Aluminum alloy standard sample production method and system

Abstract

The invention relates to the technical field of aluminum alloy production data processing, and provides an aluminum alloy standard sample production method and system, and the method comprises the steps: obtaining a data traceability table, substituting the data traceability table into a preset production model, and generating control parameters of each production unit; according to the system, automatic control over the steps of a cooling device, a preheating mold, molten aluminum treatment, casting, cooling, cutting and the like is achieved, the system comprises a casting preparation unit, a cooling device unit, a preheating mold unit, a molten aluminum treatment unit, a casting unit, a cooling unit, a cutting unit and a data consulting unit, traceability and visualization of production data are achieved, and the production efficiency and the product quality are improved; and the intelligence and transparency of the production process are enhanced, and comprehensive optimization is provided for production of the aluminum alloy standard sample.

Description

Technical Field

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

[0002] Aluminum alloy standard samples are the basis for quality control and testing of aluminum alloy products. During the production process, professional cooling devices are used to preheat and cool the mold, and the aluminum soup is refined and degassed. Through the steps of casting, sampling, cooling, taking out, cutting and marking, aluminum alloy standard samples that meet the requirements are produced. Finally, after the quality assessment process such as upper and lower inspections, the quality of aluminum alloy standard samples meets the established standards, providing a reliable reference for the production and testing of aluminum alloy products.

[0003] In the production process of aluminum alloy standard samples, there are the following technical pain points: from the traceability record of raw materials to the parameter setting in each step of the production process, casting temperature, refining agent dosage, Ar treatment time, etc., all need to be accurately recorded. Any data deviation may affect the accuracy and representativeness of the final sample. Since the production process involves multiple links and complex physical and chemical changes, the existing technology cannot effectively integrate and analyze the aluminum alloy standard sample data. In order to solve this technical pain point, the present invention provides an aluminum alloy standard sample production method and system. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides a method and system for producing aluminum alloy standard samples to solve the problem that the prior art 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: In a first aspect, the present invention provides a method for producing an aluminum alloy standard sample, comprising: Step S101, obtaining a data traceability table, the data traceability table includes target values ​​of aluminum alloy standard samples, formula production data and raw materials used for each component when sold, collecting parameters in the process of producing aluminum alloy standard samples, storing the data traceability table and the parameters in the process of aluminum alloy standard samples in a database, substituting the data traceability table into a preset aluminum alloy standard sample production model, generating aluminum alloy standard sample production control parameters, the aluminum alloy standard sample production control parameters including cooling device control parameters, preheating mold control parameters, aluminum soup processing control parameters, casting control parameters, cooling control parameters and cutting control parameters; Step S102, the cooling device executes the 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 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 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 in the aluminum soup processing process. When the aluminum soup meets the preset aluminum soup processing parameters, the casting unit is triggered; Step S105, obtaining weather, temperature, humidity information, casting temperature and sampling image information during the casting process, performing data preprocessing on the weather, temperature, humidity information, casting temperature and sampling image information during the casting process, obtaining preprocessed forging data, substituting the preprocessed forging data and casting control parameters into a preset casting production model, generating a casting task command, sending the casting task command to the casting equipment, and the casting equipment casting the aluminum material after the aluminum soup treatment; Step S106, cooling the aluminum material after casting according to the cooling control parameters, collecting the 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 the 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, obtaining 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 aluminum alloy standard samples.

[0006] Furthermore, in the aluminum alloy standard sample production method described in the present invention, step S101 comprises: 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 mark unit to obtain historical production data of aluminum alloy standard samples; The historical production data of aluminum alloy standard samples are used for feature extraction, and the extracted features are used as input. The 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 the aluminum alloy standard sample production model.

[0007] Furthermore, in the aluminum alloy standard sample production method described in the present invention, step S105 comprises: Obtain weather, temperature and humidity information in real time during the casting process, and use cameras or other image acquisition devices to obtain sampled image information; The acquired weather, temperature, humidity information, casting temperature and sampling image information are preprocessed. 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, which predicts the optimal parameters of the casting process according to the input data and uses the optimal parameters as the casting task commands.

[0008] Furthermore, in the aluminum alloy standard sample production method described in the present invention, step S107 comprises: 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.

[0009] According to the cutting control parameters, the specific position to be cut is determined on the aluminum material, and at the determined position to be cut, the aluminum material is marked with a suitable marking tool; According to the marked position of the aluminum material, use the cutting equipment to cut the aluminum material.

[0010] Furthermore, in the aluminum alloy standard sample production method described in the present invention, step S108 comprises: Collect data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark 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.

