Aluminum alloy standard sample production method and system

Abstract

The present invention relates to the technical field of aluminum alloy production data processing. The present invention provides a method and system for producing aluminum alloy standard samples. By obtaining a data traceability table and substituting it into a preset production model, control parameters of each production unit are generated, and automated control of steps such as a cooling device, a preheating mold, aluminum soup processing, casting, cooling, and cutting is achieved. The system includes casting preparation, a cooling device, a preheating mold, aluminum soup processing, casting, cooling, cutting, and data review units, thereby achieving traceability and visualization of production data. The present invention improves production efficiency and product quality, and enhances the intelligence and transparency of the production process, providing comprehensive optimization for the production of aluminum alloy standard samples.

Description

Technical Field

[0001] The present invention relates to the technical field of aluminum alloy production data processing, and in particular to a method and system for producing aluminum alloy standard samples. Background Art

[0002] Aluminum alloy standard samples are the basis for quality control and testing of aluminum alloy products. During the production process, specialized cooling equipment is used to preheat and cool the mold, and the aluminum slurry is refined and degassed. Through the steps of casting, sampling, cooling, removal, cutting, and marking, aluminum alloy standard samples that meet the requirements are produced. Finally, through a quality assessment process including top-down inspection, the quality of the aluminum alloy standard samples is ensured to meet established standards, providing a reliable reference for the production and testing of aluminum alloy products.

[0003] The production of aluminum alloy standard samples presents several technical challenges. From raw material traceability to parameter setting at every production step, including casting temperature, refining agent dosage, and Ar treatment time, precise records are required. Any deviation in these data can impact the accuracy and representativeness of the final sample. Due to the multiple steps and complex physical and chemical changes involved in the production process, existing technologies are unable to effectively integrate and analyze aluminum alloy standard sample data. To address this technical challenge, the present invention provides a method and system for producing aluminum alloy standard samples. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the present invention provides a method and system for producing aluminum alloy standard samples to solve the problem that the existing technology cannot effectively integrate and analyze aluminum alloy standard sample data.

[0005] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0006] In a first aspect, the present invention provides a method for producing an aluminum alloy standard sample, comprising:

[0007] Step S101: Obtain a data traceability table, which includes target values ​​of the aluminum alloy standard sample, formulation data, and raw materials used for each component when it is sold; collect parameters used in the production process of the aluminum alloy standard sample; store the data traceability table and the parameters used in the production process of the aluminum alloy standard sample in a database; substitute the data traceability table into a preset aluminum alloy standard sample production model to generate aluminum alloy standard sample production control parameters; the aluminum alloy standard sample production control parameters include cooling device control parameters, preheating mold control parameters, aluminum slurry treatment control parameters, casting control parameters, cooling control parameters, and cutting control parameters;

[0008] Step S102: The cooling device executes the cooling device control parameters, which are used to adjust the water inlet and outlet of the cooling water bucket and the height of the automatic lifting device so that water can enter or exit the cooling device in the cooling unit;

[0009] Step S103: The preheating device executes the preheating mold control parameters. The preheating device is used to maintain the temperature of the mold during the casting process, record the preheating temperature and time of the mold, and detect whether each preheating value meets the process standard;

[0010] Step S104: sending the aluminum slurry processing parameters to the aluminum slurry processing equipment. After the aluminum slurry processing equipment executes the aluminum slurry processing parameters, it monitors the data parameters during the aluminum slurry processing process. When the aluminum slurry meets the preset aluminum slurry processing parameters, the casting unit is triggered.

[0011] Step S105: Acquire weather, temperature, humidity, casting temperature, and sampled image information during the casting process, perform data preprocessing on the acquired weather, temperature, humidity, casting temperature, and sampled image information to obtain preprocessed forging data, substitute the preprocessed forging data and casting control parameters into a preset casting production model, generate a casting task command, send the casting task command to the casting equipment, and cast the aluminum material after the aluminum slurry treatment;

[0012] Step S106, cooling the cast aluminum material according to the cooling control parameters, collecting temperature data of the aluminum material during the cooling process, and optimizing the cooling unit control parameters if the temperature data of the aluminum material is higher than a preset cooling standard temperature value;

[0013] Step S107, determining the position of the aluminum material to be cut according to the cutting control parameters, marking the aluminum material according to the position of the aluminum material to be cut to obtain the marked position of the aluminum material, and cutting the aluminum material according to the marked position of the aluminum material;

[0014] Step S108, summarize and classify the information of the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark unit, and generate visual data for reviewing the production data of the aluminum alloy standard sample.

[0015] Furthermore, in the aluminum alloy standard sample production method described in the present invention, step S101 includes:

[0016] Receive the objectives of the aluminum alloy standard sample production model, the objectives of the aluminum alloy standard sample production model include production efficiency and product quality parameters;

[0017] Obtain historical production data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain historical production data of aluminum alloy standard samples;

[0018] Feature extraction is performed on the historical production data of aluminum alloy standard samples, and the extracted features are used as input. Production efficiency and product quality parameters are used as output. The random forest model is trained using the historical production data of aluminum alloy standard samples to obtain an aluminum alloy standard sample production model.

[0019] Furthermore, in the aluminum alloy standard sample production method described in the present invention, step S105 includes:

[0020] Obtain weather, temperature, and humidity information during the casting process in real time, and use cameras or other image acquisition devices to obtain sampled image information;

[0021] Data preprocessing is performed on the acquired weather, temperature, humidity information, casting temperature, and sampled image information. The preprocessed data will be used for casting production model calculation and casting task command generation;

[0022] The preprocessed forging data and casting control parameters are substituted into the preset casting production model. The casting production model is based on machine learning and predicts the optimal parameters of the casting process according to the input data, and uses the optimal parameters as the casting task command.

[0023] Furthermore, in the aluminum alloy standard sample production method described in the present invention, step S107 includes:

[0024] According to the requirements and specifications of the production of aluminum alloy standard samples, the cutting control parameters are determined. The cutting control parameters include cutting speed, cutting position, cutting angle, etc.

[0025] According to the cutting control parameters, determine the specific position to be cut on the aluminum material, and use appropriate marking tools to mark the aluminum material at the determined position to be cut;

[0026] According to the marked position of the aluminum material, use the cutting equipment to cut the aluminum material.

[0027] Furthermore, in the aluminum alloy standard sample production method described in the present invention, step S108 includes:

[0028] Data is collected from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain raw material traceability information, cooling device configuration parameters, mold preheating temperature and time, aluminum soup processing process parameters, casting temperature and sampling images, cooling process records, cutting position and marking information;

[0029] Classify the collected data and clean the classified data. Data cleaning includes removing duplicate data, processing missing data, and correcting erroneous data operations;

[0030] Use data visualization tools to convert the cleaned and validated data into visual forms, including charts, tables, and images.

