Method and device for dynamic optimization of process parameters for the production of aluminium alloy ingots

Abstract

The application is suitable for the technical field of process parameter optimization design, and particularly relates to an aluminum alloy ingot preparation process parameter dynamic optimization method and device. The method comprises the following steps: based on cooling intensity data and process constraint data, a current liquid forming section is analyzed to obtain a plurality of cooling sub-sections to be optimized; based on temperature data of a first cooling sub-section, process constraint data and superheat compensation, cooling intensity adjustment data of the first cooling sub-section is determined; based on the cooling intensity adjustment data of the second cooling sub-section, the cooling intensity adjustment data of the first cooling sub-section is connected to obtain adjustment parameters of each optimization point in the first cooling sub-section; and based on the adjustment parameters of each optimization point in the first cooling sub-section, the cooling process of the first cooling sub-section is optimized. The aluminum alloy ingot preparation process parameter dynamic optimization method can solve the technical problem that real-time parameter regulation cannot be realized.

Description

Technical Field

[0001] This application belongs to the field of process parameter optimization design technology, and in particular relates to a method and equipment for dynamic optimization of process parameters for aluminum alloy ingot preparation. Background Technology

[0002] Aluminum alloys are made by adding one or more elements (such as Mg, Si, Cu, Zn, Mn, Li, etc.) to an aluminum matrix, thereby improving its strength, hardness, corrosion resistance, weldability, and other properties through alloying. Compared to pure aluminum, aluminum alloys offer significant improvements in strength, stiffness, and durability.

[0003] In the traditional aluminum alloy ingot preparation process, the optimization parameters of the current liquid forming stage are usually adjusted based on the solidification state reflected after the cooling process. This results in a certain time gap between the discovery of problems from the solidification results and the actual modification in the next stage, making it impossible to achieve real-time parameter control. Summary of the Invention

[0004] This application provides a method and equipment for dynamic optimization of process parameters in aluminum alloy ingot preparation. It can solve the technical problem that in the traditional aluminum alloy ingot preparation process, the optimization parameters of the current liquid forming stage are usually adjusted based on the solidification state reflected after the cooling process. This results in a certain time gap between the discovery of the problem from the solidification result and the actual modification in the next stage, making it impossible to achieve real-time parameter control.

[0005] In a first aspect, embodiments of this application provide a method for dynamically optimizing process parameters for aluminum alloy ingot preparation, including:

[0006] Based on cooling intensity data and process constraint data, the current liquid forming section is analyzed to obtain several cooling sub-sections to be optimized; wherein, the cooling intensity data is used to indicate the intensity of adjusting the cooling water flow rate or the coolant effect; the process constraint data is used to reflect the safe temperature that the billet can accept;

[0007] Each cooling sub-segment to be optimized is optimized separately. Based on the temperature data of the first cooling sub-segment, the process constraint data, and the superheat compensation amount, the cooling intensity adjustment data of the first cooling sub-segment is determined; wherein, the superheat compensation amount is used to adjust the temperature data of the first cooling sub-segment.

[0008] Based on the cooling intensity adjustment data of the second cooling sub-segment, the cooling intensity adjustment data of the first cooling sub-segment is processed to obtain the adjustment parameters of each optimization point within the first cooling sub-segment; wherein, the second cooling sub-segment is the preceding cooling sub-segment of the first cooling sub-segment; the processing is used to indicate that the cooling intensity adjustment data at the front end of the first cooling sub-segment is connected to the cooling intensity adjustment data at the rear end of the second cooling sub-segment.

[0009] Based on the adjustment parameters of each optimization point within the first cooling sub-segment, the cooling process of the first cooling sub-segment is optimized.

[0010] The technical solutions described in this application embodiment have at least the following technical effects:

[0011] The method for dynamic optimization of aluminum alloy ingot preparation process parameters provided in this application analyzes the current liquid forming section based on cooling intensity data and process constraint data to obtain multiple cooling sub-segments to be optimized. Each cooling sub-segment is optimized separately. Based on the temperature data, process constraint data, and superheat compensation amount of the first cooling sub-segment, the cooling intensity adjustment data of the first cooling sub-segment is determined. Based on the cooling intensity adjustment data of the second cooling sub-segment, the cooling intensity adjustment data of the first cooling sub-segment is processed to obtain the adjustment parameters for each optimization point within the first cooling sub-segment. Based on the adjustment parameters of each optimization point within the first cooling sub-segment, the cooling process of the first cooling sub-segment is optimized. By coarsely adjusting the temperature data, process constraint data, and superheat compensation of the first cooling sub-section, the temperature data of the first cooling sub-section is adjusted in advance to determine the cooling intensity adjustment data of the first cooling sub-section. Then, the first cooling sub-section is independently optimized. Subsequently, the adjustment data of the second cooling sub-section is used to connect the first sub-section, so that the control of the front end of the first cooling sub-section and the control of the back end of the second cooling sub-section are seamlessly matched in cooling optimization. It is no longer necessary to rely on the solidification state reflected after the cooling process to adjust the optimization parameters of the current liquid forming section, thus enabling real-time parameter control.

