Forming management control system and method for semi-solid magnesium alloy

Abstract

The invention discloses a semi-solid magnesium alloy forming management control system and method, and relates to the technical field of intelligent management, and the method comprises the following steps: sending a first regulation and control signal, calculating the similarity between an actual finished product picture and a first picture, judging the defect of an actual finished product, screening a second control parameter, and setting a first change amount; sending a second regulation and control signal to obtain a third control parameter, calculating the temperature change rate of the subspace, screening the fault subspace, sending a maintenance signal, and establishing a first association relationship. The quality of the finished product is improved by matching the first control parameters corresponding to the finished product model and the mold model, the generation of the defects is effectively detected and prevented by acquiring the actual finished product picture and the historical defect information, setting the similarity threshold and judging the actual finished product defects, intelligent control is realized through the association relationship, and the production efficiency is improved. The production efficiency and the product quality are improved, and defects are reduced, so that the waste of materials is reduced, and the production cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent management, and in particular to a forming management control system and method for a semi-solid magnesium alloy. Background Art

[0002] In recent years, semi-solid magnesium alloy forming technology has received widespread attention due to its advantages such as high efficiency, energy saving, near-net shape production and high performance of formed parts. This technology has important application value and broad application prospects in industrial fields such as automobiles, electronics, 3C products, aerospace, and national defense and military. Semi-solid magnesium alloy forming technology combines the advantages of solidification processing and plastic processing. The processing temperature is lower than that of liquid and the deformation resistance is smaller than that of solid. It can be processed into parts with complex shapes and high precision and performance requirements with a large deformation amount at one time.

[0003] At present, in the Chinese invention patent with announcement number CN 107350453 B, a dual-circuit mold temperature control method for aluminum-magnesium alloy die-casting is disclosed. By dividing the temperature control zone in the die-casting mold, not only can the die-casting mold be heated quickly and evenly to achieve dynamic thermal balance, but also the temperature difference of each temperature control zone can be adjusted to reduce the deformation of the alloy casting, and the pressure in the die-casting mold, the temperature and flow of the heat transfer oil and the flow of the cooling water can be adjusted to more flexibly control the temperature in the mold, so that the magnesium-aluminum alloy in the die-casting mold can be evenly cooled, crystallized and solidified. However, the relevant technology does not analyze the relevant parameters of the multi-step process, lacks the comprehensiveness of the molding control, does not compensate and control the relevant parameters affecting the molding quality, lacks the accuracy of the molding control, and has no correlation between the control parameters and the finished product, which is not conducive to the rapid responsiveness of the system. Summary of the invention

[0004] The technical problem solved by the present invention is: the related technology does not analyze the relevant parameters of the multi-step process, lacks the comprehensiveness of the molding control, does not compensate and control the relevant parameters affecting the molding quality, lacks the accuracy of the molding control, and has no correlation between the control parameters and the finished product, which is not conducive to the rapid responsiveness of the system.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: In the first aspect, a forming management and control method of a semi-solid magnesium alloy comprises the following steps: Step 100, obtaining a finished product model and a mold model, matching corresponding first control parameters according to the finished product model and the mold model, and sending a first control signal according to the first control parameter; Step 200, obtaining an actual finished product image and historical defect information, wherein the historical defect information includes a historical finished product model, a corresponding historical finished product image, a corresponding historical defect name, and a corresponding historical defect cause, matching the corresponding historical finished product image, the corresponding historical defect name, and the corresponding historical defect cause according to the finished product model, respectively, and recording them as a first image, a first defect, and a first cause, respectively, wherein the first cause corresponds to the first defect, calculating the similarity between the actual finished product image and the first image, setting a similarity threshold, judging the actual finished product defect according to the similarity threshold, setting the defect name of the corresponding first image as the actual finished product defect name, and obtaining the corresponding actual defect cause; Step S300, screening the second control parameter according to the defect cause corresponding to the actual finished product defect name, setting the first change amount, sending the second control signal according to the first change amount, continuously controlling the second control parameter, obtaining the controlled second control parameter, storing and updating the first control parameter according to the controlled second control parameter, and obtaining the third control parameter; Step S400, simulate the casting process according to the third control parameter, set the acquisition cycle, continuously monitor the spatial temperature image in the molding cavity during the acquisition cycle, divide the spatial temperature image into subspaces, and continuously calculate the temperature change rate of the subspaces, screen the faulty subspaces according to the temperature change rate, send a maintenance signal, and after the maintenance is completed, establish a first association relationship between the mold, the finished product model and the third control parameter.

[0006] As a preferred solution of the forming management and control method of a semi-solid magnesium alloy according to the present invention, the step 100 includes the following sub-steps: Step S101, obtaining a finished product model and a mold model, calling a casting database, inputting the finished product model and the mold model into the casting database, and matching the finished product model and the mold model with corresponding first control parameters; The first control parameters include injection speed, mold temperature, barrel temperature, injection pressure and mold insulation time; Step S102: Send a first control signal according to the first control parameter.