[0031] In a second aspect, the present invention provides an aluminum alloy standard sample production system, which is applied to the aluminum alloy standard sample production method as described above, comprising:

[0032] The casting preparation unit obtains a data traceability table, which includes the target value of the aluminum alloy standard sample, the formulation data, and the raw materials used for each component when it is sold. It collects the parameters used in the production process of the aluminum alloy standard sample, stores the data traceability table and the parameters used in the production process of the aluminum alloy standard sample in a database, substitutes the data traceability table into the preset aluminum alloy standard sample production model, and generates the aluminum alloy standard sample production control parameters. The aluminum alloy standard sample production control parameters include cooling device control parameters, preheating mold control parameters, aluminum soup treatment control parameters, casting control parameters, cooling control parameters, and cutting control parameters;

[0033] A cooling device unit, wherein the cooling device executes cooling device control parameters, and the cooling device control parameters are used to adjust the water inlet and outlet of the cooling water bucket and the height of the automatic lifting device so that water enters or exits the cooling equipment in the cooling unit;

[0034] Preheating mold unit: The preheating equipment executes the preheating mold control parameters. The preheating equipment is used to maintain the temperature of the mold during the casting process, record the preheating temperature and time of the mold, and detect whether the preheating value each time meets the process standards;

[0035] The aluminum soup processing unit sends the aluminum soup processing parameters to the aluminum soup processing equipment. After the aluminum soup processing equipment executes the aluminum soup processing parameters, it monitors the data parameters during the aluminum soup processing process. When the aluminum soup meets the preset aluminum soup processing parameters, the casting unit is triggered;

[0036] The casting unit obtains weather, temperature, humidity, casting temperature, and sampling image information during the casting process, performs data preprocessing on the weather, temperature, humidity, casting temperature, and sampling image information during the casting process to obtain preprocessed forging data, substitutes the preprocessed forging data and casting control parameters into a preset casting production model, generates a casting task command, and sends the casting task command to the casting equipment, which then casts the aluminum material after the aluminum soup treatment;

[0037] The cooling unit cools the aluminum material after casting according to the cooling control parameters, collects the temperature data of the aluminum material during the cooling process, and optimizes the cooling unit control parameters if the temperature data of the aluminum material is higher than the preset cooling standard temperature value;

[0038] The cutting unit determines the position of the aluminum material to be cut according to the cutting control parameters, marks the aluminum material according to the position of the aluminum material to be cut, obtains the marked position of the aluminum material, and cuts the aluminum material according to the marked position of the aluminum material;

[0039] The data review unit summarizes and classifies the information of the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark unit, and generates visual data for reviewing the production data of aluminum alloy standard samples.

[0040] Furthermore, in the aluminum alloy standard sample production system of the present invention, the casting preparation unit is further used to:

[0041] Receive the objectives of the aluminum alloy standard sample production model, the objectives of the aluminum alloy standard sample production model include production efficiency and product quality parameters;

[0042] Obtain historical production data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain historical production data of aluminum alloy standard samples;

[0043] Feature extraction is performed on the historical production data of aluminum alloy standard samples, and the extracted features are used as input. Production efficiency and product quality parameters are used as output. The random forest model is trained using the historical production data of aluminum alloy standard samples to obtain an aluminum alloy standard sample production model.

[0044] Furthermore, in the aluminum alloy standard sample production system described in the present invention, the casting unit is further used to:

[0045] Obtain weather, temperature, and humidity information during the casting process in real time, and use cameras or other image acquisition devices to obtain sampled image information;

[0046] Data preprocessing is performed on the acquired weather, temperature, humidity information, casting temperature, and sampled image information. The preprocessed data will be used for casting production model calculation and casting task command generation;

[0047] The preprocessed forging data and casting control parameters are substituted into the preset casting production model. The casting production model is based on machine learning and predicts the optimal parameters of the casting process according to the input data, and uses the optimal parameters as the casting task command.

[0048] Furthermore, in the aluminum alloy standard sample production system described in the present invention, the cutting unit is further used to:

[0049] According to the requirements and specifications of the production of aluminum alloy standard samples, the cutting control parameters are determined. The cutting control parameters include cutting speed, cutting position, cutting angle, etc.

[0050] According to the cutting control parameters, determine the specific position to be cut on the aluminum material, and use appropriate marking tools to mark the aluminum material at the determined position to be cut;

[0051] According to the marked position of the aluminum material, use the cutting equipment to cut the aluminum material.

[0052] Furthermore, in the aluminum alloy standard sample production system described in the present invention, the data review unit is further used to:

[0053] Data is collected from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain raw material traceability information, cooling device configuration parameters, mold preheating temperature and time, aluminum soup processing process parameters, casting temperature and sampling images, cooling process records, cutting position and marking information;

[0054] Classify the collected data and clean the classified data. Data cleaning includes removing duplicate data, processing missing data, and correcting erroneous data operations;

[0055] Use data visualization tools to convert the cleaned and validated data into visual forms, including charts, tables, and images.

[0056] The beneficial effects of the present invention are mainly reflected in the following aspects:

[0057] This invention significantly improves the production efficiency of aluminum alloy standard samples through automated and intelligent production processes. The collaborative operation of various production units (such as the cooling unit, preheating mold unit, and aluminum bath processing unit), as well as the generation of casting task commands based on data models, reduces manual intervention and waiting time, making the production process smoother and more efficient.

[0058] This invention ensures the quality stability and consistency of aluminum alloy standard samples by precisely controlling various parameters during the production process (such as those for the cooling device, preheating the mold, and aluminum bath treatment). Furthermore, through quality assessment processes such as top-down inspections, the product qualification rate is further improved and the scrap rate is reduced.

[0059] This invention establishes a comprehensive data traceability system, comprehensively tracking and recording raw materials, parameters, and operational records throughout the production process. This not only facilitates the rapid identification and cause analysis of problematic products, but also provides valuable data support for subsequent production improvements and quality enhancements. Through data visualization and analysis, this invention helps production personnel promptly understand resource consumption (such as energy and raw materials) during the production process, enabling them to rationally allocate resources and avoid waste and shortages. Furthermore, data-driven production decisions can be more scientific and accurate, further improving resource utilization efficiency.

[0060] The implementation of this invention has advanced the intelligent production of aluminum alloy standard samples. By introducing advanced technologies such as machine learning and data modeling, it has achieved automated control and optimized adjustment of the production process, laying a solid foundation for future intelligent manufacturing and digital factory construction.

[0061] In summary, the present invention has shown significant beneficial effects in improving production efficiency, enhancing product quality, enhancing data traceability, optimizing resource allocation, and promoting intelligent production, bringing comprehensive improvement and enhancement to the production of aluminum alloy standard samples. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on the drawings without paying any creative labor.

[0063] Figure 1 A schematic flow chart of a method for producing an aluminum alloy standard sample provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0064] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and corresponding drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention. The technical solutions provided by each embodiment of the present invention are described in detail below in conjunction with the drawings.