[0012] In one possible implementation of the first aspect, each of the cooling sub-segments to be optimized is optimized separately. Based on the temperature data of the first cooling sub-segment, the process constraint data, and the superheat compensation amount, cooling intensity adjustment data of the first cooling sub-segment is determined, including:

[0013] Each cooling sub-segment to be optimized is optimized separately, and first compensation data is obtained based on the temperature data of the first cooling sub-segment and the superheat compensation amount; wherein, the first compensation data is used to reflect the temperature after adjusting the temperature data of the first cooling sub-segment based on the superheat compensation amount;

[0014] If the first compensation data exceeds the process constraint data, the cooling intensity adjustment data of the first cooling sub-segment is obtained based on the process constraint data and the first compensation data.

[0015] If the first compensation data does not exceed the process constraint data, the preset cooling intensity adjustment data is used as the cooling intensity adjustment data for the first cooling sub-segment.

[0016] In one possible implementation of the first aspect, each of the cooling sub-segments to be optimized is optimized separately. Based on the temperature data of the first cooling sub-segment, the process constraint data, and the superheat compensation amount, cooling intensity adjustment data of the first cooling sub-segment is determined, including:

[0017] Each cooling sub-segment to be optimized is optimized separately. Based on the temperature data of the first cooling sub-segment, the correction data, and the superheat compensation amount, second compensation data is obtained. The correction data is used to dynamically correct the temperature data of the first cooling sub-segment. The second compensation data reflects the temperature after the temperature data of the first cooling sub-segment is adjusted based on the correction data and the superheat compensation amount.

[0018] If the second compensation data exceeds the process constraint data, the cooling intensity adjustment data of the first cooling sub-segment is obtained based on the process constraint data and the second compensation data.

[0019] If the second compensation data does not exceed the process constraint data, the preset cooling intensity adjustment data is used as the cooling intensity adjustment data for the first cooling sub-segment.

[0020] In one possible implementation of the first aspect, based on the cooling intensity adjustment data of the second cooling sub-segment, the cooling intensity adjustment data of the first cooling sub-segment is processed to obtain the adjustment parameters for each optimization point within the first cooling sub-segment, including:

[0021] Obtain the transition region of the first cooling sub-segment; wherein, the front end of the transition region of the first cooling sub-segment is the front end of the first cooling sub-segment;

[0022] Based on the cooling intensity adjustment data of the first cooling sub-segment and the cooling intensity adjustment data of the second cooling sub-segment, a connection process is performed on each optimization point in the transition area to determine the adjustment parameters of each optimization point in the transition area.

[0023] In one possible implementation of the first aspect, the method further includes:

[0024] The largest adjustment parameter among all the optimization points in the first cooling sub-segment is determined as the first parameter;

[0025] For each optimization point within the transition region, if the adjustment coefficient calculated for the optimization point does not exceed the first parameter, the adjustment coefficient calculated for the optimization point is used as the adjustment parameter for the optimization point.

[0026] For each optimization point within the transition region, if the adjustment coefficient calculated for the optimization point exceeds the first parameter, the first parameter is used as the adjustment parameter for the optimization point.

[0027] In one possible implementation of the first aspect, the method further includes:

[0028] The transition region is determined based on a preset region and / or the region corresponding to the maximum temperature within the first cooling sub-segment; wherein the rear end of the transition region is in front of the region corresponding to the maximum temperature within the first cooling sub-segment.

[0029] In one possible implementation of the first aspect, based on cooling intensity data and process constraint data, the current liquid forming section is analyzed to obtain multiple cooling sub-segments to be optimized, including:

[0030] Obtain the initial temperature data corresponding to the current liquid forming section;

[0031] Based on the cooling intensity data, a cooling calculation is performed on the initial temperature data to obtain a first temperature;

[0032] If the length of the current liquid forming segment exceeds the first length, the liquid forming segment with the first temperature greater than the process constraint data is regarded as a number of cooling sub-segments to be optimized.

[0033] In one possible implementation of the first aspect, when the length corresponding to the current liquid forming segment exceeds a first length, the liquid forming segment with the first temperature greater than the process constraint data is designated as multiple cooling sub-segments to be optimized, including:

[0034] If the length of the current liquid forming segment exceeds the first length, the liquid forming segment with the first temperature greater than the process constraint data is obtained, and the liquid forming segment with the first temperature greater than the process constraint data is determined as a plurality of cooling sub-segments to be optimized according to the first length.

[0035] In one possible implementation of the first aspect, the method further includes:

[0036] If the length of the current liquid forming segment does not exceed the first length, the liquid forming segment with the first temperature greater than the process constraint data is regarded as the cooling sub-segment to be optimized.