[0011] In a second aspect, the present invention provides an aluminum alloy standard sample production system, which is applied to an aluminum alloy standard sample production method as described above, comprising: The casting preparation unit obtains a data traceability table, which includes the target value of the aluminum alloy standard sample, the formula production data, and the raw materials used for each component when it is sold; collects the parameters in the process of making the aluminum alloy standard sample; stores the data traceability table and the parameters in the process of the aluminum alloy standard sample in the database; substitutes the data traceability table into the preset aluminum alloy standard sample production model to generate the aluminum alloy standard sample production control parameters, which include cooling device control parameters, preheating mold control parameters, aluminum soup processing control parameters, casting control parameters, cooling control parameters, and cutting control parameters; A cooling device unit, the cooling device executes cooling device control parameters, 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 device 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 each preheating value 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 in 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 information, casting temperature and sampling image information during the casting process, performs data preprocessing on the weather, temperature, humidity information, casting temperature and sampling image information during the casting process, obtains preprocessed forging data, substitutes the preprocessed forging data and casting control parameters into a preset casting production model, generates a casting task command, sends the casting task command to the casting equipment, and the manufacturing equipment 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 control parameters of the cooling unit 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.

[0012] Furthermore, in the aluminum alloy standard sample production system described in the present invention, the casting preparation unit is also 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 mark unit to obtain historical production data of aluminum alloy standard samples; The historical production data of aluminum alloy standard samples are used for feature extraction, and the extracted features are used as input. The 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 the aluminum alloy standard sample production model.

[0013] Furthermore, in the aluminum alloy standard sample production system described in the present invention, the casting unit is also used for: Obtain weather, temperature and humidity information in real time during the casting process, and use cameras or other image acquisition devices to obtain sampled image information; The acquired weather, temperature, humidity information, casting temperature and sampling image information are preprocessed. 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, which predicts the optimal parameters of the casting process according to the input data and uses the optimal parameters as the casting task commands.

[0014] Furthermore, in the aluminum alloy standard sample production system described in the present invention, the cutting unit is also used for: 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.

[0015] According to the cutting control parameters, the specific position to be cut is determined on the aluminum material, and at the determined position to be cut, the aluminum material is marked with a suitable marking tool; According to the marked position of the aluminum material, use the cutting equipment to cut the aluminum material.

[0016] Furthermore, in the aluminum alloy standard sample production system described in the present invention, the data review unit is also used for: Collect data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark 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.

[0017] The beneficial effects of the present invention are mainly reflected in the following aspects: The present invention significantly improves the production efficiency of aluminum alloy standard samples through automated and intelligent production processes. The collaborative work between various production units (such as cooling device units, preheating mold units, aluminum soup processing units, etc.) and the generation of casting task commands based on data models reduce manual intervention and waiting time, making the production process smoother and more efficient.

[0018] The present invention ensures the quality stability and consistency of the aluminum alloy standard sample by accurately controlling various parameters in the production process (such as cooling device control parameters, preheating mold control parameters, aluminum soup treatment control parameters, etc.). At the same time, through the quality evaluation process such as upper and lower inspections, the product qualification rate is further improved and the scrap rate is reduced.

[0019] The present invention has established a complete data traceability system, which comprehensively traces and records the raw materials, parameters, operation records, etc. in the production process. This not only helps to quickly locate and analyze the causes of problem products, but also provides valuable data support for subsequent production improvements and quality improvements. Through data visualization and analysis, the present invention can help production personnel to timely understand the resource consumption (such as energy, raw materials, etc.) in the production process, so as to rationally allocate resources and avoid waste and shortages. At the same time, production decisions based on data can also be more scientific and accurate, further improving resource utilization efficiency.

[0020] The implementation of this invention promotes the intelligent process of aluminum alloy standard sample production. By introducing advanced technologies such as machine learning and data models, the automatic control and optimization adjustment of the production process are realized, laying a solid foundation for future intelligent manufacturing and digital factory construction.

[0021] 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

[0022] 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.

[0023] Figure 1 A schematic flow chart of a method for producing a standard aluminum alloy sample provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings.

[0025] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0026] In a first aspect, the present invention provides a method for producing an aluminum alloy standard sample, comprising: Step S101, obtaining a data traceability table, the data traceability table includes target values ​​of aluminum alloy standard samples, formula production data and raw materials used for each component when sold, collecting parameters in the process of producing aluminum alloy standard samples, storing the data traceability table and the parameters in the process of aluminum alloy standard samples in a database, substituting the data traceability table into a preset aluminum alloy standard sample production model, generating aluminum alloy standard sample production control parameters, the aluminum alloy standard sample production control parameters including cooling device control parameters, preheating mold control parameters, aluminum soup processing control parameters, casting control parameters, cooling control parameters and cutting control parameters; The data traceability sheet is a document that details the target values ​​of aluminum alloy standard samples, recipe production data, and the raw materials used for each component when it is sold. This information is essential to ensure the quality and traceability of the product.