[0007] As a preferred solution of the forming management and control method of a semi-solid magnesium alloy according to the present invention, the step 200 includes the following sub-steps: Step S301, obtaining actual finished product pictures and historical defect information, wherein the historical defect information includes historical finished product models, corresponding historical finished product pictures, corresponding historical defect names, and corresponding historical defect causes; Step S202, comparing the actual finished product model with the historical finished product model to obtain a comparison result, wherein the comparison result includes that the actual finished product model is the same as the historical finished product model, and the actual finished product model is different from the historical finished product model; Step S203, performing a first operation to filter the corresponding historical finished product pictures, the corresponding historical defect names and the corresponding historical defect causes according to the comparison results, which are recorded as the first picture, the first defect and the first cause respectively, wherein the first defects include pores, shrinkage, cold shut, shrinkage and cracks, and the first causes correspond to the first defects respectively, including barrel temperature too high, barrel temperature too low, mold temperature too low, injection pressure too high and mold insulation time short; When the comparison result is that the actual finished product model is the same as the historical finished product model, the historical finished product picture corresponding to the historical finished product model, the corresponding historical defect name and the corresponding historical defect cause are obtained; when the comparison result is that the actual finished product model is different from the historical finished product model, the actual finished product picture is set as defect-free; Step S204, calculate the similarity between the actual finished product image and the first image, set a similarity threshold, determine the actual finished product defect according to the similarity threshold, set the defect name of the corresponding first image as the actual finished product defect name, and obtain the corresponding defect cause.

[0008] As a preferred solution of the forming management and control method of a semi-solid magnesium alloy according to the present invention, the step S204 further includes the following sub-steps: Step S2041, filtering and graying the actual finished product image, extracting a first feature quantity of the actual finished product image after filtering and graying, wherein the first feature quantity is represented as a shape feature quantity, obtaining any first image, extracting a second feature quantity of the first image, wherein the second feature quantity represents a shape feature quantity; Step S2042, calculating the similarity between the first feature quantity and the second feature quantity by using a cosine similarity formula; Step S2043, setting the first value as the similarity threshold, traversing the similarities, sorting the similarities in descending order, selecting the similarity with the largest value, comparing the similarity with the largest value with the first value, obtaining a comparison result, and performing a first operation according to the comparison result, wherein the first operation includes outputting a first control parameter accurate signal and determining an actual finished product defect; Step S2045, when the first operation is to determine the actual finished product defect, the defect name of the corresponding first image is set as the actual finished product defect name, and the defect cause corresponding to the first image is obtained and set as the actual finished product defect cause.

[0009] As a preferred solution of the forming management and control method of a semi-solid magnesium alloy according to the present invention, step S300 includes the following sub-steps: Step S301, screening the second control parameter according to the actual finished product defect name and the corresponding actual defect cause, the screening logic includes: Obtaining the actual defect cause, wherein the actual defect cause includes an actual barrel temperature that is too high, an actual barrel temperature that is too low, an actual mold temperature that is too low, an actual injection pressure that is too high, and an actual mold insulation time that is short. When the actual defect cause is that the barrel temperature is too high or the barrel temperature is too low, the second control parameter is set to the barrel temperature; when the actual defect cause is that the actual mold temperature is too low, the second control parameter is set to the mold temperature; when the actual defect cause is that the actual injection pressure is too high, the second control parameter is set to the injection pressure; when the actual defect cause is that the actual mold insulation time is short, the second control parameter is set to the mold insulation time; Step S302, setting the second value, the third value and the fourth value as the first change amount, issuing a second control signal according to the first change amount, continuously controlling the second control parameter, and obtaining the controlled second control parameter, wherein the continuous control is represented by continuous increase control or continuous decrease control, and the second value, the third value and the fourth value are obtained through big data analysis; When the actual defect cause is that the actual barrel temperature is too high, the first control parameter is continuously reduced according to the second value; when the actual defect cause is that the actual barrel temperature is too low, the first control parameter is continuously increased according to the second value; when the actual defect cause is that the actual mold temperature is too low, the first control parameter is continuously increased according to the second value; when the actual defect cause is that the actual injection pressure is too high, the first control parameter is continuously reduced according to the third value; when the actual defect cause is the actual mold insulation time period, the first control parameter is continuously increased according to the fourth value; Step S302, storing and updating the first control parameter according to the controlled second control parameter to obtain a third control parameter.