[0037] In a second aspect, embodiments of this application provide a dynamic optimization system for aluminum alloy ingot preparation process parameters, used to implement the dynamic optimization method for aluminum alloy ingot preparation process parameters described in any of the first aspects above. The dynamic optimization system is applied to aluminum alloy ingot preparation equipment, and includes:

[0038] The analysis unit is used to analyze the current liquid forming section based on cooling intensity data and process constraint data to obtain multiple cooling sub-segments to be optimized; wherein, the cooling intensity data is used to indicate the intensity of adjusting the cooling water flow rate or the coolant effect; the process constraint data is used to reflect the safe temperature that the billet can accept;

[0039] The determining unit is used to optimize each of the cooling sub-segments to be optimized, and to determine the cooling intensity adjustment data of the first cooling sub-segment based on the temperature data of the first cooling sub-segment, the process constraint data, and the superheat compensation amount; wherein, the superheat compensation amount is used to adjust the temperature data of the first cooling sub-segment.

[0040] The generation unit is used to perform a connection process on the cooling intensity adjustment data of the first cooling sub-segment based on the cooling intensity adjustment data of the second cooling sub-segment, to obtain the adjustment parameters of each optimization point in the first cooling sub-segment; wherein, the second cooling sub-segment is the cooling sub-segment preceding the first cooling sub-segment; the connection process is used to instruct the cooling intensity adjustment data at the front end of the first cooling sub-segment to be connected with the cooling intensity adjustment data at the rear end of the second cooling sub-segment;

[0041] The optimization unit is used to optimize the cooling process of the first cooling sub-segment based on the adjustment parameters of each optimization point within the first cooling sub-segment.

[0042] Thirdly, embodiments of this application provide a device for dynamically optimizing process parameters of aluminum alloy ingot preparation, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for dynamically optimizing process parameters of aluminum alloy ingot preparation as described in any of the first aspects above.

[0043] It is understood that the beneficial effects of the second and third aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a flowchart illustrating a method for dynamically optimizing process parameters in aluminum alloy ingot preparation according to an embodiment of this application.

[0046] Figure 2 This is a schematic diagram of the implementation process of determining the cooling intensity adjustment data of the first cooling segment in the dynamic optimization method of aluminum alloy ingot preparation process parameters provided in an embodiment of this application;

[0047] Figure 3 This is a schematic diagram of the structure of the dynamic optimization system for aluminum alloy ingot preparation process parameters provided in the embodiments of this application;

[0048] Figure 4 This is a schematic diagram of the aluminum alloy ingot preparation equipment provided in the embodiments of this application. Detailed Implementation

[0049] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0050] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0051] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0052] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if the described condition or event is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once the described condition or event is detected," or "in response to the detection of the described condition or event."

[0053] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0054] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0055] In related technologies, aluminum alloys are made by adding one or more elements (such as Mg, Si, Cu, Zn, Mn, Li, etc.) to an aluminum matrix, thereby improving properties such as strength, hardness, corrosion resistance, and weldability through alloying. Compared to pure aluminum, aluminum alloys offer significant improvements in strength, stiffness, and durability.

[0056] In traditional aluminum alloy ingot manufacturing processes, the optimization parameters of the current liquid forming segment are typically adjusted based on the solidification state observed after the cooling process. This results in a time lag between identifying problems in the solidification results and making actual modifications in the next stage, hindering real-time parameter control. For example, the optimization parameters of the current liquid forming segment may be adjusted only after cracks, inclusion aggregation, coarse grains, or uneven grain distribution are detected during subsequent solidification. Furthermore, segmented adjustments guided by subsequent solidification results, or adjustments based on data from the current liquid forming segment, often overlook the connection issues at the boundaries between adjacent liquid forming segments (e.g., a sudden increase or decrease in cooling intensity between adjacent segments, such as high cooling intensity at the rear end of the second cooling segment and low cooling intensity at the front end of the first cooling segment). This leads to abrupt changes in the temperature field at the junction of the first and second cooling segments, creating stress concentration areas. This causes a sudden change in the billet temperature, resulting in stress differences and ultimately quality defects such as surface depressions and internal microcracks.

[0057] To address the aforementioned issues, this application provides a method and equipment for dynamically optimizing process parameters in aluminum alloy ingot preparation.

[0058] This method analyzes the current liquid forming section based on cooling intensity data and process constraint data to obtain multiple cooling sub-segments to be optimized. Each sub-segment is then optimized individually. Based on the temperature data, process constraint data, and superheat compensation amount of the first cooling sub-segment, the cooling intensity adjustment data for that sub-segment is determined. Using the cooling intensity adjustment data of the second cooling sub-segment, the cooling intensity adjustment data of the first sub-segment is combined to obtain adjustment parameters for each optimization point within the first cooling sub-segment. Based on the adjustment parameters for each optimization point within the first cooling sub-segment, the cooling process of the first cooling sub-segment is optimized. By coarsely adjusting the temperature data, process constraint data, and superheat compensation of the first cooling sub-section, the temperature data of the first cooling sub-section is adjusted in advance to determine the cooling intensity adjustment data of the first cooling sub-section. Then, the first cooling sub-section is independently optimized. Subsequently, the adjustment data of the second cooling sub-section is used to connect the first sub-section, so that the control of the front end of the first cooling sub-section and the control of the back end of the second cooling sub-section are seamlessly matched in cooling optimization. It is no longer necessary to rely on the solidification state reflected after the cooling process to adjust the optimization parameters of the current liquid forming section, thus enabling real-time parameter control.