[0065] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0066] In a first aspect, the present invention provides a method for producing an aluminum alloy standard sample, comprising:

[0067] Step S101: Obtain a data traceability table, which includes target values ​​of the aluminum alloy standard sample, formulation data, and raw materials used for each component when it is sold; collect parameters used in the production process of the aluminum alloy standard sample; store the data traceability table and the parameters used in the production process of the aluminum alloy standard sample in a database; substitute the data traceability table into a preset aluminum alloy standard sample production model to generate aluminum alloy standard sample production control parameters; the aluminum alloy standard sample production control parameters include cooling device control parameters, preheating mold control parameters, aluminum slurry treatment control parameters, casting control parameters, cooling control parameters, and cutting control parameters;

[0068] A data traceability sheet is a document that details the target values ​​of aluminum alloy standard samples, recipe data, and the raw materials used for each component at the time of sale. This information is crucial for ensuring product quality and traceability.

[0069] The actual production process of aluminum alloy standard samples involves multiple links and parameters, such as temperature, time, dosage, etc. The data traceability table and the parameters collected during the production process are stored in a database.

[0070] Substitute the data traceability table into the preset aluminum alloy standard sample production model. This production model is built based on historical data, professional knowledge, and machine learning algorithms to generate optimal production control parameters. Through the processing of the production model, a series of aluminum alloy standard sample production control parameters can be generated, including but not limited to:

[0071] Cooling device control parameters: used to adjust the water inlet and outlet of the cooling water bucket, the height of the automatic lifting device, etc., to control the cooling process.

[0072] Preheating mold control parameters: used to maintain the temperature of the mold during the casting process and record the preheating temperature and time.

[0073] Aluminum soup processing control parameters: parameters related to the refining, degassing and other processing processes of aluminum soup.

[0074] Casting control parameters: including casting temperature, sampling method and other key casting parameters.

[0075] Cooling control parameters: used to control the cooling process of aluminum after casting to ensure product quality.

[0076] Cutting control parameters: Determine the cutting position, speed, angle, etc. of the aluminum material to meet product specification requirements.

[0077] Step S102: The cooling device executes the cooling device control parameters, which are used to adjust the water inlet and outlet of the cooling water bucket and the height of the automatic lifting device so that water can enter or exit the cooling device in the cooling unit;

[0078] The cooling device control parameters are generated by the aluminum alloy standard sample production model. They are specifically used to adjust the various functions of the cooling device to ensure that the aluminum alloy standard sample can be properly cooled after casting.

[0079] The cooling water tank is a crucial component of the cooling unit. By adjusting its inlet and outlet, the flow and speed of the cooling water can be controlled. The cooling unit's control parameters specify specific inlet and outlet settings to suit different cooling requirements. For example, to achieve rapid cooling, the inlet flow can be increased; to achieve slower cooling, the inlet flow can be reduced or the drain opening can be adjusted.

[0080] Automatic lifting devices control the height of cooling equipment (such as cooling water buckets), thereby affecting the contact between the cooling water and the aluminum alloy standard specimen and the cooling effect. Based on the cooling device's control parameters, the automatic lifting device adjusts to the appropriate height. For example, during the initial cooling phase, the cooling device may need to be lowered to ensure adequate contact; in subsequent phases, the cooling device may need to be raised to reduce contact time and avoid overcooling.

[0081] Water enters or leaves the cooling equipment in the cooling unit:

[0082] Through the above adjustments, cooling water can enter the cooling device in the cooling unit at a predetermined flow rate and speed to cool the aluminum alloy standard sample. When the predetermined cooling time or temperature is reached, the cooling water will be discharged from the cooling device through the drain, completing a cooling cycle. By executing the cooling device control parameters, the cooling device can automatically and accurately complete the cooling process without human intervention, thereby improving production efficiency and product quality. In addition, because the cooling device control parameters are generated based on the aluminum alloy standard sample production model, they can be dynamically adjusted according to actual conditions to adapt to different production conditions and needs.

[0083] Step S103: The preheating device executes the preheating mold control parameters. The preheating device is used to maintain the temperature of the mold during the casting process, record the preheating temperature and time of the mold, and detect whether each preheating value meets the process standard;

[0084] Preheating mold control parameters are generated by the aluminum alloy standard sample production model based on data traceability tables and real-time production conditions. They are specifically designed to guide the operation of the preheating equipment to maintain a stable mold temperature during the casting process. The preheating equipment preheats the mold according to the preheating mold control parameters. This involves heating the mold to a specific temperature range and maintaining it for a period of time to ensure uniform temperature distribution. The preheating equipment continues to operate during the casting process to maintain the mold within the predetermined temperature range.

[0085] The preheating equipment also records the mold's preheating temperature and time. This data is crucial for monitoring the production process, ensuring adherence to process standards, and ensuring quality traceability. The preheating equipment is also equipped with a real-time detection mechanism to verify that the mold's preheating values ​​meet process standards. If the preheating values ​​deviate from the predetermined range, the preheating equipment will automatically adjust the heating power or take other measures to ensure that the mold temperature quickly returns to normal.

[0086] By implementing preheating mold control parameters, the preheating equipment can automate and precisely control mold preheating without manual intervention, thereby improving production efficiency and product quality. Furthermore, because the preheating mold control parameters are generated based on a production model of standard aluminum alloy samples, they can be dynamically adjusted to suit varying production conditions and requirements. Proper mold preheating allows the molten aluminum to solidify rapidly upon injection into the mold, forming a dense microstructure and enhancing the product's strength and durability. Furthermore, stable mold temperature reduces thermal stress and deformation during the casting process, further improving the product's dimensional accuracy and surface quality.

[0087] Step S104: sending the aluminum slurry processing parameters to the aluminum slurry processing equipment. After the aluminum slurry processing equipment executes the aluminum slurry processing parameters, it monitors the data parameters during the aluminum slurry processing process. When the aluminum slurry meets the preset aluminum slurry processing parameters, the casting unit is triggered.

[0088] In step S104, the aluminum bath processing parameters are sent to the aluminum bath processing equipment. This step is a key step in the production of aluminum alloy standard samples, ensuring that the quality of the aluminum bath (i.e., the molten aluminum alloy material) meets the predetermined standards before casting. The following is a detailed analysis of this step:

[0089] Aluminum bath processing parameters are generated based on a production model of aluminum alloy standard samples. They contain a series of instructions and set values ​​that guide the operation of aluminum bath processing equipment. These parameters are designed to improve the aluminum bath's composition, temperature, gas content, and other key indicators through specific physical or chemical processes to meet casting requirements.

[0090] The aluminum bath treatment parameters are sent to the aluminum bath treatment equipment via a pre-set communication protocol or interface. These parameters may include the type and amount of refining agent, the flow rate and time of Ar treatment, the target temperature, etc.

[0091] After receiving the parameters, the aluminum bath processing equipment begins to perform the corresponding processing operations. For example, it adds refining agents to remove impurities, performs Ar treatment to remove gases and salts, or adjusts the heating power to control the aluminum bath temperature.