[0010] As a preferred solution of the forming management and control method of a semi-solid magnesium alloy described in the present invention, the updating logic of the first control parameter includes a continuous increase logic and a continuous decrease logic, and the continuous increase logic includes: Obtaining a first control parameter corresponding to the third control parameter, recorded as a first target parameter, counting the number of times the first change amount is continuously increased, recorded as a first number, calculating the product of the first number and the first change amount, recorded as a first product, calculating the sum of the first product and the first target parameter, recording the sum of the first product and the first target parameter as a third control parameter, and replacing the corresponding first control parameter; The logic of the continuous reduction includes: Obtain the first control parameter corresponding to the third control parameter, record it as the second target parameter, count the number of adjustments and controls of the first change amount that decreases continuously, record it as the second number, calculate the product of the first change amount and the second number, record it as the second product, calculate the difference between the target parameter and the second product, record the difference between the target parameter and the second product as the third control parameter, and replace the corresponding first control parameter.

[0011] As a preferred solution of the forming management and control method of a semi-solid magnesium alloy according to the present invention, the step S400 includes the following sub-steps: Step S401, simulating the casting process according to the third control parameter, and setting the first time period as the acquisition period; Step S402, continuously monitoring the temperature in the molding cavity during a first time period by using an infrared temperature sensor, and automatically converting the temperature into a spatial temperature map or a spatial temperature image; Step S403, segmenting the spatial temperature image into subspaces using the cavity segmentation algorithm of the STL model, and numbering the subspaces, wherein the numbers are natural numbers: Step S404, obtaining the temperature values ​​of adjacent sub-units, wherein the adjacent values ​​are the temperature values ​​corresponding to the same sub-units collected in time sequence, and continuously calculating the temperature change rate of the sub-space. The calculation logic of the temperature change rate includes: Obtaining temperature values ​​of adjacent subunits, respectively recorded as a first temperature value and a second temperature value, calculating a difference between the temperature values ​​of adjacent subunits, recorded as a second difference, calculating a ratio of the second difference to the first temperature value, recorded as a first ratio, traversing the first ratio, calculating an average value of the first ratio, and setting the average value of the first ratio as the temperature change rate of the subspace; Step S405, screening the fault subspace according to the temperature change rate and sending a maintenance signal, wherein the screening logic of the fault subspace includes: Setting the fifth value as the temperature change rate threshold, comparing the temperature change rate with the fifth ratio, and when the temperature change rate is greater than or equal to the fifth ratio, setting the subspace as the fault subspace; and when the temperature change rate is less than the fifth ratio, deleting the subspace; Step S406, after the maintenance is completed, a first association relationship between the mold model, the finished product model and the third control parameter is established, the current mold model and the current finished product model are obtained, and the corresponding third control parameter is obtained according to the first association relationship.

[0012] In a second aspect, a forming management and control system for a semi-solid magnesium alloy includes a collection module, an analysis module and a construction module; The acquisition module is used to obtain the finished product model and the mold model, match the corresponding first control parameter according to the finished product model and the mold model, and send the first control signal according to the first control parameter; The analysis module is used to obtain actual finished product pictures and historical defect information, wherein the historical defect information includes historical finished product models, corresponding historical finished product pictures, corresponding historical defect names, and corresponding historical defect causes, and the corresponding historical finished product pictures, corresponding historical defect names, and corresponding historical defect causes are matched according to the finished product models, respectively, and are recorded as the first picture, the first defect, and the first cause, respectively. The first cause corresponds to the first defect, and the similarity between the actual finished product picture and the first picture is calculated, and a similarity threshold is set. The actual finished product defect is judged according to the similarity threshold, and the defect name of the corresponding first picture is set as the actual finished product defect name, and the corresponding actual defect cause is obtained. The second control parameter is screened according to the defect cause corresponding to the actual finished product defect name, and a first change amount is set. A second control signal is issued according to the first change amount, and the second control parameter is continuously controlled to obtain the second control parameter after control, and the first control parameter is stored and updated according to the second control parameter after control to obtain the third control parameter; The construction module simulates the casting process according to the third control parameter, sets an acquisition cycle, continuously monitors the spatial temperature image in the molding cavity during the acquisition cycle, divides the spatial temperature image into subspaces, and continuously calculates the temperature change rate of the subspaces, selects faulty subspaces according to the temperature change rate, sends a maintenance signal, and after the maintenance is completed, establishes a first association relationship between the mold, the finished product model and the third control parameter.

[0013] In a third aspect, the present invention provides an electronic device comprising a memory, a processor and storage in the memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in any one of the methods described above are executed.

[0014] In a fourth aspect, the present invention provides a storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps in any one of the methods described above are executed.