[0059] The dynamic optimization method for aluminum alloy ingot preparation process parameters provided in this application embodiment can be applied to aluminum alloy ingot preparation equipment. In this case, the aluminum alloy ingot preparation equipment is the subject of execution of the dynamic optimization method for aluminum alloy ingot preparation process parameters provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of aluminum alloy ingot preparation equipment.

[0060] For example, aluminum alloy ingot preparation equipment may include a melting device (such as an electric furnace / induction furnace for melting raw materials), a casting machine (for initially shaping the molten metal from the melting device), a water cooler (for cooling the initially shaped ingot), a cutting machine (for cutting the cooled ingot into appropriate lengths), and a control device. The control device is electrically connected to the melting device, the casting machine, the water cooler, and the cutting machine, respectively. The control device can control the melting device to melt the raw materials, then control the casting machine to initially shape the molten metal from the melting device, then control the water cooler to cool the initially shaped ingot, and finally control the cutting machine to cut the cooled ingot into appropriate lengths to obtain the finished aluminum alloy ingot.

[0061] For example, the control device can be a microcontroller, mobile phone, tablet computer, laptop computer, ultra-mobile personal computer (UMPC), netbook, desktop computer, computing device, or computer, laptop computer, handheld communication device, handheld computing device, etc. connected to a wireless modem.

[0062] To better understand the dynamic optimization method for aluminum alloy ingot preparation process parameters provided in the embodiments of this application, the specific implementation process of the dynamic optimization method for aluminum alloy ingot preparation process parameters provided in the embodiments of this application will be described by way of example below.

[0063] Figure 1 This paper presents a schematic flowchart illustrating a method for dynamically optimizing process parameters in aluminum alloy ingot preparation, as provided in an embodiment of this application. The method includes:

[0064] S100, based on cooling intensity data and process constraint data, analyzes the current liquid forming section to obtain several cooling sub-segments to be optimized. The cooling intensity data indicates the intensity of adjustments to the cooling water flow rate or the coolant's effect. The process constraint data reflects the safe temperature range that the cast billet can tolerate.

[0065] It is understood that cooling intensity data is used to reflect the adjustable cooling capacity parameters of the cooling system. Cooling intensity data can include cooling water flow rate data (such as inlet and outlet flow rates) and coolant intensity data (such as coolant injection pressure and coolant concentration). Process constraint data is used to define the acceptable "safe temperature range" for the cast billet during cooling. The value of the safe temperature can be determined based on the material, specifications, and liquid forming process parameters of the aluminum alloy ingot being liquid-formed. The first cooling segment is the cooling segment in the current cycle that requires cooling intensity adjustment and parameter optimization.

[0066] For example, the initial temperature data corresponding to the current liquid forming segment is obtained. Cooling calculations are performed on the initial temperature data based on cooling intensity data to obtain a first temperature. If the length of the current liquid forming segment exceeds the first length, the liquid forming segments with a first temperature greater than the process constraint data are designated as multiple cooling sub-segments to be optimized. If the length of the current liquid forming segment does not exceed the first length, the liquid forming segments with a first temperature greater than the process constraint data are designated as cooling sub-segments to be optimized.

[0067] For example, the cooling intensity data is q=K× × =0.83 (where α is the flow rate influence coefficient and b is the pressure influence coefficient, for example, α is 0.6 and b is 0.3), the process constraint data is 650°C, and the initial temperature data corresponding to the current liquid forming section is 730°C. According to the cooling intensity data, the initial temperature data is cooled and calculated (i.e., 730 × 0.83 = 605.9°C). The temperature after cooling is still greater than the process constraint data. Therefore, multiple cooling sub-segments to be optimized are determined for the liquid forming section (such as along the length direction) that is greater than the process constraint data.

[0068] This setup optimizes only the segment experiencing persistent overheating, eliminating the need to adjust the entire liquid forming section, thus reducing the energy consumption and operational complexity of the cooling system.

[0069] S200 optimizes each cooling sub-segment to be optimized separately. Based on the temperature data, process constraint data, and superheat compensation amount of the first cooling sub-segment, the cooling intensity adjustment data of the first cooling sub-segment is determined. Among them, the superheat compensation amount is used to adjust the temperature data of the first cooling sub-segment.

