Use a metal analyzer or chemical composition testing equipment to sample the target metal casting and analyze its chemical composition, including the content of the main alloy elements, impurity content, etc., which constitute the casting material data; use a 3D scanner or measuring equipment to scan or measure the target metal casting to obtain its 3D geometry data; use calipers, gauges and other measuring tools to accurately measure the key dimensions of the target metal casting and record the measurement results, including key dimensions such as length, width, height, wall thickness, etc. The collected casting material data, casting geometric structure and casting geometric dimensions are integrated to form complete basic casting information.

[0022] Step S200, constructing a first screening constraint according to the casting material data, casting geometry and casting geometry. Specifically, analyzing the casting material data, determining the main alloying elements, impurity content and the influence on the thermophysical properties of the target metal casting, and evaluating the key performance parameters of the casting material such as thermal conductivity, melting point, thermal expansion coefficient, etc. Analyzing the casting geometry, determining the overall shape, internal structure and wall thickness of the casting, and evaluating the influence of the casting geometry on the heat transfer path and temperature distribution, for example, the thick wall part requires a longer cooling time. According to the casting geometry, calculating the casting volume, surface area and other key parameters, and analyzing the influence of these key parameters on the casting cooling rate and cooling uniformity. Comprehensively analyzing the influence of casting material, geometry and size on the cooling process, generating a series of screening conditions, including material type, thermal conductivity range, geometry characteristics (such as wall thickness, structural complexity), size range, etc., converting the screening conditions into executable mathematical models or algorithms, and obtaining the first screening constraint, which is used to screen out cooling records similar or related to the target metal casting from the cooling record database.

[0023] Step S300, based on the cooling acceptance criteria of the target metal casting, a second screening constraint is constructed. Specifically, the relevant technical standards, process specifications or customer requirements are consulted to determine the various performance indicators that the target metal casting needs to achieve after cooling, including the temperature distribution, hardness, organizational structure, residual stress, etc. of the casting. The various indicators in the cooling acceptance criteria are analyzed to determine the influence of each indicator on the performance of the casting and the relationship between each other, evaluate the importance and priority of each indicator, and determine which indicators are critical and must be met, and which indicators are secondary and can have a certain tolerance. According to the cooling acceptance criteria, a series of screening conditions are generated, including temperature distribution range, hardness range, organizational structure characteristics, residual stress level, etc., which are used to screen out qualified cooling records that meet the cooling acceptance criteria from the memory database, and convert the screening conditions into quantifiable indicators or parameters for numerical comparison and screening. For example, the temperature distribution range is converted into a specific temperature threshold, and the hardness range is converted into a specific hardness value range. The quantified screening conditions are integrated into a model to form a second screening constraint.

[0024] Step S400, retrieve the cooling record database, perform data screening in the cooling record database according to the first screening constraint, and obtain a memory database. Specifically, the cooling record database is a database that stores a large amount of cooling record data of metal castings, including the material, geometry, size, cooling process parameters, and performance data after cooling of the castings. Use a database query tool or programming language (such as SQL) to connect to the cooling record database, convert the first screening constraint (the screening condition based on the casting material data, geometry and geometry) into a filter condition in the database query statement, execute the query statement, and screen out records that meet the first screening constraint from the cooling record database. Perform further data cleaning and sorting on the screened records, extract cooling record data similar to or related to the current target metal casting, including cooling process parameters and performance data after cooling, etc., and store the screened and extracted cooling record data in a new database, which is the memory database.