[0015] The beneficial effects of the present invention are as follows: by matching the first control parameter corresponding to the finished product model and the mold model, and sending a control signal, the accuracy and consistency of the molding process are ensured, thereby improving the quality of the finished product; by obtaining the actual finished product picture and historical defect information, calculating the similarity between the actual finished product picture and the historical picture, and setting a similarity threshold to judge the actual finished product defects, the occurrence of defects is effectively detected and prevented; by establishing an association between the mold, the finished product model and the third control parameter, intelligent control is achieved, production efficiency and product quality are improved, the occurrence of defects is reduced, thereby reducing material waste and reducing production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of the basic flow of a forming management and control method of a semi-solid magnesium alloy provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0018] Example, see Figure 1 , as an embodiment of the present invention, provides a forming management and control method for a semi-solid magnesium alloy, comprising the following steps: Step 100, obtaining a finished product model and a mold model, matching corresponding first control parameters according to the finished product model and the mold model, and sending a first control signal according to the first control parameter; Step 200, obtaining an actual finished product image and historical defect information, wherein the historical defect information includes a historical finished product model, a corresponding historical finished product image, a corresponding historical defect name, and a corresponding historical defect cause, matching the corresponding historical finished product image, the corresponding historical defect name, and the corresponding historical defect cause according to the finished product model, respectively, and recording them as a first image, a first defect, and a first cause, respectively, wherein the first cause corresponds to the first defect, calculating the similarity between the actual finished product image and the first image, setting a similarity threshold, judging the actual finished product defect according to the similarity threshold, setting the defect name of the corresponding first image as the actual finished product defect name, and obtaining the corresponding actual defect cause; Step S300, screening the second control parameter according to the defect cause corresponding to the actual finished product defect name, setting the first change amount, sending the second control signal according to the first change amount, continuously controlling the second control parameter, obtaining the controlled second control parameter, storing and updating the first control parameter according to the controlled second control parameter, and obtaining the third control parameter; Step S400, simulate the casting process according to the third control parameter, set the acquisition cycle, continuously monitor the spatial temperature image in the molding cavity during the acquisition cycle, divide the spatial temperature image into subspaces, and continuously calculate the temperature change rate of the subspaces, screen the faulty subspaces according to the temperature change rate, send a maintenance signal, and after the maintenance is completed, establish a first association relationship between the mold, the finished product model and the third control parameter.

[0019] The present invention matches the first control parameter corresponding to the finished product model and the mold model and sends a control signal to ensure the accuracy and consistency of the molding process, thereby improving the quality of the finished product. The present invention obtains actual finished product pictures and historical defect information, calculates the similarity between the actual finished product pictures and the historical pictures, and sets a similarity threshold to judge the actual finished product defects, effectively detects and prevents the occurrence of defects. By establishing an association between the mold, the finished product model and the third control parameter, intelligent control is achieved, production efficiency and product quality are improved, and defects are reduced, thereby reducing material waste and reducing production costs.

[0020] The step 100 includes the following sub-steps: Step S101, obtaining a finished product model and a mold model, calling a casting database, inputting the finished product model and the mold model into the casting database, and matching the finished product model and the mold model with corresponding first control parameters; The first control parameters include injection speed, mold temperature, barrel temperature, injection pressure and mold insulation time; Step S102: Send a first control signal according to the first control parameter.

[0021] In specific implementation, by retrieving the casting database and inputting the finished product model and mold model, the corresponding first control parameters are accurately matched to ensure that each link of the molding process has the most suitable parameter settings. Accurate control parameter settings help improve molding quality and reduce defects such as pores, shrinkage, cold shut, etc., thereby improving the yield and overall performance of the product. Through automated parameter matching and control signal sending, human errors can be reduced and the efficiency and reliability of the production process can be improved.

[0022] The step 200 includes the following sub-steps: Step S301, obtaining actual finished product pictures and historical defect information, wherein the historical defect information includes historical finished product models, corresponding historical finished product pictures, corresponding historical defect names, and corresponding historical defect causes; Step S202, comparing the actual finished product model with the historical finished product model to obtain a comparison result, wherein the comparison result includes that the actual finished product model is the same as the historical finished product model, and the actual finished product model is different from the historical finished product model; Step S203, performing a first operation to filter the corresponding historical finished product pictures, the corresponding historical defect names and the corresponding historical defect causes according to the comparison results, which are recorded as the first picture, the first defect and the first cause respectively, wherein the first defects include pores, shrinkage, cold shut, shrinkage and cracks, and the first causes correspond to the first defects respectively, including barrel temperature too high, barrel temperature too low, mold temperature too low, injection pressure too high and mold insulation time short; When the comparison result is that the actual finished product model is the same as the historical finished product model, the historical finished product picture corresponding to the historical finished product model, the corresponding historical defect name and the corresponding historical defect cause are obtained; when the comparison result is that the actual finished product model is different from the historical finished product model, the actual finished product picture is set as defect-free; Step S204, calculate the similarity between the actual finished product image and the first image, set a similarity threshold, determine the actual finished product defect according to the similarity threshold, set the defect name of the corresponding first image as the actual finished product defect name, and obtain the corresponding defect cause.