[0070] It is understandable that cooling intensity adjustment data is used to indicate the cooling water flow rate or the intensity of the coolant effect in a water chiller, for example, by changing the water flow rate or pressure.

[0071] In traditional techniques, the cooling intensity adjustment data for the first cooling segment is typically calculated directly based on process constraint data and the temperature data of the first cooling segment. However, this method has a problem: if the temperature of the subsequent casting segment fluctuates, such as increasing, and if the current temperature of the liquid forming segment is slightly higher than the process constraint data (e.g., the process constraint data is 650℃, and the current temperature of the liquid forming segment is 660℃), the calculated cooling intensity adjustment data is 650÷660≈0.985 (only a slight enhancement in cooling is needed). If the temperature rises to 670℃, after cooling treatment using the adjusted cooling intensity data, the temperature will still be higher than the process constraint data, i.e., 670×0.985=659.95°C, which is higher than the process constraint data of 650℃. In other words, the cooling intensity adjustment data for the first cooling segment calculated directly based on the process constraint data and the temperature data of the first cooling segment can only satisfy the condition that the temperature of the casting segment does not fluctuate.

[0072] To address this issue, this application adjusts the temperature data of the first cooling segment by using superheat compensation. The calculated cooling intensity adjustment data is less than the "cooling intensity adjustment data of the first cooling segment calculated directly based on process constraint data and the temperature data of the first cooling segment". In other words, compared to the traditional method, even when the temperature of the billet segment fluctuates, the temperature after cooling treatment can still meet the requirements of the process constraint data, achieving a more conservative cooling intensity adjustment (a stronger cooling enhancement).

[0073] For example, the temperature data of the first cooling segment is corrected using a superheat compensation amount to obtain the compensated temperature. Based on the compensated temperature and process constraint data, the cooling intensity adjustment data for the first cooling segment is determined. For instance, when the process constraint data is 650℃, the superheat compensation amount can be 65℃ (i.e., 10% of the process constraint data). If the temperature data of the first cooling segment is 680℃, then the first compensation data is 680 + 65 = 745℃, which is greater than the process constraint data of 650℃. Therefore, 650 ÷ 745 ≈ 0.87. That is, the cooling intensity of this liquid forming segment needs to be increased by 13% (achieved by increasing the water flow rate (by 13% on the original basis) or the pressure), which is how the cooling intensity adjustment data for the first cooling segment is determined.

[0074] With this setup, if the cooling intensity is calculated directly based on the current temperature and process constraints, it is easy to exceed the process constraints when the billet temperature fluctuates. By using superheat compensation to shift the temperature data towards a "conservative target range," subsequent temperature fluctuations can be pre-corrected. The resulting cooling intensity adjustment data can still maintain a greater margin for overheating risk, reducing overheating or process deviations caused by temperature fluctuations.

[0075] In one possible implementation, S200, each cooling sub-segment to be optimized is optimized separately. Based on the temperature data, process constraint data, and superheat compensation amount of the first cooling sub-segment, the cooling intensity adjustment data of the first cooling sub-segment is determined, including:

[0076] S210, each cooling sub-segment to be optimized is optimized separately, and first compensation data is obtained based on the temperature data and superheat compensation amount of the first cooling sub-segment. The first compensation data reflects the temperature of the first cooling sub-segment after adjusting the temperature data based on the superheat compensation amount.

[0077] It is understandable that temperature measuring devices (such as infrared thermometers) are arranged at the inlet section (e.g., 0.2m from the start of the first cooling section), the intermediate section (e.g., the midpoint of the first cooling section), and the outlet section (e.g., 0.2m from the end of the first cooling section) of the first cooling section along the billet's travel direction, and the temperature at each optimized point is recorded. For the temperature data corresponding to each optimized point within the first cooling section, a superheat compensation amount is superimposed to obtain multiple first compensation data points; for example, first compensation data = superheat compensation amount + temperature data.

[0078] It should be noted that the formula for calculating the superheat compensation ΔTb is ΔTb=k×(ΔTh-ΔT1), where k is the compensation coefficient (calibrated through orthogonal experiments, with a value ranging from 0.3 to 0.5; the larger the billet thickness, the larger the k value, to enhance the adjustment of superheat sensitivity for thick billets). When the measured superheat ΔTh (e.g., the actual temperature of the molten aluminum in the mold - the liquidus temperature of the aluminum alloy) is higher than the standard value ΔT1 (set to 60℃), ΔTb is positive (indicating that cooling needs to be strengthened to offset the effect of excessive superheat); when ΔTh is lower than ΔT1, ΔTb is negative (indicating that cooling can be appropriately reduced).

[0079] With this setting, when temperature fluctuations occur (such as an increase in superheat) due to the superheat compensation amount, the first compensation data will be raised accordingly, so that the temperature data will shift towards the "conservative target range". This can pre-correct subsequent temperature fluctuations, thereby solving the problem of overheating or process deviation caused by the traditional method of "judging cooling requirements only based on surface temperature measurement data".