[0025] In a possible implementation, step S400 further includes step S410, performing similarity analysis on multiple cooling record data in the memory database to obtain a database consistency factor. Specifically, multiple cooling record data are extracted from the memory database, and these cooling record data include different cooling conditions, temperature records, timestamps and other information. Key features are extracted from each cooling record data, including temperature change trends, maximum / minimum temperature values, cooling time, etc. during the cooling process. Similarity between these cooling record data is calculated using similarity measurement methods (such as cosine similarity, Euclidean distance, etc.). Based on the similarity calculation results between all cooling record data, a database consistency factor is obtained by weighted average, median, etc. The consistency factor reflects the overall similarity between the cooling record data in the memory database. Step S420, determine whether the consistency factor meets the preset requirements. If not, obtain a database expansion instruction. Specifically, according to actual needs or experience, one or more preset requirements for the consistency factor are set (such as the consistency factor must be less than a certain threshold), and the calculated consistency factor is compared with the preset requirements. If the consistency factor does not meet the preset requirements (i.e., the consistency is high), a database expansion instruction is generated to guide the data supplement operation of the memory database. Step S430, the memory database is supplemented with data according to the database expansion instruction. Specifically, according to the requirements of the database expansion instruction, new cooling record data are collected. These new cooling record data can come from new experiments, tests or cooling systems in actual operation. The new data is added to the memory database to enrich the content of the memory database. This implementation method can timely discover the data shortage or consistency problems that may exist in the memory database by performing similarity analysis and consistency evaluation on the cooling record data in the memory database. When the consistency factor does not meet the preset requirements, it means that the data in the memory database is insufficient to fully reflect different cooling conditions. At this time, the integrity and accuracy of the memory database are enhanced by data supplementation, thereby achieving the technical effect of improving the accuracy and reliability of subsequent analysis.

[0026] In a possible implementation, step S400 further includes step S440, constructing a cooling record database, wherein the cooling record database includes multiple sample points. Specifically, historical cooling record data from a cooling system in an experiment, test or actual operation is collected, the collected data is cleaned, deduplicated and formatted to ensure the quality and consistency of the data, and the sorted data is stored as a sample point in the cooling record database, each sample point is a data record in the cooling record database, representing the record data under a specific cooling condition, and may contain multiple attributes, such as cooling conditions, temperature records, timestamps, etc. Step S450, according to the first screening constraint, obtain the target constraint point in the cooling record database. Specifically, the first screening constraint is applied in the cooling record database to screen out sample points that meet the conditions as target constraint points. Step S460, collect multiple neighboring sample points from the multiple sample points whose distance to the target constraint point is within a preset distance threshold, and obtain the memory database based on the multiple neighboring sample points. Specifically, the distance from each sample point in the cooling record database to the target constraint point is calculated (based on the similarity or actual distance between the sample point attributes), and according to the preset distance threshold, the sample points that are closer to the target constraint point are screened out as neighboring sample points, and the screened neighboring sample points are used as the content of the memory database, that is, the memory database contains the target constraint point and the cooling record data similar to the target constraint point. This implementation method expands the content of the memory database by introducing neighboring sample points, so that it contains more records that are similar to the target constraint point but not completely the same, achieving the technical effect of enriching the memory database and helping to capture potential patterns.

[0027] In a possible implementation, step S440 further includes step S441, obtaining a plurality of sample cooling record data, wherein the plurality of sample cooling record data includes a plurality of casting material data, a plurality of casting geometric structures, and a plurality of casting geometric dimensions. Specifically, a plurality of sample cooling record data are collected from a production or test environment, the sample cooling record data come from different casting batches, different production conditions, or different time periods, and each sample cooling record data includes three parts: casting material data, casting geometric structures, and casting geometric dimensions. Step S442, inputting the plurality of casting material data, the plurality of casting geometric structures, and the plurality of casting geometric dimensions into a three-dimensional space coordinate system, and generating a plurality of sample points. Specifically, the collected casting material data, casting geometric structures, and casting geometric dimensions are converted into numerical values ​​or vectors that can be represented in a three-dimensional space coordinate system, and a unique coordinate point is assigned to each sample in the three-dimensional space coordinate system according to the converted numerical values ​​or vectors, and the coordinate point represents the comprehensive characteristics of the sample in terms of material, structure, and size, and the coordinate points of all samples in the three-dimensional space coordinate system are gathered together to form a plurality of sample points. Step S443, construct the cooling record database according to the multiple sample points. Specifically, the generated multiple sample points are stored in the database to form a cooling record database. This implementation method reduces data redundancy and storage space requirements by merging multiple feature dimensions into a three-dimensional coordinate point, achieving the technical effect of efficiently storing and managing a large amount of sample data in the cooling record database.