[0092] During the processing, the aluminum slag processing equipment monitors various parameters of the aluminum slag in real time, such as temperature, composition, and gas content. This data is collected by sensors and fed back to the control system. When the aluminum slag processing equipment detects that the various parameters meet the preset aluminum slag processing parameters, the aluminum slag is considered to have passed the processing.

[0093] Once the aluminum broth is processed and meets the standards, the aluminum broth processing equipment sends a signal to the casting unit to trigger the subsequent casting operation. This ensures that casting will only proceed when the aluminum broth quality meets the standards, thus ensuring the quality of the aluminum alloy standard sample.

[0094] Step S105: Acquire weather, temperature, humidity, casting temperature, and sampled image information during the casting process, perform data preprocessing on the acquired weather, temperature, humidity, casting temperature, and sampled image information to obtain preprocessed forging data, substitute the preprocessed forging data and casting control parameters into a preset casting production model, generate a casting task command, send the casting task command to the casting equipment, and the manufacturing equipment cast the aluminum material after the aluminum soup treatment;

[0095] Environmental factors such as weather, temperature, and humidity can affect the cooling rate of the aluminum bath and the temperature distribution of the mold during the casting process.

[0096] Casting temperature: Casting temperature is a key factor in ensuring that the aluminum soup fills the mold smoothly and forms a good microstructure. The casting temperature must be strictly controlled to avoid problems caused by overheating or overcooling.

[0097] Sampling image information: Sampling image information is obtained through a camera or other image acquisition device, which can be used to monitor the flow state, filling condition and defects of the aluminum soup.

[0098] The acquired weather, temperature, humidity, casting temperature, and sampled image information are preprocessed. This preprocessing process may include data cleaning (removing noise and outliers), data transformation (such as normalization or standardization), and feature extraction to facilitate subsequent model processing.

[0099] A pre-set casting production model is a model based on machine learning or statistical methods that can predict the optimal parameters of the casting process based on input data. These parameters may include casting speed, cooling rate, mold temperature, etc.

[0100] The pre-processed forging data and casting control parameters are entered into the casting production model, which then calculates the optimal casting task command based on this data. This casting task command includes a series of specific operational instructions, such as casting speed, cooling method, and mold temperature setting. The casting task command is then sent to the casting equipment, which then casts the aluminum material after the aluminum bath is treated.

[0101] By parameterizing the casting process and integrating it into the casting production model, we achieve automation and real-time control of the casting process. This not only improves production efficiency but also reduces the impact of human error and uncertainty on product quality. Real-time acquisition and processing of casting process data enables the production system to quickly respond to environmental and production condition changes, thereby maintaining stable product quality.

[0102] Step S106, cooling the cast aluminum material according to the cooling control parameters, collecting temperature data of the aluminum material during the cooling process, and optimizing the cooling unit control parameters if the temperature data of the aluminum material is higher than a preset cooling standard temperature value;

[0103] In step S106, if the temperature of the aluminum material during the cooling process exceeds the preset cooling standard temperature, the cooling unit control parameters need to be optimized. A genetic algorithm is a search algorithm that simulates natural selection and genetic mechanisms and is suitable for solving complex optimization problems. The following are the specific steps for optimizing the cooling unit control parameters using a genetic algorithm:

[0104] Determine the range of values ​​for the cooling unit control parameters (such as cooling water flow rate, cooling time, cooling medium temperature, etc.) and randomly generate a set of candidate solutions for the cooling unit control parameters. Each candidate solution is called an individual, and the collection of all individuals is called a population.

[0105] The cooling unit control parameters are converted into a coding form that can be processed by the genetic algorithm, such as binary coding or real number coding. When fitness needs to be calculated, the coding is converted back to the original parameter value.

[0106] Define a fitness function to evaluate the performance of each individual. In this example, the fitness function could be the absolute value of the difference between the aluminum material temperature during the cooling process and the preset cooling standard temperature, or the square of this difference. The goal is to minimize this difference.

[0107] Each individual in the population is decoded and substituted into the cooling unit model to calculate the temperature data of the aluminum material during the cooling process, and then its fitness value is calculated according to the fitness function.

[0108] Based on their fitness, excellent individuals are selected as parents to generate the next generation. Common selection strategies include roulette wheel selection and tournament selection. This selection operation generates a parent population for subsequent crossover and mutation operations.

[0109] Set a crossover probability to determine the probability of a parent individual undergoing a crossover operation. Randomly pair individuals in the parent population and then generate offspring individuals using a crossover method (such as single-point crossover, two-point crossover, uniform crossover, etc.). Set a mutation probability to determine the probability of a mutation in the offspring. Randomly mutate individuals in the offspring population according to the mutation probability. The mutation method can be to change a bit in the code (binary coding) or to randomly adjust the parameter value within a certain range (real number coding).

[0110] Replace the parent population with the offspring population, or merge the parent and offspring populations and sort them by fitness, selecting the top N individuals as the new population. Set termination conditions: these can be when the maximum number of iterations is reached, when the fitness value reaches a preset threshold, or when the population fitness value no longer significantly improves. When the termination condition is met, the iteration stops and the individual with the highest fitness value in the current population is output as the optimal solution, i.e., the optimized cooling unit control parameters.

[0111] By optimizing the cooling unit control parameters through genetic algorithms, a set of control parameter combinations that achieve the best cooling effect can be automatically searched, thereby improving the quality and efficiency of aluminum alloy standard sample production.

[0112] Step S107, determining the position of the aluminum material to be cut according to the cutting control parameters, marking the aluminum material according to the position of the aluminum material to be cut to obtain the marked position of the aluminum material, and cutting the aluminum material according to the marked position of the aluminum material;

[0113] The specific location on the aluminum material that needs to be cut is accurately calculated and determined based on the cutting control parameters, including cutting length, cutting angle, etc. These control parameters are usually pre-set according to product specifications and design requirements.

[0114] After determining the position to be cut, use a suitable marking tool (such as a marking pen, laser marker, etc.) to mark the aluminum surface. The mark should be clear and accurate so that the subsequent cutting operation can be accurately aligned.

[0115] The marking contents may include cutting lines, reference points, etc., depending on the cutting requirements and process flow.

[0116] The marking operation clearly identifies the location on the aluminum material to be cut. This step ensures the accuracy and consistency of the cutting operation.

[0117] According to the marking position on the aluminum material, use cutting equipment (such as sawing machine, shearing machine, etc.) to cut the aluminum material. During the cutting process, ensure that the cut surface is flat, burr-free, and meets the product specifications.

[0118] The selection of cutting equipment and operating parameters (such as cutting speed, feed rate, etc.) should be determined according to the material, thickness and cutting requirements of the aluminum material.

[0119] Step S108, summarize and classify the information of the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark unit, and generate visual data for reviewing the production data of the aluminum alloy standard sample.

[0120] In step S108, information from each production unit is aggregated and categorized, and visual data is generated. This is a crucial step in the production of aluminum alloy standard samples. This step aims to integrate all data generated throughout the entire process, from casting preparation to cut-off marking, making it easily accessible and analyzable. This helps production managers gain a comprehensive understanding of production conditions, optimize production processes, and improve product quality. The following is a detailed explanation of this step:

[0121] Casting preparation unit: collects and summarizes data traceability tables, raw material traceability information, recipe production data, and pre-casting preparation parameters, etc.