[0023] In specific implementation, by comparing actual finished products with historical data, possible defects in finished products can be more accurately identified and predicted. Through the analysis of historical defect information, it is convenient to take measures in advance in the production process to prevent potential defects from occurring. Production parameters can be adjusted according to the causes of historical defects, the production process can be optimized, the scrap rate can be reduced, and automated defect detection and cause analysis can shorten the production cycle and improve production efficiency.

[0024] The step S204 further includes the following sub-steps: Step S2041, filtering and graying the actual finished product image, extracting a first feature quantity of the actual finished product image after filtering and graying, wherein the first feature quantity is represented as a shape feature quantity, obtaining any first image, extracting a second feature quantity of the first image, wherein the second feature quantity represents a shape feature quantity; Step S2042, calculating the similarity between the first feature quantity and the second feature quantity by using a cosine similarity formula; Step S2043, setting the first value as the similarity threshold, traversing the similarities, sorting the similarities in descending order, selecting the similarity with the largest value, comparing the similarity with the largest value with the first value, obtaining a comparison result, and performing a first operation according to the comparison result, wherein the first operation includes outputting a first control parameter accurate signal and determining an actual finished product defect; Step S2045, when the first operation is to determine the actual finished product defect, the defect name of the corresponding first image is set as the actual finished product defect name, and the defect cause corresponding to the first image is obtained and set as the actual finished product defect cause.

[0025] In the specific implementation, through filtering and grayscale processing, image noise is reduced and the accuracy of image feature extraction is improved, thereby improving the reliability of defect detection. By setting a similarity threshold and sorting in descending order, it is intelligently determined whether the actual finished product has defects, reducing the interference of human factors and improving the objectivity of defect judgment.

[0026] The step S300 includes the following sub-steps: Step S301, screening the second control parameter according to the actual finished product defect name and the corresponding actual defect cause, the screening logic includes: Obtaining the actual defect cause, wherein the actual defect cause includes an actual barrel temperature that is too high, an actual barrel temperature that is too low, an actual mold temperature that is too low, an actual injection pressure that is too high, and an actual mold insulation time that is short. When the actual defect cause is that the barrel temperature is too high or the barrel temperature is too low, the second control parameter is set to the barrel temperature; when the actual defect cause is that the actual mold temperature is too low, the second control parameter is set to the mold temperature; when the actual defect cause is that the actual injection pressure is too high, the second control parameter is set to the injection pressure; when the actual defect cause is that the actual mold insulation time is short, the second control parameter is set to the mold insulation time; Step S302, setting the second value, the third value and the fourth value as the first change amount, issuing a second control signal according to the first change amount, continuously controlling the second control parameter, and obtaining the controlled second control parameter, wherein the continuous control is represented by continuous increase control or continuous decrease control, and the second value, the third value and the fourth value are obtained through big data analysis; When the actual defect cause is that the actual barrel temperature is too high, the first control parameter is continuously reduced according to the second value; when the actual defect cause is that the actual barrel temperature is too low, the first control parameter is continuously increased according to the second value; when the actual defect cause is that the actual mold temperature is too low, the first control parameter is continuously increased according to the second value; when the actual defect cause is that the actual injection pressure is too high, the first control parameter is continuously reduced according to the third value; when the actual defect cause is the actual mold insulation time period, the first control parameter is continuously increased according to the fourth value; Step S302, storing and updating the first control parameter according to the controlled second control parameter to obtain a third control parameter.

[0027] In the specific implementation, the second control parameter is screened according to the defect name and cause of the actual finished product, the process parameters that need to be adjusted are accurately identified, the molding quality is improved, and the change amount obtained by big data analysis is used to continuously adjust the control parameters, thereby realizing the intelligent process adjustment, reducing human intervention, and improving the accuracy and efficiency of the adjustment. Continuous control is expressed as continuous increase or continuous decrease control. This dynamic adjustment method quickly responds to changes in the molding process, corrects parameters in time, reduces the occurrence of defects, and reduces the risk of production interruption through real-time monitoring and adjustment.

[0028] The updating logic of the first control parameter includes a continuous increase logic and a continuous decrease logic, and the continuous increase logic includes: Obtaining a first control parameter corresponding to the third control parameter, recorded as a first target parameter, counting the number of times the first change amount is continuously increased, recorded as a first number, calculating the product of the first number and the first change amount, recorded as a first product, calculating the sum of the first product and the first target parameter, recording the sum of the first product and the first target parameter as a third control parameter, and replacing the corresponding first control parameter; The logic of the continuous reduction includes: Obtain the first control parameter corresponding to the third control parameter, record it as the second target parameter, count the number of adjustments and controls of the first change amount that decreases continuously, record it as the second number, calculate the product of the first change amount and the second number, record it as the second product, calculate the difference between the target parameter and the second product, record the difference between the target parameter and the second product as the third control parameter, and replace the corresponding first control parameter.