[0028] Step S500, perform qualified screening on the memory database according to the second screening constraint, and generate a qualified memory database and an abnormal memory database. Specifically, the memory database is loaded into a data processing environment, the second screening constraint is converted into a data processing logic or query statement, each record in the memory database is traversed, and it is checked whether it meets the performance index requirements in the second screening constraint. According to whether each record meets the second screening constraint, it is classified as a qualified record or an abnormal record. A qualified record refers to a record that meets all cooling acceptance criteria, and an abnormal record refers to a record that does not meet at least one cooling acceptance criterion. All qualified records are extracted and stored in a new database, which is a qualified memory database. The qualified memory database contains records that are similar to the cooling process of the target metal casting and meet the performance standards; all abnormal records are extracted and stored in another database, which is an abnormal memory database.

[0029] Step S600, perform fine screening of cooling control parameters according to the qualified memory database and the abnormal memory database, and generate a target cooling control parameter adjustable interval set. Specifically, analyze the cooling control parameter records in the qualified memory database, such as cooling rate, temperature set point, cooling medium flow, etc., analyze the relationship between these cooling control parameters and the cooling performance of the target metal casting, and determine the key control parameters that affect the casting performance. Compare the cooling control parameter records in the qualified memory database and the abnormal memory database, identify the key control parameters that have significant differences between the qualified and abnormal records, and for the screened key control parameters, determine the feasible or effective interval of each cooling control parameter based on the records in the qualified memory database and the value range or distribution of the key control parameters in the qualified records. Combine the feasible intervals of all key control parameters to form a target cooling control parameter adjustable interval set, which is the basis for cooling process control and optimization and is used to guide the cooling process of the target metal casting.

[0030] In a possible implementation, step S600 further includes step S610, performing tolerance interval screening on K qualified cooling control parameter sets in the K qualified cooling record data in the qualified memory database to generate a cooling control parameter tolerance interval set. Specifically, K qualified cooling record data are read from the qualified memory database, and a corresponding cooling control parameter set is extracted from each qualified cooling record data. Based on the K qualified cooling control parameter sets, the tolerance interval of each cooling control parameter is calculated according to the distribution of parameter values ​​(such as mean ± standard deviation) or expert experience, that is, within the qualified parameter range, the parameter value is allowed to have a certain fluctuation without affecting the cooling effect. The tolerance interval of each cooling control parameter is integrated into a set, which is the cooling control parameter tolerance interval set. Step S620, performing abnormal interval screening on L abnormal cooling control parameter sets in the L abnormal cooling record data in the abnormal memory database to generate an abnormal control parameter tolerance interval set. Specifically, read L abnormal cooling record data from the abnormal memory database, extract the corresponding cooling control parameter set from each abnormal cooling record data, analyze the abnormal cooling control parameter set, find out the parameters or parameter combinations that cause the cooling abnormality, and determine the parameter value interval that causes the cooling abnormality based on the analysis results of the abnormal parameters. This interval may be a specific range or one or more discrete points. Integrate the determined abnormal intervals into a set, which is the abnormal control parameter tolerance interval set. Step S660, use the abnormal control parameter tolerance interval set to perform parameter fine screening on the cooling control parameter tolerance interval set to generate a target cooling control parameter adjustable interval set. Specifically, compare the cooling control parameter tolerance interval set with the abnormal control parameter tolerance interval set, exclude the part overlapping with the abnormal control parameter tolerance interval set from the cooling control parameter tolerance interval set, and after excluding the abnormal interval, the remaining tolerance interval is the target cooling control parameter adjustable interval set. This implementation method ensures that the generated target cooling control parameter adjustable interval set contains both the qualified parameter range and the parameter values ​​that may cause abnormalities through the analysis of qualified and abnormal cooling record data, thereby achieving the technical effect of improving the accuracy and reliability of cooling control.