[0027] In the actual production process of aluminum alloy standard samples, multiple links and parameters are involved, such as temperature, time, dosage, etc. The data traceability table and the parameters collected during the production process are stored in a database.

[0028] 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, and can 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: 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.

[0029] Preheating mold control parameters: used to maintain the temperature of the mold during the casting process and record the preheating temperature and time.

[0030] Aluminum soup processing control parameters: parameters related to the refining, degassing and other processing processes of aluminum soup.

[0031] Casting control parameters: including key casting parameters such as casting temperature and sampling method.

[0032] Cooling control parameters: used to control the cooling process of aluminum after casting to ensure product quality.

[0033] Cutting control parameters: determine the cutting position, speed, angle, etc. of the aluminum material to meet product specification requirements.

[0034] Step S102, the cooling device executes the 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 device in the cooling unit; 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.

[0035] The cooling water bucket is an important part of the cooling device. By adjusting its water inlet and outlet, the flow and speed of the cooling water can be controlled. The cooling device control parameters specify specific water inlet and outlet settings to adapt to different cooling needs. For example, when fast cooling is required, the water inlet flow can be increased; when slow cooling is required, the water inlet flow can be reduced or the opening degree of the outlet can be adjusted.

[0036] The automatic lifting device is used to control the height of cooling equipment (such as cooling water buckets), thereby affecting the contact degree between cooling water and aluminum alloy standard samples and the cooling effect. According to the instructions of the cooling device control parameters, the automatic lifting device will be adjusted to the appropriate height. For example, in the initial cooling stage, it may be necessary to lower the cooling device to a lower position to ensure sufficient contact; in the subsequent stage, it may be necessary to raise the cooling device to reduce the contact time and avoid overcooling.

[0037] Water enters or leaves the cooling device in the cooling unit: 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 port to complete a cooling cycle. By executing the cooling device control parameters, the cooling device can automatically and accurately complete the cooling process without manual intervention, thereby improving production efficiency and product quality. In addition, since 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.

[0038] 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; The preheating mold control parameters are generated by the aluminum alloy standard sample production model based on the data traceability table and real-time production conditions. They are specifically used to guide the operation of the preheating equipment to maintain the temperature stability of the mold during the casting process. The preheating equipment performs preheating treatment on the mold according to the instructions of the preheating mold control parameters, which involves heating the mold to a specific temperature range and maintaining it for a period of time to ensure uniform temperature distribution. During the casting process, the preheating equipment continues to work to maintain the mold within the predetermined temperature range.

[0039] The preheating equipment is also responsible for recording the preheating temperature and time of the mold. This data is important for monitoring the production process, ensuring that process standards are adhered to, and for quality traceability. The preheating equipment is also equipped with a detection mechanism to detect in real time whether the preheating value of the mold meets the process standards. If the preheating value is found to 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 levels.

[0040] By executing the preheating mold control parameters, the preheating equipment can realize the automation and precise control of mold preheating without manual intervention, thereby improving production efficiency and product quality. In addition, since the preheating mold control parameters are generated based on the aluminum alloy standard sample production model, they can be dynamically adjusted according to the actual situation to adapt to different production conditions and needs. Correct mold preheating can enable the aluminum liquid to solidify quickly when injected into the mold, forming a dense microstructure, thereby improving the strength and durability of the product. At the same time, stable mold temperature can also reduce thermal stress and deformation during casting, further improving the dimensional accuracy and surface quality of the product.

[0041] Step S104, sending 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 in the aluminum soup processing process. When the aluminum soup meets the preset aluminum soup processing parameters, the casting unit is triggered; In step S104, the aluminum soup processing parameters are sent to the aluminum soup processing equipment. This step is a link in the production process of aluminum alloy standard samples, so that the quality of aluminum soup (i.e. molten aluminum alloy material) before casting reaches the predetermined standard. The following is a detailed analysis of this step: Aluminum soup processing parameters are generated based on the aluminum alloy standard sample production model. They contain a series of instructions and set values ​​that guide the operation of aluminum soup processing equipment. These parameters are designed to improve the key indicators such as the composition, temperature, gas content, etc. of aluminum soup through specific physical or chemical processes to meet casting requirements.

[0042] The aluminum bath treatment parameters are sent to the aluminum bath treatment equipment through a preset 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.

[0043] After receiving the parameters, the aluminum soup processing equipment starts to perform the corresponding processing operations, such as adding refining agents to remove impurities, performing Ar treatment to remove gas and salt, or adjusting the heating power to control the aluminum soup temperature.

[0044] During the processing, the aluminum soup processing equipment will monitor various data parameters of the aluminum soup in real time, such as temperature, component content, gas content, etc. These data are collected by sensors and fed back to the control system. When the aluminum soup processing equipment detects that the various data parameters of the aluminum soup meet the preset aluminum soup processing parameter requirements, the aluminum soup is considered to have been processed and qualified.