[0029] In specific implementation, it is possible to make adaptive adjustments based on feedback from actual production, thereby improving the flexibility and adaptability of the production system. Accurate parameter adjustments can reduce material waste caused by improper parameters and improve material utilization.

[0030] The step S400 includes the following sub-steps: Step S401, simulating the casting process according to the third control parameter, and setting the first time period as the acquisition period; Step S402, continuously monitoring the temperature in the molding cavity during a first time period by using an infrared temperature sensor, and automatically converting the temperature into a spatial temperature map or a spatial temperature image; Step S403, segmenting the spatial temperature image into subspaces using the cavity segmentation algorithm of the STL model, and numbering the subspaces, wherein the numbers are natural numbers: Step S404, obtaining the temperature values ​​of adjacent sub-units, wherein the adjacent values ​​are the temperature values ​​corresponding to the same sub-units collected in time sequence, and continuously calculating the temperature change rate of the sub-space. The calculation logic of the temperature change rate includes: Obtaining temperature values ​​of adjacent subunits, respectively recorded as a first temperature value and a second temperature value, calculating a difference between the temperature values ​​of adjacent subunits, recorded as a second difference, calculating a ratio of the second difference to the first temperature value, recorded as a first ratio, traversing the first ratio, calculating an average value of the first ratio, and setting the average value of the first ratio as the temperature change rate of the subspace; Step S405, screening the fault subspace according to the temperature change rate and sending a maintenance signal, wherein the screening logic of the fault subspace includes: Setting the fifth value as the temperature change rate threshold, comparing the temperature change rate with the fifth ratio, and when the temperature change rate is greater than or equal to the fifth ratio, setting the subspace as the fault subspace; and when the temperature change rate is less than the fifth ratio, deleting the subspace; Step S406, after the maintenance is completed, a first association relationship between the mold model, the finished product model and the third control parameter is established, the current mold model and the current finished product model are obtained, and the corresponding third control parameter is obtained according to the first association relationship.

[0031] In the specific implementation, the casting process is simulated through the third control parameter to more accurately predict the problems that may occur in actual production and improve the accuracy of the simulation. The infrared temperature sensor is used to continuously monitor the temperature in the molding cavity during the acquisition period, and the temperature changes in the molding process are grasped in real time. Maintenance is carried out in time, and the monitored temperature data is automatically converted into a spatial temperature image to intuitively display the temperature distribution in the molding cavity, which is convenient for analysis and adjustment. The spatial temperature image is divided into subspaces through the cavity segmentation algorithm of the STL model, and each area in the molding cavity is more finely managed and controlled.

[0032] The present invention matches the first control parameter corresponding to the finished product model and the mold model and sends a control signal to ensure the accuracy and consistency of the molding process, thereby improving the quality of the finished product. The present invention obtains actual finished product pictures and historical defect information, calculates the similarity between the actual finished product pictures and the historical pictures, and sets a similarity threshold to judge the actual finished product defects, effectively detects and prevents the occurrence of defects. By establishing an association between the mold, the finished product model and the third control parameter, intelligent control is achieved, production efficiency and product quality are improved, and defects are reduced, thereby reducing material waste and reducing production costs.

[0033] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Among them, the storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk. These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 Functions specified in one or more boxes It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A forming management and control method for a semi-solid magnesium alloy, characterized in that: The following steps are involved: Step 100, obtaining a finished product model and a mold model, matching corresponding first control parameters according to the finished product model and the mold model, and sending a first control signal according to the first control parameter; Step 200, obtaining an actual finished product image and historical defect information, wherein the historical defect information includes a historical finished product model, a corresponding historical finished product image, a corresponding historical defect name, and a corresponding historical defect cause, matching the corresponding historical finished product image, the corresponding historical defect name, and the corresponding historical defect cause according to the finished product model, respectively, and recording them as a first image, a first defect, and a first cause, respectively, wherein the first cause corresponds to the first defect, calculating the similarity between the actual finished product image and the first image, setting a similarity threshold, judging the actual finished product defect according to the similarity threshold, setting the defect name of the corresponding first image as the actual finished product defect name, and obtaining the corresponding actual defect cause; Step S300, screening the second control parameter according to the defect cause corresponding to the actual finished product defect name, setting the first change amount, sending the second control signal according to the first change amount, continuously controlling the second control parameter, obtaining the controlled second control parameter, storing and updating the first control parameter according to the controlled second control parameter, and obtaining the third control parameter; Step S400, simulate the casting process according to the third control parameter, set the acquisition cycle, continuously monitor the spatial temperature image in the molding cavity during the acquisition cycle, divide the spatial temperature image into subspaces, and continuously calculate the temperature change rate of the subspaces, screen the faulty subspaces according to the temperature change rate, send a maintenance signal, and after the maintenance is completed, establish a first association relationship between the mold, the finished product model and the third control parameter.