[0031] In a possible implementation, step S610 further includes step S611, retrieving the K qualified cooling record data with the cooling control parameter as an index to obtain multiple qualified cooling control parameter cluster sets, wherein each qualified cooling control parameter cluster set corresponds to a cooling control parameter. Specifically, in the qualified memory database, according to each cooling control parameter as an index, the corresponding qualified cooling record data is retrieved. The retrieved qualified cooling record data is clustered according to its corresponding cooling control parameter to form multiple qualified cooling control parameter cluster sets, each cluster set contains a record of cooling control parameter values ​​corresponding to the same cooling control parameter. Step S612, constructing multiple qualified box plots based on the multiple qualified cooling control parameter cluster sets. Specifically, a box plot is a graph used to display data distribution, which displays data distribution through information such as quartiles and outliers. For each qualified cooling control parameter cluster set, its quartile is calculated, and the corresponding box plot is drawn. Step S613, calculating the interquartile range of the multiple qualified box plots, and multiplying the calculation result by the preset screening step length to obtain multiple tolerance screening step lengths. Specifically, the interquartile range is the difference between the third quartile and the first quartile in the box plot. The calculated interquartile range is multiplied by a preset screening step (a preset coefficient used to adjust the strictness of the screening. A larger screening step will result in a wider screening interval, and a smaller screening step will result in a narrower screening interval) to obtain the tolerance screening step of each cooling control parameter. Step S614: Based on the multiple tolerance screening steps, a search is performed in the multiple qualified cooling control parameter clustering sets to obtain multiple qualified cooling control parameter clustering intervals. Specifically, in each qualified cooling control parameter clustering set, data search is performed based on the corresponding tolerance screening step, and the qualified clustering interval of each cooling control parameter is determined according to the search results. These intervals are relatively dense and reasonable parts of the data distribution. Step S615: The multiple qualified cooling control parameter clustering intervals are used as a cooling control parameter tolerance interval set. Specifically, the qualified clustering intervals of each cooling control parameter are integrated together to form a complete cooling control parameter tolerance interval set. This implementation method performs individual analysis and screening for each cooling control parameter, more finely controls the screening results, and achieves the technical effect of improving the accuracy and reliability of tolerance interval screening.

[0032] In a possible implementation, step S614 further includes step S6141, respectively calculating multiple cluster centers of the multiple qualified cooling control parameter cluster sets. Specifically, a clustering algorithm (such as K-means, DBSCAN, etc.) is used to calculate the cluster center from each qualified cooling control parameter cluster set to obtain multiple cluster centers. Among them, the cluster center represents the "center of mass" or "center point" of a cluster, which is obtained by calculating the average value or other statistics of all points in the cluster. Step S6142, taking the multiple cluster centers as the starting point and the multiple tolerance screening steps as the search radius, construct multiple first search intervals. Specifically, taking each cluster center as the center of the circle (or center point) and the corresponding tolerance screening step as the radius, construct multiple circular (or square) first search intervals in the qualified cooling control parameter cluster set. Step S6143, again taking the multiple cluster centers as the starting point, expanding the multiple first search intervals according to the multiple tolerance screening steps to generate multiple second search intervals. Specifically, based on the cluster center, the first search interval is expanded according to the same tolerance screening step length. The expansion method can be to increase the radius length, or to adjust the shape or direction of the search interval, and multiple second search intervals are generated after expansion. Step S6144, the multiple first search intervals and the multiple second search intervals are respectively authenticated by interval density transition. When the authentication is passed, the expansion is stopped, and the multiple search intervals corresponding to the multiple interval density maximum values ​​are used as multiple qualified cooling control parameter aggregation intervals. Specifically, for each first search interval and the second search interval, the data point density is calculated by calculating the ratio of the number of data points in the interval to the interval area (or volume), and it is determined whether the density difference between adjacent search intervals reaches a preset threshold. If the density difference is large, it indicates that an interval with relatively concentrated density has been retrieved, and the authentication is passed at this time. When the authentication is passed, the expansion is stopped, and the search interval corresponding to the interval density maximum value is selected as the qualified cooling control parameter aggregation interval. This implementation method accurately locates the aggregation interval of qualified cooling control parameters by gradually expanding the search interval and performing density transition authentication, and achieves the technical effect of quickly locating the area where data distribution is relatively concentrated and improving the search efficiency.