[0045] When the aluminum soup processing is completed and meets the standards, the aluminum soup processing equipment will send a signal to the casting unit to trigger the subsequent casting operation. This ensures that casting will only be carried out when the aluminum soup quality meets the standards, thereby ensuring the quality of the aluminum alloy standard sample.

[0046] Step S105, obtaining weather, temperature, humidity information, casting temperature and sampling image information during the casting process, performing data preprocessing on the weather, temperature, humidity information, casting temperature and sampling image information during the casting process, obtaining preprocessed forging data, substituting the preprocessed forging data and casting control parameters into a preset casting production model, generating a casting task command, sending the casting task command to the casting equipment, and the manufacturing equipment casting the aluminum material after the aluminum soup treatment; Environmental factors such as weather, temperature, and humidity will affect the cooling rate of the aluminum soup and the temperature distribution of the mold during the casting process.

[0047] Casting temperature: Casting temperature is a key factor to ensure 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.

[0048] 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.

[0049] The acquired weather, temperature, humidity information, casting temperature and sampled image information are preprocessed. The preprocessing process may include data cleaning (removing noise and outliers), data conversion (such as normalization or standardization) and feature extraction for subsequent model processing.

[0050] 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 the input data. These parameters may include casting speed, cooling rate, mold temperature, etc.

[0051] Substitute the pre-processed forging data and casting control parameters into the casting production model, and the model will calculate the optimal casting task command based on these data. The casting task command includes a series of specific operation instructions, such as casting speed, cooling method, mold temperature setting, etc. The casting task command is sent to the casting equipment, and the casting equipment casts the aluminum material after aluminum soup treatment according to the command.

[0052] By parameterizing the casting process and introducing it into the casting production model, the casting process is automated and controlled in real time. This not only improves production efficiency, but also reduces the impact of human errors and uncertainties on product quality. Real-time acquisition and processing of casting process data enables the production system to quickly respond to environmental changes and changes in production conditions, thereby maintaining stable product quality.

[0053] Step S106, cooling the aluminum material after casting according to the cooling control parameters, collecting the 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 the preset cooling standard temperature value; In step S106, if the temperature data of the aluminum material during the cooling process is higher than the preset cooling standard temperature value, the cooling unit control parameters need to be optimized. 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 genetic algorithm: Determine the value range of the cooling unit control parameters (such as cooling water flow rate, cooling time, cooling medium temperature, etc.). 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.

[0054] 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 the fitness needs to be calculated, the coding is converted back to the original parameter value.

[0055] Define a fitness function to evaluate the quality of each individual. In this example, the fitness function can be the absolute value of the difference between the temperature of the aluminum material during the cooling process and the preset cooling standard temperature value, or the square of the difference, etc. The goal is to minimize this difference.

[0056] 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.

[0057] According to the fitness value of the individual, excellent individuals are selected as parents to generate the next generation. Common selection strategies include roulette selection, tournament selection, etc. A parent population is generated through the selection operation for subsequent crossover and mutation operations.

[0058] Set a crossover probability to determine the possibility of crossover operation of parent individuals. Randomly pair individuals in the parent population, and then generate offspring individuals according to a certain crossover method (such as single-point crossover, double-point crossover, uniform crossover, etc.). Set a mutation probability to determine the possibility of mutation of offspring individuals. Randomly mutate individuals in the offspring population according to the mutation probability. The mutation method can be to change a certain bit in the code (binary code) or randomly adjust the parameter value within a certain range (real code).

[0059] Replace the parent population with the offspring population, or merge the parent and offspring populations and sort them by fitness value, and select the first N individuals as the new population. Set the termination condition: it can be reaching the maximum number of iterations, the fitness value reaches the preset threshold, or the fitness value of the population is no longer significantly improved. When the termination condition is met, stop the iteration and output the individual with the highest fitness value in the current population as the optimal solution, that is, the optimized cooling unit control parameters.

[0060] 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.

[0061] 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, obtaining the marked position of the aluminum material, and cutting the aluminum material according to the marked position of the aluminum material; According to the cutting control parameters, including cutting length, cutting angle and other requirements, the specific location on the aluminum material that needs to be cut is accurately calculated and determined. These control parameters are usually pre-set according to product specifications and design requirements.

[0062] After determining the position to be cut, use a suitable marking tool (such as a marking pen, laser marker, etc.) to mark the surface of the aluminum material. The marking should be clear and accurate so that the subsequent cutting operation can be accurately aligned.

[0063] The marking contents may include cut-off lines, reference points, etc., depending on the cut-off requirements and process flow.

[0064] 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.

[0065] According to the marked 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 specification requirements.

[0066] 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.

[0067] 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 aluminum alloy standard samples.