2. A forming management and control method for a semi-solid magnesium alloy as claimed in claim 1, characterized in that: The step 100 includes the following sub-steps: Step S101, obtaining a finished product model and a mold model, calling a casting database, inputting the finished product model and the mold model into the casting database, and matching the finished product model and the mold model with corresponding first control parameters; The first control parameters include injection speed, mold temperature, barrel temperature, injection pressure and mold insulation time; Step S102: Send a first control signal according to the first control parameter.

3. The forming management and control method of a semi-solid magnesium alloy according to claim 1, characterized in that: The step 200 includes the following sub-steps: Step S301, obtaining actual finished product pictures and historical defect information, wherein the historical defect information includes historical finished product models, corresponding historical finished product pictures, corresponding historical defect names, and corresponding historical defect causes; Step S202, comparing the actual finished product model with the historical finished product model to obtain a comparison result, wherein the comparison result includes that the actual finished product model is the same as the historical finished product model, and the actual finished product model is different from the historical finished product model; Step S203, performing a first operation to filter the corresponding historical finished product pictures, the corresponding historical defect names and the corresponding historical defect causes according to the comparison results, which are recorded as the first picture, the first defect and the first cause respectively, wherein the first defects include pores, shrinkage, cold shut, shrinkage and cracks, and the first causes correspond to the first defects respectively, including barrel temperature too high, barrel temperature too low, mold temperature too low, injection pressure too high and mold insulation time short; When the comparison result is that the actual finished product model is the same as the historical finished product model, the historical finished product picture corresponding to the historical finished product model, the corresponding historical defect name and the corresponding historical defect cause are obtained; when the comparison result is that the actual finished product model is different from the historical finished product model, the actual finished product picture is set as defect-free; Step S204, calculate the similarity between the actual finished product image and the first image, set a similarity threshold, determine the actual finished product defect according to the similarity threshold, set the defect name of the corresponding first image as the actual finished product defect name, and obtain the corresponding defect cause.

4. A forming management and control method for a semi-solid magnesium alloy as claimed in claim 3, characterized in that: The step S204 further includes the following sub-steps: Step S2041, filtering and graying the actual finished product image, extracting a first feature quantity of the actual finished product image after filtering and graying, wherein the first feature quantity is represented as a shape feature quantity, obtaining any first image, extracting a second feature quantity of the first image, wherein the second feature quantity represents a shape feature quantity; Step S2042, calculating the similarity between the first feature quantity and the second feature quantity by using a cosine similarity formula; Step S2043, setting the first value as the similarity threshold, traversing the similarities, sorting the similarities in descending order, selecting the similarity with the largest value, comparing the similarity with the largest value with the first value, obtaining a comparison result, and performing a first operation according to the comparison result, wherein the first operation includes outputting a first control parameter accurate signal and determining an actual finished product defect; Step S2045, when the first operation is to determine the actual finished product defect, the defect name of the corresponding first image is set as the actual finished product defect name, and the defect cause corresponding to the first image is obtained and set as the actual finished product defect cause.

5. The forming management and control method of a semi-solid magnesium alloy according to claim 1, characterized in that: The step S300 includes the following sub-steps: Step S301, screening the second control parameter according to the actual finished product defect name and the corresponding actual defect cause, the screening logic includes: Obtaining the actual defect cause, wherein the actual defect cause includes an actual barrel temperature that is too high, an actual barrel temperature that is too low, an actual mold temperature that is too low, an actual injection pressure that is too high, and an actual mold insulation time that is short. When the actual defect cause is that the barrel temperature is too high or the barrel temperature is too low, the second control parameter is set to the barrel temperature; when the actual defect cause is that the actual mold temperature is too low, the second control parameter is set to the mold temperature; when the actual defect cause is that the actual injection pressure is too high, the second control parameter is set to the injection pressure; when the actual defect cause is that the actual mold insulation time is short, the second control parameter is set to the mold insulation time; Step S302, setting the second value, the third value and the fourth value as the first change amount, issuing a second control signal according to the first change amount, continuously controlling the second control parameter, and obtaining the controlled second control parameter, wherein the continuous control is represented by continuous increase control or continuous decrease control, and the second value, the third value and the fourth value are obtained through big data analysis; When the actual defect cause is that the actual barrel temperature is too high, the first control parameter is continuously reduced according to the second value; when the actual defect cause is that the actual barrel temperature is too low, the first control parameter is continuously increased according to the second value; when the actual defect cause is that the actual mold temperature is too low, the first control parameter is continuously increased according to the second value; when the actual defect cause is that the actual injection pressure is too high, the first control parameter is continuously reduced according to the third value; when the actual defect cause is the actual mold insulation time period, the first control parameter is continuously increased according to the fourth value; Step S302, storing and updating the first control parameter according to the controlled second control parameter to obtain a third control parameter.