[0033] Step S700, performing control parameter target optimization in the target cooling control parameter adjustable interval set to obtain the target cooling control parameter set. Specifically, determine the optimization target, that is, the performance index or target value that the target metal casting cooling process is expected to achieve, including the temperature distribution uniformity, hardness distribution range, residual stress level, etc. of the casting. According to the physical model of the cooling process and known data, a mathematical model is constructed to describe the relationship between the cooling control parameters and the casting performance. The model can reflect the influence of the control parameters on the casting performance and can predict the casting performance within a given control parameter range. According to the actual situation and process requirements, set the constraints of the optimization model, including the value range of the control parameters, the limiting conditions of the casting performance, etc., to ensure the feasibility and effectiveness of the optimization results. In the target cooling control parameter adjustable interval set, use an optimization algorithm, such as a genetic algorithm, a particle swarm optimization algorithm, a gradient descent algorithm, etc., to perform iterative calculations, and by continuously adjusting the values ​​of the control parameters, find a control parameter combination that makes the casting performance optimal or meets a specific goal, and use experiments or simulations to evaluate the cooling control parameter set obtained by the optimization calculation to verify whether it meets the optimization goals and constraints. The verified target cooling control parameters that meet the optimization objectives and constraints are combined and organized into a target cooling control parameter set.

[0034] Step S800, synchronize the target cooling control parameter set to the control unit, and execute the cooling control of the target metal casting. Specifically, the target cooling control parameter set is transmitted to the control unit by wired or wireless means. The control unit is an automated control system or device for receiving and executing cooling control parameters, which can be a PLC (programmable logic controller), an industrial control computer or other control system with corresponding functions. The corresponding control parameters are set or updated in the control unit to make them consistent with the target cooling control parameter set. Start the control unit to execute the cooling control of the target metal casting. The control unit automatically adjusts the relevant parameters of the cooling system, such as temperature, flow, time, etc., according to the set target cooling control parameter set. During the cooling process, the cooling condition of the target metal casting and the operating status of the control system are continuously monitored. If necessary, the control parameters are adjusted in real time according to the monitoring results to ensure that the cooling process of the casting meets the expected requirements. The embodiment of the present application adopts technical means such as constructing a first screening constraint based on the basic casting information of the target metal casting, constructing a second screening constraint based on the cooling acceptance standard of the target metal casting, using the first screening constraint and the second screening constraint to perform qualified screening on the cooling record database and the memory database respectively, performing fine screening of cooling control parameters based on the qualified memory database and the abnormal memory database, and optimizing the control parameter target in the target cooling control parameter adjustable interval set, thereby achieving the technical effect of realizing high-precision cooling control and meeting high-precision requirements.

[0035] In the above, refer to Figure 1 A metal casting cooling control method according to an embodiment of the present invention is described in detail. Figure 2 A metal casting cooling control system according to an embodiment of the present invention is described.

[0036] A metal casting cooling control system according to an embodiment of the present invention is used to solve the technical problem that the existing metal casting cooling control has low control accuracy and cannot meet the high-precision requirements, so as to achieve the technical effect of realizing high-precision cooling control and meeting the high-precision requirements. A metal casting cooling control system includes: a basic casting information acquisition module 10, a first screening constraint construction module 20, a second screening constraint construction module 30, a memory database acquisition module 40, a qualified screening module 50, a target cooling control parameter adjustable interval set generation module 60, a target cooling control parameter set acquisition module 70, and a cooling control module 80.