[0068] In step S108, the information of each production unit is summarized and classified, and visual data is generated, which is an important part of the production process of aluminum alloy standard samples. This step aims to integrate all the data generated from casting preparation to cutting marking, making it easy to access and analyze, so as to help production managers fully understand the production status, optimize the production process, and improve product quality. The following is a detailed analysis of this step: Casting preparation unit: collect and summarize data traceability tables, raw material traceability information, formula production data, and pre-casting preparation parameters, etc.

[0069] Cooling device unit: records the water inlet and outlet adjustment parameters of the cooling water bucket, the height setting of the automatic lifting device, the temperature data during the cooling process, etc.

[0070] Preheating mold unit: Arrange the mold's preheating temperature, preheating time, preheating times, and any abnormal conditions during the preheating process.

[0071] Aluminum soup treatment unit: summarizes the parameters in 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 aluminum soup after treatment.

[0072] Casting unit: collects weather, temperature, humidity information, casting temperature, sampling image information and casting control parameters during the casting process.

[0073] Cooling unit: records temperature data, cooling time, usage of cooling medium, etc. during the cooling process.

[0074] Cutting marking unit: organize the information such as cutting control parameters, cutting position, cutting angle, sample size after cutting and appearance quality.

[0075] Use data visualization tools (such as charts, tables, images, etc.) to transform the summarized and classified data so that it can be presented in an intuitive and easy-to-understand form. Visualized data should include key production indicators, trend analysis, abnormal warnings and other information so that production managers can quickly identify problems and take appropriate measures.

[0076] Production managers can consult the visualized data to fully understand the production status of aluminum alloy standard samples, including production efficiency, product quality, equipment operation status, etc. Based on the analysis of visualized data, potential problems in the production process can be discovered in a timely manner, such as fluctuations in raw material quality, equipment performance degradation, process parameter deviations, etc., so as to take 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 the company's production decisions.

[0077] Specifically, the aluminum alloy standard sample production method described in the present invention, 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 mark unit to obtain historical production data of aluminum alloy standard samples; The historical production data of aluminum alloy standard samples are used for feature extraction, and the extracted features are used as input. The 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 the aluminum alloy standard sample production model.

[0078] Receive the goals of the aluminum alloy standard sample production model. These goals usually include production efficiency (such as output per unit time) and product quality parameters (such as sample composition accuracy, physical properties, etc.). These goals are the basis for the subsequent production control parameter generation and optimization.

[0079] Collect historical production data from various production units (including casting preparation unit, cooling device unit, preheating mold unit, aluminum soup handling unit, casting unit, cooling unit and cutting marking unit). These data cover the entire process from raw material preparation to finished product cutting and are an important source of information reflecting the actual production status.

[0080] Perform feature extraction on the collected historical production data. Feature extraction is a key step in data mining and machine learning, which aims to extract useful information for model training from raw data. In the production of aluminum alloy standard samples, these features may include raw material composition ratio, process parameters (such as temperature, time, flow, etc.), equipment status, etc.

[0081] The extracted features are used as input, and 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. Random forest is an ensemble learning method that improves the accuracy and stability of the model by building multiple decision trees and combining their prediction results. In this step, the random forest model is used to learn the complex relationship between historical production data and production efficiency and product quality.

[0082] The trained random forest model can predict the corresponding production efficiency and quality parameters based on the input features. In actual production, the optimized production control parameters can be obtained by inputting the current production conditions (such as raw material composition, equipment status, etc.) into the model. These 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, which together guide the production process of aluminum alloy standard samples.

[0083] As production progresses and new data is generated, the historical production data set can be regularly updated and the random forest model can be retrained. This allows the model to continuously adapt to changes in production conditions and further improve production efficiency and product quality.

[0084] In summary, step S101 provides scientific and reasonable guidance for the production of aluminum alloy standard samples through a series of steps such as receiving production model targets, acquiring historical production data, feature extraction, training random forest models, and generating production control parameters. This process not only makes full use of the valuable information in historical production data, but also realizes the continuous optimization and improvement of production models through machine learning methods.

[0085] Specifically, in the aluminum alloy standard sample production method described in the present invention, step S105 comprises: Obtain weather, temperature and humidity information in real time during the casting process, and use cameras or other image acquisition devices to obtain sampled image information; The acquired weather, temperature, humidity information, casting temperature and sampling image information are preprocessed. 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, which predicts the optimal parameters of the casting process according to the input data and uses the optimal parameters as the casting task commands.

[0086] Environmental sensors are used to obtain weather conditions, temperature, and humidity information at the casting site in real time. This information is crucial to understanding the physical and chemical changes in the casting process, as they may affect key parameters such as the fluidity and cooling rate of aluminum. Cameras or other image acquisition devices are used to obtain sampling image information during the casting process in real time. These images provide important information such as the macroscopic morphology and surface quality of aluminum, which helps to detect potential quality problems in a timely manner.