[0122] Cooling device unit: records the water inlet and outlet adjustment parameters of the cooling water barrel, the height setting of the automatic lifting device, temperature data during the cooling process, etc.

[0123] Preheating mold unit: Arrange the mold's preheating temperature, preheating time, preheating times, and any abnormal conditions during the preheating process.

[0124] Aluminum soup treatment unit: summarizes the parameters of the aluminum soup treatment process, such as the amount and type of refining agent, the flow rate and time of Ar treatment, and the component analysis of the aluminum soup after treatment.

[0125] Casting unit: collects weather, temperature, humidity information, casting temperature, sampling image information and casting control parameters during the casting process.

[0126] Cooling unit: records temperature data, cooling time, cooling medium usage, etc. during the cooling process.

[0127] Cutting marking unit: organizes information such as cutting control parameters, cutting position, cutting angle, sample size after cutting and appearance quality.

[0128] Use data visualization tools (such as charts, tables, and images) to transform aggregated and categorized data into an intuitive and easy-to-understand presentation. Visualized data should include key production indicators, trend analysis, and abnormality warnings, allowing production managers to quickly identify problems and take appropriate action.

[0129] Production managers can review visualized data to gain a comprehensive understanding of the production status of aluminum alloy standard samples, including production efficiency, product quality, and equipment operating status. Analysis of this visualized data allows for timely identification of potential production issues, such as raw material quality fluctuations, equipment performance degradation, and process parameter deviations, enabling targeted improvement measures. Visualized data can also be used to formulate and adjust production plans, as well as calculate and control production costs, providing strong support for a company's production decisions.

[0130] Specifically, the aluminum alloy standard sample production method described in the present invention, step S101 includes:

[0131] Receive the objectives of the aluminum alloy standard sample production model, the objectives of the aluminum alloy standard sample production model include production efficiency and product quality parameters;

[0132] Obtain historical production data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain historical production data of aluminum alloy standard samples;

[0133] Feature extraction is performed on the historical production data of aluminum alloy standard samples, and the extracted features are used as input. Production efficiency and product quality parameters are used as output. The random forest model is trained using the historical production data of aluminum alloy standard samples to obtain an aluminum alloy standard sample production model.

[0134] Receive the goals for the aluminum alloy standard sample production model. These goals typically include production efficiency (e.g., output per unit time) and product quality parameters (e.g., sample composition accuracy, physical properties, etc.). These goals serve as the basis for the subsequent generation and optimization of production control parameters.

[0135] Historical production data is collected from each production unit (including casting preparation, cooling unit, preheating mold unit, aluminum bath processing unit, casting unit, cooling unit, and cutting marking unit). This data covers the entire process from raw material preparation to finished product cutting and is an important source of information reflecting actual production status.

[0136] Perform feature extraction on the collected historical production data. Feature extraction is a key step in data mining and machine learning, aiming to extract information from raw data that is useful for model training. In the production of aluminum alloy standard samples, these features may include raw material composition ratios, process parameters (such as temperature, time, flow rate, etc.), and equipment status.

[0137] The extracted features are used as input, and production efficiency and product quality parameters are used as output. A random forest model is trained using historical production data for aluminum alloy standard samples. Random forest is an ensemble learning method that improves model accuracy and stability by constructing multiple decision trees and combining their predictions. In this step, the random forest model is used to learn the complex relationship between historical production data, production efficiency, and product quality.

[0138] The trained random forest model can predict corresponding production efficiency and quality parameters based on input features. In actual production, current production conditions (such as raw material composition and equipment status) can be input into the model to obtain optimized production control parameters. These parameters include cooling device control parameters, preheating mold control parameters, aluminum bath treatment control parameters, casting control parameters, cooling control parameters, and cutting control parameters, which together guide the production process of aluminum alloy standard samples.

[0139] As production progresses and new data is generated, the historical production dataset can be regularly updated and the random forest model retrained. This allows the model to continuously adapt to changes in production conditions, further improving production efficiency and product quality.

[0140] In summary, step S101 provides scientific and rational guidance for the production of aluminum alloy standard samples through a series of steps, including receiving production model objectives, acquiring historical production data, extracting features, training a random forest model, and generating production control parameters. This process not only fully utilizes the valuable information in historical production data but also achieves continuous optimization and improvement of the production model through machine learning methods.

[0141] Specifically, in the aluminum alloy standard sample production method described in the present invention, step S105 includes:

[0142] Obtain weather, temperature, and humidity information during the casting process in real time, and use cameras or other image acquisition devices to obtain sampled image information;

[0143] Data preprocessing is performed on the acquired weather, temperature, humidity information, casting temperature, and sampled image information. The preprocessed data will be used for casting production model calculation and casting task command generation;

[0144] The preprocessed forging data and casting control parameters are substituted into the preset casting production model. The casting production model is based on machine learning and predicts the optimal parameters of the casting process according to the input data, and uses the optimal parameters as the casting task command.

[0145] Environmental sensors provide real-time information on weather conditions, temperature, and humidity at the casting site. This information is crucial for understanding the physical and chemical changes occurring during the casting process, as they can affect key parameters such as the aluminum's fluidity and cooling rate. Cameras or other image acquisition devices are used to capture real-time images of samples taken during the casting process. These images provide crucial information on the aluminum's macromorphology and surface quality, helping to identify potential quality issues.

[0146] Data preprocessing is performed on acquired weather, temperature, humidity, casting temperature, and sampled image information. This preprocessing step may include data cleaning (e.g., noise removal and outlier processing), data transformation (e.g., normalization), and feature extraction (e.g., extracting key features from images). This preprocessed data is then used to calculate the casting production model and generate casting task commands.

[0147] The preprocessed forging data and casting control parameters are fed into a pre-set casting production model. This model, built using a machine learning algorithm, predicts the optimal parameters for the casting process based on the input data. These optimal parameters may include casting temperature, cooling rate, sampling location, and other factors, which together determine the final quality of the aluminum alloy standard sample. The optimal parameters calculated by the casting production model are used as casting task commands to directly guide the operation of the casting equipment. These commands ensure that the casting process proceeds according to the predetermined process requirements, thereby improving the consistency of the aluminum alloy standard sample.

[0148] During the casting process, the system may also need to monitor aluminum material quality indicators (such as composition, hardness, and tensile strength) in real time and feed this data back into the casting production model for adjustment. In this way, the system can continuously learn and optimize casting parameters to adapt to changes in production conditions such as raw material fluctuations and equipment aging.

[0149] In summary, step S105 achieves precise control of the casting process by acquiring key data from the casting process in real time, performing data preprocessing, calculating optimal parameters using a machine learning model, and generating casting task commands. This process not only improves the production quality and efficiency of aluminum alloy standard samples but also provides strong support for intelligent and automated production.