[0037] The basic casting information acquisition module 10 is used to acquire the basic casting information of the target metal casting, wherein the basic casting information includes casting material data, casting geometry and casting geometry; the first screening constraint construction module 20 is used to construct a first screening constraint according to the casting material data, casting geometry and casting geometry; the second screening constraint construction module 30 is used to construct a second screening constraint based on the cooling acceptance standard of the target metal casting; the memory database acquisition module 40 is used to retrieve the cooling record database, and perform data screening in the cooling record database according to the first screening constraint to obtain the memory database; the qualified screening module 50 Used to perform qualified screening on the memory database according to the second screening constraint, and generate a qualified memory database and an abnormal memory database; the target cooling control parameter adjustable interval set generation module 60 is used to perform fine screening of cooling control parameters according to the qualified memory database and the abnormal memory database, and generate a target cooling control parameter adjustable interval set; the target cooling control parameter set acquisition module 70 is used to optimize the control parameter target in the target cooling control parameter adjustable interval set, and obtain the target cooling control parameter set; the cooling control module 80 is used to synchronize the target cooling control parameter set to the control unit, and execute the cooling control of the target metal casting.

[0038] The specific configuration of the target cooling control parameter adjustable interval set generation module 60 will be described in detail below. As described above, the target cooling control parameter adjustable interval set generation module 60 may further include: a tolerance interval screening unit for performing tolerance interval screening on K qualified cooling control parameter sets in the K qualified cooling record data in the qualified memory database to generate a cooling control parameter tolerance interval set; an abnormal interval screening unit for performing abnormal interval screening on L abnormal cooling control parameter sets in the L abnormal cooling record data in the abnormal memory database to generate an abnormal control parameter tolerance interval set; and a parameter fine screening unit for performing parameter fine screening on the cooling control parameter tolerance interval set using the abnormal control parameter tolerance interval set to generate a target cooling control parameter adjustable interval set.

[0039] Among them, K qualified cooling control parameter sets among the K qualified cooling record data in the qualified memory database are subjected to tolerance interval screening to generate a cooling control parameter tolerance interval set, and the tolerance interval screening unit may further include: a qualified cooling control parameter cluster set acquisition subunit is used to retrieve the K qualified cooling record data with the cooling control parameter as an index to obtain multiple qualified cooling control parameter cluster sets, wherein each qualified cooling control parameter cluster set corresponds to a cooling control parameter; a qualified box plot construction subunit is used to construct multiple qualified box plots based on the multiple qualified cooling control parameter cluster sets; a tolerance screening step acquisition subunit is used to calculate the interquartile range of the multiple qualified box plots, and multiply the calculation result by the preset screening step to obtain multiple tolerance screening steps; a qualified cooling control parameter cluster interval acquisition subunit is used to search in the multiple qualified cooling control parameter cluster sets based on the multiple tolerance screening steps to obtain multiple qualified cooling control parameter cluster intervals, and use the multiple qualified cooling control parameter cluster intervals as the cooling control parameter tolerance interval set.

[0040] Among them, based on the multiple tolerance screening steps, a search is performed in the multiple qualified cooling control parameter cluster sets to obtain multiple qualified cooling control parameter cluster intervals. The qualified cooling control parameter cluster interval acquisition subunit may further include: a cluster center calculation microunit is used to respectively calculate the multiple cluster centers of the multiple qualified cooling control parameter cluster sets; a first search interval construction microunit is used to take the multiple cluster centers as the starting point and take the multiple tolerance screening steps as the search radius to construct multiple first search intervals; a second search interval generation microunit is used to take the multiple cluster centers as the starting point again and expand the multiple first search intervals according to the multiple tolerance screening steps to generate multiple second search intervals; an interval density transition authentication microunit is used to perform interval density transition authentication on the multiple first search intervals and the multiple second search intervals respectively. When the authentication is passed, the expansion is stopped, and the multiple search intervals corresponding to the multiple interval density maximum values ​​are used as multiple qualified cooling control parameter cluster intervals.