[0087] The acquired weather, temperature, humidity information, casting temperature and sampled image information are preprocessed. The preprocessing steps may include data cleaning (such as noise removal, outlier processing), data transformation (such as normalization, standardization) and feature extraction (such as extracting key features from images). The preprocessed data will be used for subsequent casting production model calculation and casting task command generation.

[0088] The preprocessed forging data and casting control parameters are substituted into the preset casting production model. This model is built based on a machine learning algorithm and can predict the optimal parameters of the casting process based on the input data. These optimal parameters may include casting temperature, cooling rate, sampling location, etc., which together determine the final quality of the aluminum alloy standard sample. The optimal parameters calculated by the casting production model will be used as casting task commands to directly guide the operation of the casting equipment. These commands ensure that the casting process is carried out according to the predetermined process requirements, thereby improving the consistency of the aluminum alloy standard sample.

[0089] During the casting process, the system may also need to monitor the quality indicators of aluminum materials (such as composition, hardness, tensile strength, etc.) in real time and feed this data back to 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.

[0090] In summary, step S105 achieves precise control of the casting process by acquiring key data in 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.

[0091] Specifically, in the aluminum alloy standard sample production method described in the present invention, step S107 includes: 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.

[0092] According to the cutting control parameters, the specific position to be cut is determined on the aluminum material, and at the determined position to be cut, the aluminum material is marked with a suitable marking tool; According to the marked position of the aluminum material, use the cutting equipment to cut the aluminum material.

[0093] According to the requirements and specifications of aluminum alloy standard sample production, the cutting control parameters are determined. These parameters are the basis of the cutting operation and are directly related to the dimensional accuracy and shape consistency of the aluminum after cutting. The cutting control parameters mainly include cutting speed, cutting position, cutting angle, etc. The cutting speed needs to be determined according to the material, thickness and performance of the cutting equipment of the aluminum to ensure the flatness of the cut surface and the cutting efficiency. The cutting position and cutting angle must strictly follow the product design drawings and process requirements to ensure that the aluminum after cutting meets the size and shape requirements.

[0094] After determining the cutting control parameters, determine the specific position to be cut on the aluminum material according to these parameters. Then, use appropriate marking tools (such as scribers, laser markers, etc.) to clearly and accurately mark the surface of the aluminum material. The marks should be easy to identify and not easy to fade, so that the subsequent cutting operations can be accurately aligned. According to the marked position of the aluminum material, use cutting equipment (such as sawing machines, shearing machines, etc.) to cut the aluminum material. The selection of cutting equipment should be determined according to the material, thickness and cutting requirements of the aluminum material to ensure cutting efficiency and quality. During the cutting process, ensure that the cutting equipment is stable, the cutting blade is sharp, and the cutting is strictly carried out according to the marked position. At the same time, attention should also be paid to the control of the cutting speed to avoid problems such as uneven cutting surface or deformation of the aluminum material caused by too fast or too slow. After the cutting is completed, the cutting surface should be cleaned in time to remove burrs and flash to ensure the cutting quality.

[0095] After the cutting operation is completed, the cut aluminum material needs to be inspected for quality. The inspection content includes the flatness, dimensional accuracy, shape consistency and surface quality of the cut surface. Through quality inspection, problems that occur during the cutting process can be discovered and dealt with in a timely manner to ensure that the quality of the aluminum alloy standard sample meets the requirements.

[0096] Specifically, the aluminum alloy standard sample production method described in the present invention, step S108 includes: Collect data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark 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.

[0097] Data is collected extensively from 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 aluminum alloy standard sample production, ensuring the comprehensiveness and accuracy of the data.

[0098] The collected data include raw material traceability information, cooling device configuration parameters, mold preheating temperature and time, aluminum soup processing parameters, casting temperature and sampling images, cooling process records, cutting position and marking information, etc. These data reflect the key parameters and status of the production process and are crucial for subsequent data analysis and processing.

[0099] The collected data are classified and organized according to data type and source to facilitate subsequent data cleaning and analysis.

[0100] 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 and provide a solid foundation for subsequent data analysis and visualization.

[0101] Use data visualization tools to convert cleaned and verified data into visual form. These tools can present complex data in an intuitive and easy-to-understand way, helping production personnel quickly understand the production process and product quality.

[0102] Visualization forms include charts, tables, and images. For example, a bar chart can be used to show the output changes of different production units, a line chart can be used to show the change trend of mold preheating temperature over time, and an image can be used to show the macroscopic morphology of the sampled samples. These visualization forms not only improve the readability of the data, but also help production personnel to promptly identify problems in the production process and take corresponding measures.