6. A forming management and control method for a semi-solid magnesium alloy as claimed in claim 1, characterized in that: The updating logic of the first control parameter includes a continuous increase logic and a continuous decrease logic, and the continuous increase logic includes: Obtaining a first control parameter corresponding to the third control parameter, recorded as a first target parameter, counting the number of times the first change amount is continuously increased, recorded as a first number, calculating the product of the first number and the first change amount, recorded as a first product, calculating the sum of the first product and the first target parameter, recording the sum of the first product and the first target parameter as a third control parameter, and replacing the corresponding first control parameter; The logic of the continuous reduction includes: Obtain the first control parameter corresponding to the third control parameter, record it as the second target parameter, count the number of adjustments and controls of the first change amount that decreases continuously, record it as the second number, calculate the product of the first change amount and the second number, record it as the second product, calculate the difference between the target parameter and the second product, record the difference between the target parameter and the second product as the third control parameter, and replace the corresponding first control parameter.

7. A forming management and control method for a semi-solid magnesium alloy as claimed in claim 1, characterized in that: The step S400 includes the following sub-steps: Step S401, simulating the casting process according to the third control parameter, and setting the first time period as the acquisition period; Step S402, continuously monitoring the temperature in the molding cavity during a first time period by using an infrared temperature sensor, and automatically converting the temperature into a spatial temperature map or a spatial temperature image; Step S403, segmenting the spatial temperature image into subspaces using the cavity segmentation algorithm of the STL model, and numbering the subspaces, wherein the numbers are natural numbers: Step S404, obtaining the temperature values ​​of adjacent sub-units, wherein the adjacent values ​​are the temperature values ​​corresponding to the same sub-units collected in time sequence, and continuously calculating the temperature change rate of the sub-space. The calculation logic of the temperature change rate includes: Obtaining temperature values ​​of adjacent subunits, respectively recorded as a first temperature value and a second temperature value, calculating a difference between the temperature values ​​of adjacent subunits, recorded as a second difference, calculating a ratio of the second difference to the first temperature value, recorded as a first ratio, traversing the first ratio, calculating an average value of the first ratio, and setting the average value of the first ratio as the temperature change rate of the subspace; Step S405, screening the fault subspace according to the temperature change rate and sending a maintenance signal, wherein the screening logic of the fault subspace includes: Setting the fifth value as the temperature change rate threshold, comparing the temperature change rate with the fifth ratio, and when the temperature change rate is greater than or equal to the fifth ratio, setting the subspace as the fault subspace; and when the temperature change rate is less than the fifth ratio, deleting the subspace; Step S406, after the maintenance is completed, a first association relationship between the mold model, the finished product model and the third control parameter is established, the current mold model and the current finished product model are obtained, and the corresponding third control parameter is obtained according to the first association relationship.

8. A forming management and control system for a semi-solid magnesium alloy, the system being used to execute the forming management and control method for a semi-solid magnesium alloy according to claim 1, characterized in that: It includes an acquisition module, an analysis module and a construction module; The acquisition module is used to obtain the finished product model and the mold model, match the corresponding first control parameter according to the finished product model and the mold model, and send the first control signal according to the first control parameter; The analysis module is used to obtain actual finished product pictures and historical defect information, wherein the historical defect information includes historical finished product models, corresponding historical finished product pictures, corresponding historical defect names, and corresponding historical defect causes, and the corresponding historical finished product pictures, corresponding historical defect names, and corresponding historical defect causes are matched according to the finished product models, respectively, and are recorded as the first picture, the first defect, and the first cause, respectively. The first cause corresponds to the first defect, and the similarity between the actual finished product picture and the first picture is calculated, and a similarity threshold is set. The actual finished product defect is judged according to the similarity threshold, and the defect name of the corresponding first picture is set as the actual finished product defect name, and the corresponding actual defect cause is obtained. The second control parameter is screened according to the defect cause corresponding to the actual finished product defect name, and a first change amount is set. A second control signal is issued according to the first change amount, and the second control parameter is continuously controlled to obtain the second control parameter after control, and the first control parameter is stored and updated according to the second control parameter after control to obtain the third control parameter; The construction module simulates the casting process according to the third control parameter, sets an acquisition cycle, continuously monitors the spatial temperature image in the molding cavity during the acquisition cycle, divides the spatial temperature image into subspaces, and continuously calculates the temperature change rate of the subspaces, selects faulty subspaces according to the temperature change rate, sends a maintenance signal, and after the maintenance is completed, establishes a first association relationship between the mold, the finished product model and the third control parameter.

9. An electronic device, characterized in that: It comprises a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a forming management and control method of a semi-solid magnesium alloy as described in claims 1-7 by calling the computer program stored in the memory.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a computer, the computer executes the forming management and control method of a semi-solid magnesium alloy as described in claims 1-7.

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