[0150] Specifically, the aluminum alloy standard sample production method described in the present invention, step S107 includes:

[0151] According to the requirements and specifications of the production of aluminum alloy standard samples, the cutting control parameters are determined. The cutting control parameters include cutting speed, cutting position, cutting angle, etc.

[0152] According to the cutting control parameters, determine the specific position to be cut on the aluminum material, and use appropriate marking tools to mark the aluminum material at the determined position to be cut;

[0153] According to the marked position of the aluminum material, use the cutting equipment to cut the aluminum material.

[0154] Cutting control parameters are determined based on the production requirements and specifications of aluminum alloy standard samples. These parameters are fundamental to the cutting operation and directly impact the dimensional accuracy and shape consistency of the cut aluminum. Cutting control parameters primarily include cutting speed, cutting position, and cutting angle. The cutting speed must be determined based on the material and thickness of the aluminum, as well as the performance of the cutting equipment, to ensure surface smoothness and cutting efficiency. The cutting position and cutting angle must strictly adhere to the product design drawings and process requirements to ensure that the cut aluminum meets the required size and shape.

[0155] After determining the cutting control parameters, use these parameters to determine the specific location on the aluminum material to be cut. Then, use a suitable marking tool (such as a scriber or laser marker) to clearly and accurately mark the aluminum surface. The marking should be easy to identify and durable, ensuring precise alignment during subsequent cutting operations. Cut the aluminum material using cutting equipment (such as a saw or shears) according to the marked locations. The selection of cutting equipment should be determined based on the material, thickness, and cutting requirements to ensure efficient and high-quality cutting. During the cutting process, ensure that the cutting equipment is stable, the cutting blade is sharp, and that the cutting is performed strictly according to the marked locations. Also, pay attention to controlling the cutting speed to avoid problems such as uneven cut surfaces or deformation of the aluminum material caused by excessively fast or slow cutting. After cutting, clean the cut surface promptly to remove burrs and flash to ensure quality.

[0156] After the cutting operation is completed, the cut aluminum material must undergo a quality inspection. Inspection content includes the flatness, dimensional accuracy, shape consistency, and surface quality of the cut surface. Through quality inspection, problems that arise during the cutting process can be discovered and addressed in a timely manner, ensuring that the quality of the aluminum alloy standard sample meets the requirements.

[0157] Specifically, the aluminum alloy standard sample production method described in the present invention, step S108 includes:

[0158] Data is collected from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain raw material traceability information, cooling device configuration parameters, mold preheating temperature and time, aluminum soup processing process parameters, casting temperature and sampling images, cooling process records, cutting position and marking information;

[0159] Classify the collected data and clean the classified data. Data cleaning includes removing duplicate data, processing missing data, and correcting erroneous data operations;

[0160] Use data visualization tools to convert the cleaned and validated data into visual forms, including charts, tables, and images.

[0161] Data is collected extensively from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup handling unit, casting unit, cooling unit, and cutting marking unit. These units cover all aspects of the production of aluminum alloy standard samples, ensuring the comprehensiveness and accuracy of the data.

[0162] The collected data includes raw material traceability information, cooling device configuration parameters, mold preheating temperature and time, aluminum bath processing parameters, casting temperature and sampling images, cooling process records, cutting positions and marking information, etc. This data reflects the key parameters and status of the production process and is crucial for subsequent data analysis and processing.

[0163] The collected data are classified and organized according to data type and source to facilitate subsequent data cleaning and analysis.

[0164] The classified and organized data is cleaned, including removing duplicate data, processing missing data, and correcting erroneous data. These operations ensure the accuracy and reliability of the data, providing a solid foundation for subsequent data analysis and visualization.

[0165] Use data visualization tools to convert cleaned and verified data into visual formats. These tools can present complex data in an intuitive and easy-to-understand manner, helping production personnel quickly understand the production process and product quality.

[0166] Visualization formats include charts, tables, and images. For example, a bar chart can be used to display output changes across different production units, a line chart can be used to show the trend of mold preheating temperature over time, and an image can be used to display the macroscopic appearance of sampled data. These visualization formats not only improve data readability but also help production personnel promptly identify production process problems and take appropriate measures.

[0167] Through in-depth analysis of visualized data, production personnel can understand the actual status of the production process and identify potential problems and areas for improvement. For example, if a production unit's output is consistently low, further analysis can be conducted to determine the cause and measures can be taken to increase output. If mold preheating temperatures fluctuate significantly, the preheating equipment's operating parameters can be adjusted to ensure mold temperature stability. Data visualization also provides strong support for production decision-making. Based on the visualized data, production personnel can evaluate the effectiveness of different production plans and select the optimal one to improve production efficiency and product quality.

[0168] In a second aspect, the present invention provides an aluminum alloy standard sample production system, which is applied to the aluminum alloy standard sample production method as described above, including:

[0169] The casting preparation unit obtains a data traceability table, which includes the target value of the aluminum alloy standard sample, the formulation data, and the raw materials used for each component when it is sold. It collects the parameters used in the production process of the aluminum alloy standard sample, stores the data traceability table and the parameters used in the production process of the aluminum alloy standard sample in a database, substitutes the data traceability table into the preset aluminum alloy standard sample production model, and generates the aluminum alloy standard sample production control parameters. The aluminum alloy standard sample production control parameters include cooling device control parameters, preheating mold control parameters, aluminum soup treatment control parameters, casting control parameters, cooling control parameters, and cutting control parameters;

[0170] A cooling device unit, wherein the cooling device executes cooling device control parameters, and the cooling device control parameters are used to adjust the water inlet and outlet of the cooling water bucket and the height of the automatic lifting device so that water enters or exits the cooling equipment in the cooling unit;

[0171] Preheating mold unit: The preheating equipment executes the preheating mold control parameters. The preheating equipment is used to maintain the temperature of the mold during the casting process, record the preheating temperature and time of the mold, and detect whether the preheating value each time meets the process standards;

[0172] The aluminum soup processing unit sends the aluminum soup processing parameters to the aluminum soup processing equipment. After the aluminum soup processing equipment executes the aluminum soup processing parameters, it monitors the data parameters during the aluminum soup processing process. When the aluminum soup meets the preset aluminum soup processing parameters, the casting unit is triggered;

[0173] The casting unit obtains weather, temperature, humidity, casting temperature, and sampling image information during the casting process, performs data preprocessing on the weather, temperature, humidity, casting temperature, and sampling image information during the casting process to obtain preprocessed forging data, substitutes the preprocessed forging data and casting control parameters into a preset casting production model, generates a casting task command, and sends the casting task command to the casting equipment, which casts the aluminum material after the aluminum soup treatment;

[0174] The cooling unit cools the aluminum material after casting according to the cooling control parameters, collects the temperature data of the aluminum material during the cooling process, and optimizes the cooling unit control parameters if the temperature data of the aluminum material is higher than the preset cooling standard temperature value;

[0175] The cutting unit determines the position of the aluminum material to be cut according to the cutting control parameters, marks the aluminum material according to the position of the aluminum material to be cut, obtains the marked position of the aluminum material, and cuts the aluminum material according to the marked position of the aluminum material;

[0176] The data review unit summarizes and classifies the information of the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark unit, and generates visual data for reviewing the production data of aluminum alloy standard samples.