[0103] Through in-depth analysis of visualized data, production personnel can understand the actual status of the production process and discover potential problems and improvement points. For example, if it is found that the output of a production unit is continuously low, the cause can be further analyzed and measures can be taken to increase the output; if it is found that the mold preheating temperature fluctuates greatly, the working parameters of the preheating equipment can be adjusted to ensure the stability of the mold temperature. Data visualization also provides strong support for production decisions. Production personnel can evaluate the effects of different production plans based on visualized data and select the optimal production plan to improve production efficiency and product quality.

[0104] In a second aspect, the present invention provides an aluminum alloy standard sample production system, which is applied to an aluminum alloy standard sample production method as described above, including: The casting preparation unit obtains a data traceability table, which includes the target value of the aluminum alloy standard sample, the formula production data, and the raw materials used for each component when it is sold; collects the parameters in the process of making the aluminum alloy standard sample; stores the data traceability table and the parameters in the process of the aluminum alloy standard sample in the database; substitutes the data traceability table into the preset aluminum alloy standard sample production model to generate the aluminum alloy standard sample production control parameters, which include cooling device control parameters, preheating mold control parameters, aluminum soup processing control parameters, casting control parameters, cooling control parameters, and cutting control parameters; A cooling device unit, the cooling device executes cooling device control parameters, 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 device 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 each preheating value 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 in 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 information, casting temperature and sampling image information during the casting process, performs data preprocessing on the weather, temperature, humidity information, casting temperature and sampling image information during the casting process, obtains preprocessed forging data, substitutes the preprocessed forging data and casting control parameters into a preset casting production model, generates a casting task command, sends the casting task command to the casting equipment, and the casting equipment 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 control parameters of the cooling unit 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.

[0105] Specifically, in the aluminum alloy standard sample production system described in the present invention, the casting preparation unit is also 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 mark unit to obtain historical production data of aluminum alloy standard samples; The historical production data of aluminum alloy standard samples are used for feature extraction, and the extracted features are used as input. The 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 the aluminum alloy standard sample production model.

[0106] Specifically, in the aluminum alloy standard sample production system described in the present invention, the casting unit is also used for: Obtain weather, temperature and humidity information in real time during the casting process, and use cameras or other image acquisition devices to obtain sampled image information; The acquired weather, temperature, humidity information, casting temperature and sampling image information are preprocessed. 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, which predicts the optimal parameters of the casting process according to the input data and uses the optimal parameters as the casting task commands.

[0107] Specifically, in the aluminum alloy standard sample production system described in the present invention, the cutting unit is also used for: 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.

[0108] According to the cutting control parameters, the specific position to be cut is determined on the aluminum material, and at the determined position to be cut, the aluminum material is marked with a suitable marking tool; According to the marked position of the aluminum material, use the cutting equipment to cut the aluminum material.

[0109] Specifically, in the aluminum alloy standard sample production system described in the present invention, the data review unit is also used for: Collect data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark 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.

[0110] The present invention provides a method and system for producing aluminum alloy standard samples, aiming to solve the problem that the existing technology cannot effectively integrate and analyze aluminum alloy standard sample data. The specific solution is as follows: The data traceability table records the target value of the aluminum alloy standard sample, the formula production data and the raw materials used for each component when it is sold, ensuring the traceability of the data. The data traceability table and the parameters collected during the production process are stored in the database to achieve centralized management and long-term preservation of the data.

[0111] Aluminum alloy standard sample production model: The production model is obtained by using historical production data and feature extraction, and training through machine learning algorithms such as random forest. The data traceability table is substituted into the production model to generate production control parameters including cooling device control parameters, preheating mold control parameters, aluminum soup treatment control parameters, casting control parameters, cooling control parameters and cutting control parameters.

[0112] Each production unit (such as cooling device, preheating mold equipment, aluminum soup processing equipment, casting equipment, etc.) automatically performs corresponding operations according to the generated control parameters, reducing human intervention and improving production efficiency and data accuracy. Each production unit is integrated with the data review unit to realize real-time data collection, transmission and processing, ensuring the timeliness and consistency of data.

[0113] During the casting process, weather, temperature, humidity information and sampled image information are obtained in real time, and the data is pre-processed and input into the casting production model to generate the optimal casting parameters and adjust them in real time. During the cooling process, according to the collected aluminum material temperature data, if it is higher than the preset standard, the cooling unit control parameters are optimized to ensure product quality.

[0114] Collect data from each production unit, including raw material traceability information, cooling device configuration parameters, mold preheating temperature and time, aluminum soup processing parameters, casting temperature and sampling images, cooling process records, cutting position and marking information, etc. Classify, clean and verify the collected data to ensure data accuracy. Use data visualization tools to convert the cleaned and verified data into charts, tables, images and other forms to facilitate the review and analysis of production data.