[0080] S220, if the first compensation data exceeds the process constraint data, the cooling intensity adjustment data of the first cooling sub-segment is obtained based on the process constraint data and the first compensation data.

[0081] It is understandable that when the first compensation data exceeds the process constraint data, the temperature difference between the first compensation data and the process constraint data can be obtained based on the process constraint data and the first compensation data. The cooling intensity adjustment data of the first cooling sub-section can be obtained by matching the cooling intensity increase (ΔQ), the heat dissipation of the billet in the first cooling sub-section and the temperature deviation, which is used to indicate the cooling water flow rate or the intensity of the coolant in the water chiller. For example, ΔQ = (c × ρ × V × ΔT) ÷ (S × t × η), where c is the specific heat capacity of the aluminum alloy, ρ is the density of the aluminum alloy, V is the volume of the billet in the first cooling section, ΔT is the temperature difference between the first compensation data and the process constraint data, S is the effective contact area between the cooling system and the billet (determined by the number of nozzles, the spray angle, and the coverage area), t is the residence time of the billet in the first cooling section (section length ÷ liquid forming speed), and η is the thermal efficiency of the cooling system (valued at 0.85). For example, the process constraint data is 580℃, the first compensation data is 596℃, the temperature deviation ΔT = 16℃, the aluminum alloy square ingot has a cross-section of 300mm × 500mm, and the billet... With a section length of 2m and a liquid forming speed of 2.2m / min, then V = 2m × 0.3m × 0.5m = 0.3m³, S = 2m × (0.3m + 0.5m) × 0.8 (spray coverage) = 1.28m², t = 2m ÷ (2.2m / min ÷ 60s / min) = 54.5s, ΔQ = (900 × 2700 × 0.3 × 11) / (1.28 × 54.5 × 0.85) ≈ 0.42m³ / h, and the adjusted data = current flow rate 2.0m³ / h + 0.42m³ / h = 2.42m³ / h. Therefore, the cooling intensity adjustment data reflects adjusting the current flow rate from 2.0m³ to 2.42m³ / h.

[0082] With this setup, if the cooling intensity is calculated directly based on the current temperature and process constraints, it is easy to exceed the process constraints when the billet temperature fluctuates. By using superheat compensation to shift the temperature data towards a "conservative target range," subsequent temperature fluctuations can be pre-corrected. The resulting cooling intensity adjustment data can still maintain a greater margin for overheating risk, reducing overheating or process deviations caused by temperature fluctuations.

[0083] S230, if the first compensation data does not exceed the process constraint data, the preset cooling intensity adjustment data is used as the cooling intensity adjustment data for the first cooling sub-segment.

[0084] It is understandable that the preset cooling intensity adjustment data refers to a standardized cooling parameter scheme that is pre-set based on historical production data, process experiment results and billet solidification characteristics. Its core function is to maintain the stability and continuity of the cooling process when the billet temperature is within a safe range, and to avoid temperature fluctuations caused by frequent adjustments.

[0085] For example, the system automatically compares all the first compensation data (inlet, middle, and outlet) of the first cooling sub-segment with the process constraint data, confirms that the temperature of all optimized points is within the safe range, and meets the condition for three consecutive sampling cycles (0.5 seconds per cycle). If this condition is met, it is determined that the first compensation data does not exceed the process constraint data. Therefore, the preset cooling intensity adjustment data can be used as the cooling intensity adjustment data of the first cooling sub-segment.

[0086] This setting allows for the maintenance of stability and continuity of the cooling process while the billet temperature remains within a safe range, avoiding temperature fluctuations caused by frequent adjustments.

[0087] In one possible implementation, S200, each cooling sub-segment to be optimized is optimized separately. Based on the temperature data, process constraint data, and superheat compensation amount of the first cooling sub-segment, the cooling intensity adjustment data of the first cooling sub-segment is determined, including:

[0088] S240, each cooling segment to be optimized is optimized separately. Based on the temperature data, correction data, and superheat compensation amount of the first cooling segment, second compensation data is obtained. The correction data is used to dynamically correct the temperature data of the first cooling segment. The second compensation data reflects the temperature after adjusting the temperature data of the first cooling segment based on the correction data and the superheat compensation amount.

[0089] It is understandable that the correction data is a set of adjustment parameters used to dynamically correct the temperature data of the first cooling segment, in order to compensate for temperature measurement deviations caused by "non-superheating factors". Non-superheating factors can include: ambient temperature correction value (due to the impact of workshop ambient temperature fluctuations (e.g., 35℃ in summer, 15℃ in winter) on temperature measurement accuracy, such as an ambient temperature correction value of 0.03), equipment aging correction value (e.g., a value of 0.2), and cooling water temperature correction value (due to the impact of cooling water source temperature fluctuations on heat dissipation efficiency, such as a value of -0.3). Correction data = Ambient temperature correction value × Temperature data + Equipment aging correction value + Cooling water temperature correction value.