[0177] Specifically, in the aluminum alloy standard sample production system of the present invention, the casting preparation unit is further used to:

[0178] Receive the objectives of the aluminum alloy standard sample production model, the objectives of the aluminum alloy standard sample production model include production efficiency and product quality parameters;

[0179] Obtain historical production data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain historical production data of aluminum alloy standard samples;

[0180] Feature extraction is performed on the historical production data of aluminum alloy standard samples, and the extracted features are used as input. Production efficiency and product quality parameters are used as output. The random forest model is trained using the historical production data of aluminum alloy standard samples to obtain an aluminum alloy standard sample production model.

[0181] Specifically, in the aluminum alloy standard sample production system described in the present invention, the casting unit is further used to:

[0182] Obtain weather, temperature, and humidity information during the casting process in real time, and use cameras or other image acquisition devices to obtain sampled image information;

[0183] Data preprocessing is performed on the acquired weather, temperature, humidity information, casting temperature, and sampled image information. The preprocessed data will be used for casting production model calculation and casting task command generation;

[0184] The preprocessed forging data and casting control parameters are substituted into the preset casting production model. The casting production model is based on machine learning and predicts the optimal parameters of the casting process according to the input data, and uses the optimal parameters as the casting task command.

[0185] Specifically, in the aluminum alloy standard sample production system described in the present invention, the cutting unit is further used to:

[0186] According to the requirements and specifications of the production of aluminum alloy standard samples, the cutting control parameters are determined. The cutting control parameters include cutting speed, cutting position, cutting angle, etc.

[0187] According to the cutting control parameters, determine the specific position to be cut on the aluminum material, and use appropriate marking tools to mark the aluminum material at the determined position to be cut;

[0188] According to the marked position of the aluminum material, use the cutting equipment to cut the aluminum material.

[0189] Specifically, in the aluminum alloy standard sample production system described in the present invention, the data review unit is further used to:

[0190] Data is collected from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain raw material traceability information, cooling device configuration parameters, mold preheating temperature and time, aluminum soup processing process parameters, casting temperature and sampling images, cooling process records, cutting position and marking information;

[0191] Classify the collected data and clean the classified data. Data cleaning includes removing duplicate data, processing missing data, and correcting erroneous data operations;

[0192] Use data visualization tools to convert the cleaned and validated data into visual forms, including charts, tables, and images.

[0193] The present invention provides a method and system for producing aluminum alloy standard samples, aiming to solve the problem that existing technologies cannot effectively integrate and analyze aluminum alloy standard sample data. The specific solution is as follows:

[0194] The data traceability table records the target values ​​of aluminum alloy standard samples, formulation data, and the raw materials used for each component during sales, ensuring data traceability. The data traceability table and parameters collected during the production process are stored in a database for centralized data management and long-term preservation.

[0195] Aluminum Alloy Standard Sample Production Model: Utilizing historical production data and feature extraction, the production model is trained using machine learning algorithms such as random forests. The data traceability table is inserted into the production model to generate production control parameters, including cooling device control parameters, preheating mold control parameters, aluminum bath processing control parameters, casting control parameters, cooling control parameters, and cutting control parameters.

[0196] Each production unit (such as cooling equipment, preheating mold equipment, aluminum bath processing equipment, and casting equipment) automatically performs corresponding operations based on generated control parameters, reducing human intervention and improving production efficiency and data accuracy. Each production unit is integrated with the data access unit to achieve real-time data collection, transmission, and processing, ensuring data timeliness and consistency.

[0197] During the casting process, weather, temperature, humidity, and sampled image data are collected in real time. After data preprocessing, it is input into the casting production model to generate optimal casting parameters and adjust them in real time. During the cooling process, based on the collected aluminum material temperature data, if it exceeds the preset standard, the cooling unit control parameters are optimized to ensure product quality.

[0198] Data is collected from each production unit, including raw material traceability information, cooling device configuration parameters, mold preheating temperature and time, aluminum bath processing parameters, casting temperature and sampling images, cooling process records, cutting positions and marking information, etc. The collected data is categorized, cleaned, and verified to ensure data accuracy. Data visualization tools are used to convert the cleaned and verified data into charts, tables, and images to facilitate review and analysis of production data.

[0199] In summary, the present invention effectively solves the problem that existing technologies are unable to effectively integrate and analyze aluminum alloy standard sample data through data traceability, model generation control parameters, automated and integrated production, real-time monitoring and optimization, data aggregation and visualization, and comprehensive quality control, thereby improving production efficiency and product quality.

Claims

1. A method for producing an aluminum alloy standard sample, characterized in that: include: Step S101: Obtain a data traceability table, which includes target values ​​of the aluminum alloy standard sample, formulation data, and raw materials used for each component when it is sold; collect parameters used in the production process of the aluminum alloy standard sample; store the data traceability table and the parameters used in the production process of the aluminum alloy standard sample in a database; substitute the data traceability table into a preset aluminum alloy standard sample production model to generate aluminum alloy standard sample production control parameters; the aluminum alloy standard sample production control parameters include cooling device control parameters, preheating mold control parameters, aluminum slurry treatment control parameters, casting control parameters, cooling control parameters, and cutting control parameters; Step S102: The cooling device executes the cooling device control parameters, which are used to adjust the water inlet and outlet of the cooling water bucket and the height of the automatic lifting device so that water can enter or exit the cooling device in the cooling unit; Step S103: The preheating device executes the preheating mold control parameters. The preheating device is used to maintain the temperature of the mold during the casting process, record the preheating temperature and time of the mold, and detect whether each preheating value meets the process standard; Step S104: sending the aluminum slurry processing parameters to the aluminum slurry processing equipment. After the aluminum slurry processing equipment executes the aluminum slurry processing parameters, it monitors the data parameters during the aluminum slurry processing process. When the aluminum slurry meets the preset aluminum slurry processing parameters, the casting unit is triggered. Step S105: Acquire weather, temperature, humidity, casting temperature, and sampled image information during the casting process, perform data preprocessing on the acquired weather, temperature, humidity, casting temperature, and sampled image information to obtain preprocessed forging data, substitute the preprocessed forging data and casting control parameters into a preset casting production model, generate a casting task command, send the casting task command to the casting equipment, and cast the aluminum material after the aluminum slurry treatment; Step S106, cooling the cast aluminum material according to the cooling control parameters, collecting temperature data of the aluminum material during the cooling process, and optimizing the cooling unit control parameters if the temperature data of the aluminum material is higher than a preset cooling standard temperature value; Step S107, determining the position of the aluminum material to be cut according to the cutting control parameters, marking the aluminum material according to the position of the aluminum material to be cut to obtain the marked position of the aluminum material, and cutting the aluminum material according to the marked position of the aluminum material; Step S108, summarize and classify the information of the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark unit, and generate visual data for reviewing the production data of the aluminum alloy standard sample.