[0041] The specific configuration of the memory database acquisition module 40 will be described in detail below. As described above, the memory database acquisition module 40 may further include: a similarity analysis unit for performing similarity analysis on multiple cooling record data in the memory database to obtain a database consistency factor; a database expansion instruction acquisition unit for determining whether the consistency factor meets a preset requirement, and if not, obtaining a database expansion instruction; and a data supplement unit for supplementing data to the memory database according to the database expansion instruction.

[0042] Among them, the memory database acquisition module 40 may further include: a cooling record database construction unit for constructing a cooling record database, wherein the cooling record database includes multiple sample points; a target constraint point acquisition unit for obtaining a target constraint point in the cooling record database according to the first screening constraint; a memory database generation unit for collecting multiple neighboring sample points from the multiple sample points whose distance to the target constraint point is within a preset distance threshold, and obtaining the memory database based on the multiple neighboring sample points.

[0043] Among them, the cooling record database construction unit may further include: a sample cooling record data acquisition subunit for acquiring multiple sample cooling record data, wherein the multiple sample cooling record data include multiple casting material data, multiple casting geometric structures and multiple casting geometric dimensions; a sample point generation subunit for inputting the multiple casting material data, multiple casting geometric structures and multiple casting geometric dimensions into a three-dimensional space coordinate system to generate multiple sample points; a cooling record database generation subunit for constructing the cooling record database according to the multiple sample points.

[0044] A metal casting cooling control system provided in an embodiment of the present invention can execute a metal casting cooling control method provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0045] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0046] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for controlling cooling of a metal casting, characterized in that: The method comprises: Collecting basic casting information of the target metal casting, wherein the basic casting information includes casting material data, casting geometric structure and casting geometric dimensions; Constructing a first screening constraint according to the casting material data, the casting geometry and the casting geometry; constructing a second screening constraint based on the cooling acceptance criteria of the target metal casting; Retrieving a cooling record database, and filtering data in the cooling record database according to the first filtering constraint to obtain a memory database; Performing qualified screening on the memory database according to the second screening constraint to generate a qualified memory database and an abnormal memory database; Perform fine screening of cooling control parameters according to the qualified memory database and the abnormal memory database to generate a target cooling control parameter adjustable interval set; Performing control parameter target optimization in the target cooling control parameter adjustable interval set to obtain a target cooling control parameter set; The target cooling control parameter set is synchronized to a control unit to execute cooling control of the target metal casting.

2. A metal casting cooling control method as claimed in claim 1, characterized in that: The method comprises: Performing tolerance interval screening on K qualified cooling control parameter sets in the K qualified cooling record data in the qualified memory database to generate a cooling control parameter tolerance interval set; Performing abnormal interval screening on L abnormal cooling control parameter sets in the L abnormal cooling record data in the abnormal memory database to generate an abnormal control parameter tolerance interval set; The abnormal control parameter tolerance interval set is used to perform parameter fine screening on the cooling control parameter tolerance interval set to generate a target cooling control parameter adjustable interval set.

3. A metal casting cooling control method as claimed in claim 2, characterized in that: Performing tolerance interval screening on K qualified cooling control parameter sets in K qualified cooling record data in the qualified memory database to generate a cooling control parameter tolerance interval set, the method comprising: Retrieving the K qualified cooling record data using the cooling control parameter as an index to obtain a plurality of qualified cooling control parameter cluster sets, wherein each qualified cooling control parameter cluster set corresponds to a cooling control parameter; constructing a plurality of qualified box plots based on the plurality of qualified cooling control parameter cluster sets; Calculating the interquartile ranges of the plurality of qualified box plots, and multiplying the calculated results by a preset screening step length to obtain a plurality of tolerant screening step lengths; Searching in the plurality of qualified cooling control parameter cluster sets based on the plurality of tolerance screening steps to obtain a plurality of qualified cooling control parameter cluster intervals; The plurality of qualified cooling control parameter aggregation intervals are used as a cooling control parameter tolerance interval set.