[0090] For example, the original temperature data of the first cooling segment is first corrected using corrected data. For instance, if the inlet temperature of the first cooling segment is 590℃, the corrected value is 590×0.03+0.2-0.5=17.7-0.3=17.4℃, then Tcorrected=590+17.4=607.4℃. Based on the corrected temperature, a superheat compensation is added to obtain the second compensation data. Similarly, the second compensation data for the intermediate and outlet points are calculated to form the complete segment temperature distribution.

[0091] This setting solves the problem of insufficient accuracy caused by "only considering the single factor of superheat" in traditional temperature regulation, and provides a higher fidelity temperature reference for subsequent cooling intensity adjustment.

[0092] S250, if the second compensation data exceeds the process constraint data, the cooling intensity adjustment data of the first cooling sub-segment is obtained based on the process constraint data and the second compensation data.

[0093] It is understandable that when the second compensation data exceeds the process constraint data, the temperature difference between the second compensation data and the process constraint data can be obtained based on the process constraint data and the second compensation data. The cooling intensity adjustment data of the second cooling sub-section can be obtained by matching the cooling intensity increase (ΔQ), the heat dissipation of the billet in the second cooling sub-section and the temperature deviation, which is used to indicate the cooling water flow rate or the intensity of the coolant in the water chiller.

[0094] This setting, by adjusting the overheat compensation amount, shifts the temperature data towards a "conservative target range," enabling pre-correction of subsequent temperature fluctuations. The resulting cooling intensity adjustment data still maintains a greater margin against overheating risks, reducing overheating or process deviations caused by temperature fluctuations, environmental influences, or equipment aging.

[0095] S260, if the second compensation data does not exceed the process constraint data, the preset cooling intensity adjustment data is used as the cooling intensity adjustment data for the first cooling sub-segment.

[0096] For example, the system automatically compares all the second compensation data (inlet, middle, and outlet) of the second cooling sub-segment with the process constraint data, confirms that the temperature of all optimized points is within the safe range, and meets the condition for three consecutive sampling cycles (0.5 seconds per cycle). If this condition is met, it is determined that the second compensation data does not exceed the process constraint data. Therefore, the preset cooling intensity adjustment data can be used as the cooling intensity adjustment data of the second cooling sub-segment.

[0097] This setting allows for the maintenance of stability and continuity of the cooling process while the billet temperature remains within a safe range, avoiding temperature fluctuations caused by frequent adjustments.

[0098] S300: Based on the cooling intensity adjustment data of the second cooling sub-segment, the cooling intensity adjustment data of the first cooling sub-segment is processed to obtain the adjustment parameters for each optimization point within the first cooling sub-segment. The second cooling sub-segment is the preceding cooling sub-segment of the first cooling sub-segment. The processing indicates that the cooling intensity adjustment data at the beginning of the first cooling sub-segment is connected to the cooling intensity adjustment data at the end of the second cooling sub-segment.

[0099] It can be understood that the second cooling section is the cooling section that the billet passes through first in the preparation direction, directly in front of the first cooling section. That is, after the billet flows out of the second cooling section, it directly enters the first cooling section.

[0100] In traditional techniques, analyzing and adjusting based on the data of the current liquid forming section often overlooks the connection issues at the boundary between adjacent liquid forming sections. For example, if the cooling intensity adjustment data for the second cooling sub-section is 0.5, while the cooling intensity adjustment data for the first cooling sub-section is 0.87, this can lead to a sudden increase or decrease in the cooling intensity of adjacent liquid forming sections (e.g., the rear end of the second cooling sub-section has a high cooling intensity, while the front end of the first cooling sub-section has a low cooling intensity). This results in abrupt changes in the temperature field at the junction of the first and second cooling sub-sections, forming a stress concentration area. This causes a sudden change in the billet temperature, resulting in a stress difference and ultimately leading to quality defects such as surface depressions and internal microcracks.

[0101] For example, the second cooling sub-segment S2 is the previous segment, and the first cooling sub-segment S1 is the current segment. The connection point is between the end point of S2 and the beginning point of S1. The goal is to connect the first few points of S1 without changing the data in S2, so that there is no obvious jump between the two segments at the connection point. For example, if the first cooling sub-segment is 1 meter long, and 5 optimization points are divided at the beginning point of S1 at 0.2-meter intervals, the cooling intensity adjustment data of the second cooling sub-segment is processed with a fixed difference to obtain the adjustment parameters of each optimization point in the first cooling sub-segment. For example, if the cooling intensity adjustment data of the second cooling sub-segment is 0.5, and the fixed difference is 0.074, then the first optimization point in the first cooling sub-segment is 0.574, the second optimization point is 0.648, the third optimization point is 0.722, the fourth optimization point is 0.796, and the fifth optimization point is 0.87. In this way, there is no obvious jump between the end point of S2 and the beginning point of S1 at the connection point.