2. The method for producing an aluminum alloy standard sample according to claim 1, wherein: The step S101 includes: Receive the objectives of the aluminum alloy standard sample production model, the objectives of the aluminum alloy standard sample production model include production efficiency and product quality parameters; Obtain historical production data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain historical production data of aluminum alloy standard samples; Feature extraction is performed on the historical production data of aluminum alloy standard samples, and the extracted features are used as input. Production efficiency and product quality parameters are used as output. The random forest model is trained using the historical production data of aluminum alloy standard samples to obtain an aluminum alloy standard sample production model.

3. The method for producing an aluminum alloy standard sample according to claim 1, wherein: The step S105 includes: Obtain weather, temperature, and humidity information during the casting process in real time, and use cameras or other image acquisition devices to obtain sampled image information; Data preprocessing is performed on the acquired weather, temperature, humidity information, casting temperature, and sampled image information. The preprocessed data will be used for casting production model calculation and casting task command generation; The preprocessed forging data and casting control parameters are substituted into the preset casting production model. The casting production model is based on machine learning and predicts the optimal parameters of the casting process according to the input data, and uses the optimal parameters as the casting task command.

4. The method for producing an aluminum alloy standard sample according to claim 1, wherein: The step S107 includes: Determine the cutting control parameters according to the production requirements and specifications of aluminum alloy standard samples. The cutting control parameters include cutting speed, cutting position and cutting angle; According to the cutting control parameters, determine the specific position to be cut on the aluminum material, and use appropriate marking tools to mark the aluminum material at the determined position to be cut; According to the marked position of the aluminum material, use the cutting equipment to cut the aluminum material.

5. The method for producing an aluminum alloy standard sample according to claim 1, wherein: The step S108 includes: Data is collected from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain raw material traceability information, cooling device configuration parameters, mold preheating temperature and time, aluminum soup processing process parameters, casting temperature and sampling images, cooling process records, cutting position and marking information; Classify the collected data and clean the classified data. Data cleaning includes removing duplicate data, processing missing data, and correcting erroneous data operations; Use data visualization tools to convert the cleaned and validated data into visual forms, including charts, tables, and images.

6. An aluminum alloy standard sample production system, applied to an aluminum alloy standard sample production method according to any one of claims 1 to 5, characterized in that: include: The casting preparation unit obtains a data traceability table, which includes the target value of the aluminum alloy standard sample, the formulation data, and the raw materials used for each component when it is sold. It collects the parameters used in the production process of the aluminum alloy standard sample, stores the data traceability table and the parameters used in the production process of the aluminum alloy standard sample in a database, substitutes the data traceability table into the preset aluminum alloy standard sample production model, and generates the aluminum alloy standard sample production control parameters. The aluminum alloy standard sample production control parameters include cooling device control parameters, preheating mold control parameters, aluminum soup treatment control parameters, casting control parameters, cooling control parameters, and cutting control parameters; A cooling device unit, wherein the cooling device executes cooling device control parameters, and the cooling device control parameters are used to adjust the water inlet and outlet of the cooling water bucket and the height of the automatic lifting device so that water enters or exits the cooling equipment in the cooling unit; Preheating mold unit: The preheating equipment executes the preheating mold control parameters. The preheating equipment is used to maintain the temperature of the mold during the casting process, record the preheating temperature and time of the mold, and detect whether the preheating value each time meets the process standards; The aluminum soup processing unit sends the aluminum soup processing parameters to the aluminum soup processing equipment. After the aluminum soup processing equipment executes the aluminum soup processing parameters, it monitors the data parameters during the aluminum soup processing process. When the aluminum soup meets the preset aluminum soup processing parameters, the casting unit is triggered; The casting unit obtains weather, temperature, humidity, casting temperature, and sampling image information during the casting process, performs data preprocessing on the weather, temperature, humidity, casting temperature, and sampling image information during the casting process to obtain preprocessed forging data, substitutes the preprocessed forging data and casting control parameters into a preset casting production model, generates a casting task command, and sends the casting task command to the casting equipment, which then casts the aluminum material after the aluminum soup treatment; The cooling unit cools the aluminum material after casting according to the cooling control parameters, collects the temperature data of the aluminum material during the cooling process, and optimizes the cooling unit control parameters if the temperature data of the aluminum material is higher than the preset cooling standard temperature value; The cutting unit determines the position of the aluminum material to be cut according to the cutting control parameters, marks the aluminum material according to the position of the aluminum material to be cut, obtains the marked position of the aluminum material, and cuts the aluminum material according to the marked position of the aluminum material; The data review unit summarizes and classifies the information of the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark unit, and generates visual data for reviewing the production data of aluminum alloy standard samples.

7. The aluminum alloy standard sample production system according to claim 6, characterized in that: The casting preparation unit is further used for: Receive the objectives of the aluminum alloy standard sample production model, the objectives of the aluminum alloy standard sample production model include production efficiency and product quality parameters; Obtain historical production data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain historical production data of aluminum alloy standard samples; Feature extraction is performed on the historical production data of aluminum alloy standard samples, and the extracted features are used as input. Production efficiency and product quality parameters are used as output. The random forest model is trained using the historical production data of aluminum alloy standard samples to obtain an aluminum alloy standard sample production model.

8. The aluminum alloy standard sample production system according to claim 6, characterized in that: The casting unit is further used for: Obtain weather, temperature, and humidity information during the casting process in real time, and use cameras or other image acquisition devices to obtain sampled image information; Data preprocessing is performed on the acquired weather, temperature, humidity information, casting temperature, and sampled image information. The preprocessed data will be used for casting production model calculation and casting task command generation; The preprocessed forging data and casting control parameters are substituted into the preset casting production model. The casting production model is based on machine learning and predicts the optimal parameters of the casting process according to the input data, and uses the optimal parameters as the casting task command.

9. The aluminum alloy standard sample production system according to claim 6, characterized in that: The cutting unit is further used for: Determine the cutting control parameters according to the production requirements and specifications of aluminum alloy standard samples. The cutting control parameters include cutting speed, cutting position and cutting angle; According to the cutting control parameters, determine the specific position to be cut on the aluminum material, and use appropriate marking tools to mark the aluminum material at the determined position to be cut; According to the marked position of the aluminum material, use the cutting equipment to cut the aluminum material.

10. The aluminum alloy standard sample production system according to claim 6, characterized in that: The data review unit is further configured to: Data is collected from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit, and cutting marking unit to obtain raw material traceability information, cooling device configuration parameters, mold preheating temperature and time, aluminum soup processing process parameters, casting temperature and sampling images, cooling process records, cutting position and marking information; Classify the collected data and clean the classified data. Data cleaning includes removing duplicate data, processing missing data, and correcting erroneous data operations; Use data visualization tools to convert the cleaned and validated data into visual forms, including charts, tables, and images.

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