4. A metal casting cooling control method as claimed in claim 3, characterized in that: Based on the multiple tolerance screening steps, searching in the multiple qualified cooling control parameter clustering sets to obtain multiple qualified cooling control parameter clustering intervals, the method includes: respectively calculating a plurality of cluster centers of the plurality of qualified cooling control parameter cluster sets; Taking the plurality of cluster centers as starting points and the plurality of tolerance screening steps as search radii, constructing a plurality of first search intervals; Again taking the plurality of cluster centers as starting points, expanding the plurality of first search intervals according to the plurality of tolerance screening steps to generate a plurality of second search intervals; The multiple first search intervals and the multiple second search intervals are respectively authenticated for interval density transition. When the authentication is passed, the expansion is stopped, and the multiple search intervals corresponding to the multiple interval density maximum values ​​are used as multiple qualified cooling control parameter aggregation intervals.

5. A metal casting cooling control method as claimed in claim 1, characterized in that: The method comprises: Performing similarity analysis on multiple cooling record data in the memory database to obtain a database consistency factor; Determine whether the consistency factor meets the preset requirements, and if not, obtain a database expansion instruction; The memory database is supplemented with data according to the database expansion instruction.

6. A method for controlling cooling of metal castings as claimed in claim 1, characterized in that: The method comprises: Constructing a cooling record database, wherein the cooling record database includes a plurality of sample points; According to the first screening constraint, obtaining a target constraint point in the cooling record database; A plurality of neighboring sample points whose distances to the target constraint point are within a preset distance threshold from the plurality of sample points are collected, and the memory database is obtained according to the plurality of neighboring sample points.

7. A metal casting cooling control method as claimed in claim 6, characterized in that: The method comprises: Acquire a plurality of sample cooling record data, wherein the plurality of sample cooling record data includes a plurality of casting material data, a plurality of casting geometric structures and a plurality of casting geometric dimensions; Inputting the plurality of casting material data, the plurality of casting geometric structures and the plurality of casting geometric dimensions into a three-dimensional space coordinate system to generate a plurality of sample points; The cooling record database is constructed according to the plurality of sample points.

8. A metal casting cooling control system, characterized in that: The system is used to implement a metal casting cooling control method according to any one of claims 1 to 7, and the system comprises: A basic casting information acquisition module, wherein the basic casting information acquisition module is used to acquire basic casting information of a target metal casting, wherein the basic casting information includes casting material data, casting geometric structure and casting geometric dimensions; A first screening constraint building module, the first screening constraint building module is used to build a first screening constraint according to the casting material data, the casting geometric structure and the casting geometric size; a second screening constraint building module, the second screening constraint building module being used to build a second screening constraint based on a cooling acceptance criterion of the target metal casting; a memory database acquisition module, the memory database acquisition module being used to retrieve a cooling record database, filter data in the cooling record database according to the first filtering constraint, and obtain a memory database; A qualified screening module, the qualified screening module is used to perform qualified screening on the memory database according to the second screening constraint to generate a qualified memory database and an abnormal memory database; A target cooling control parameter adjustable interval set generation module, the target cooling control parameter adjustable interval set generation module is used to perform a cooling control parameter fine screening according to the qualified memory database and the abnormal memory database to generate a target cooling control parameter adjustable interval set; A target cooling control parameter set acquisition module, the target cooling control parameter set acquisition module is used to perform control parameter target optimization in the target cooling control parameter adjustable interval set to obtain a target cooling control parameter set; A cooling control module is used to synchronize the target cooling control parameter set to a control unit to perform cooling control of the target metal casting.

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