[0115] In summary, the present invention effectively solves the problem that the prior art cannot 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, obtaining a data traceability table, the data traceability table includes target values ​​of aluminum alloy standard samples, formula production data and raw materials used for each component when sold, collecting parameters in the process of producing aluminum alloy standard samples, storing the data traceability table and the parameters in the process of aluminum alloy standard samples in a database, substituting the data traceability table into a preset aluminum alloy standard sample production model, generating aluminum alloy standard sample production control parameters, the aluminum alloy standard sample production control parameters including cooling device control parameters, preheating mold control parameters, aluminum soup processing control parameters, casting control parameters, cooling control parameters and cutting control parameters; Step S102, the cooling device executes the 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 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 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 in the aluminum soup processing process. When the aluminum soup meets the preset aluminum soup processing parameters, the casting unit is triggered; Step S105, obtaining weather, temperature, humidity information, casting temperature and sampling image information during the casting process, performing data preprocessing on the weather, temperature, humidity information, casting temperature and sampling image information during the casting process, obtaining preprocessed forging data, substituting the preprocessed forging data and casting control parameters into a preset casting production model, generating a casting task command, sending the casting task command to the casting equipment, and the casting equipment casting the aluminum material after the aluminum soup treatment; Step S106, cooling the aluminum material after casting according to the cooling control parameters, collecting the 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 the 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, obtaining 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 aluminum alloy standard samples.

2. The method for producing a standard aluminum alloy sample according to claim 1, characterized in that: 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 mark unit to obtain historical production data of aluminum alloy standard samples; The historical production data of aluminum alloy standard samples are used for feature extraction, and the extracted features are used as input. The 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 the aluminum alloy standard sample production model.

3. The method for producing a standard aluminum alloy sample according to claim 1, characterized in that: The step S105 includes: Obtain weather, temperature and humidity information in real time during the casting process, and use cameras or other image acquisition devices to obtain sampled image information; The acquired weather, temperature, humidity information, casting temperature and sampling image information are preprocessed. 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, which predicts the optimal parameters of the casting process according to the input data and uses the optimal parameters as the casting task commands.

4. The method for producing a standard aluminum alloy sample according to claim 1, characterized in that: The step S107 includes: According to the requirements and specifications of aluminum alloy standard sample production, the cutting control parameters are determined, including cutting speed, cutting position and cutting angle; According to the cutting control parameters, the specific position to be cut is determined on the aluminum material, and at the determined position to be cut, the aluminum material is marked with a suitable marking tool; According to the marked position of the aluminum material, use the cutting equipment to cut the aluminum material.

5. The method for producing a standard aluminum alloy sample according to claim 1, characterized in that: The step S108 includes: Collect data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark 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. A system for producing aluminum alloy standard samples, applied to the method for producing aluminum alloy standard samples as claimed in 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 formula production data, and the raw materials used for each component when it is sold; collects the parameters in the process of making the aluminum alloy standard sample; stores the data traceability table and the parameters in the process of the aluminum alloy standard sample in the database; substitutes the data traceability table into the preset aluminum alloy standard sample production model to generate the aluminum alloy standard sample production control parameters, which include cooling device control parameters, preheating mold control parameters, aluminum soup processing control parameters, casting control parameters, cooling control parameters, and cutting control parameters; A cooling device unit, the cooling device executes cooling device control parameters, 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 device 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 each preheating value 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 in 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 information, casting temperature and sampling image information during the casting process, performs data preprocessing on the weather, temperature, humidity information, casting temperature and sampling image information during the casting process, obtains preprocessed forging data, substitutes the preprocessed forging data and casting control parameters into a preset casting production model, generates a casting task command, sends the casting task command to the casting equipment, and the manufacturing equipment 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 control parameters of the cooling unit 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 mark unit to obtain historical production data of aluminum alloy standard samples; The historical production data of aluminum alloy standard samples are used for feature extraction, and the extracted features are used as input. The 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 the 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 also used for: Obtain weather, temperature and humidity information in real time during the casting process, and use cameras or other image acquisition devices to obtain sampled image information; The acquired weather, temperature, humidity information, casting temperature and sampling image information are preprocessed. 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, which predicts the optimal parameters of the casting process according to the input data and uses the optimal parameters as the casting task commands.

9. The aluminum alloy standard sample production system according to claim 6, characterized in that: The cutting unit is further used for: According to the requirements and specifications of aluminum alloy standard sample production, the cutting control parameters are determined, including cutting speed, cutting position and cutting angle; According to the cutting control parameters, the specific position to be cut is determined on the aluminum material, and at the determined position to be cut, the aluminum material is marked with a suitable marking tool; 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 used for: Collect data from the casting preparation unit, cooling device unit, preheating mold unit, aluminum soup processing unit, casting unit, cooling unit and cutting mark 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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