[0102] This setup allows for seamless relay of cooling between adjacent segments, ensuring the cooling requirements of the current segment while inheriting the thermal state of the preceding segment. It eliminates the need to rely on the solidification state reflected after the cooling process to adjust the optimization parameters of the current liquid forming segment, thereby enabling real-time parameter control.

[0103] In one possible implementation, S300, based on the cooling intensity adjustment data of the second cooling sub-segment, the cooling intensity adjustment data of the first cooling sub-segment is processed to obtain the adjustment parameters for each optimization point within the first cooling sub-segment, including:

[0104] S310, Obtain the transition region of the first cooling sub-segment. The front end of the transition region of the first cooling sub-segment is the front end of the first cooling sub-segment.

[0105] It can be understood that the instantaneous position of the billet after flowing out of the second cooling section and just entering the first cooling section is the front end of the transition region. The position where the temperature field enters a relatively steady state or the temperature gradient decreases significantly is the rear end of the transition region.

[0106] This setup allows for precise location of the transition area of ​​the first cooling segment, providing a clear spatial basis for subsequent optimization of cooling intensity in the transition area (such as preventing cracking caused by a sudden drop in temperature during the transition phase).

[0107] S320: Based on the cooling intensity adjustment data of the first cooling sub-segment and the cooling intensity adjustment data of the second cooling sub-segment, perform connection processing on each optimization point in the transition area to determine the adjustment parameters of each optimization point in the transition area.

[0108] For example, the second cooling sub-segment S2 is the previous segment, and the first cooling sub-segment S1 is the current segment. The connection point is between the end point of S2 and the beginning point of S1. The goal is to connect the first few points of S1 without changing the data in S2, so that there is no obvious jump between the two segments at the connection point. For example, if the first cooling sub-segment is 1 meter long, and 5 optimization points are divided at the beginning point of S1 at 0.2-meter intervals, the cooling intensity adjustment data of the second cooling sub-segment is processed with a fixed difference to obtain the adjustment parameters of each optimization point in the first cooling sub-segment. For example, if the cooling intensity adjustment data of the second cooling sub-segment is 0.5, and the fixed difference is 0.074, then the first optimization point in the first cooling sub-segment is 0.574, the second optimization point is 0.648, the third optimization point is 0.722, the fourth optimization point is 0.796, and the fifth optimization point is 0.87. In this way, there is no obvious jump between the end point of S2 and the beginning point of S1 at the connection point.

[0109] For example, the adjustment parameters for each optimization point within the transition region can also be obtained based on the cooling intensity adjustment data of the first cooling sub-segment, the cooling intensity adjustment data of the second cooling sub-segment, the distance from the optimization point to the front end of the transition region, and the length of the transition region. For instance, the adjustment parameter for the optimization point = cooling intensity adjustment data of the second cooling sub-segment + (cooling intensity adjustment data of the first cooling sub-segment - cooling intensity adjustment data of the second cooling sub-segment) × (1 - ... ), where k is a nonlinear coefficient (e.g., taking a value of 1.5), with the second optimization point ( Taking 0.15m as an example: the adjustment parameter of the second optimization point = 2.1 (the cooling intensity adjustment data of the rear end of the second cooling sub-section reflects the optimized flow rate as 2.1m³ / h) + 0.32×(1-0.79)≈2.167m³ / h. The changes in cooling intensity before and after the connection treatment are shown in Table 1: As can be seen from Table 1, after the connection treatment, the cooling intensity increased from 2.1m³ / h to 2.42m³ / h, and the temperature change rate was ≤5℃ / m (the allowable threshold of the process), avoiding the sudden drop in temperature caused by the sudden change of "2.1→2.42m³ / h" when there was no connection (the original temperature change rate could reach 12℃ / m).

[0110]

[0111] With this setup, the adjustment data of the second cooling segment can be used to connect the first segment, so that the control of the front end of the first cooling segment and the control of the back end of the second cooling segment can be seamlessly matched in terms of cooling optimization, eliminating sudden changes in cooling intensity. Furthermore, it is no longer necessary to rely on the solidification state reflected after the cooling process to adjust the optimization parameters of the current liquid forming segment, thereby enabling real-time parameter control.

[0112] S400 optimizes the cooling process of the first cooling sub-segment based on the adjustment parameters of each optimization point within the first cooling sub-segment.

[0113] It is understandable that "nozzle groups" are divided according to the length of the billet (e.g., one group of nozzles corresponds to every 0.2 meters, including nozzles in the upper, lower, and side directions). The physical location of each optimization point (e.g., 0.2 meters from the front end of the first sub-segment) needs to be bound to the corresponding "nozzle group number"—for example, optimization point P1 (front end) of the first sub-segment corresponds to "nozzle group No. 3" in the secondary cooling zone. Optimization point P2 (0.2 meters from the front end) corresponds to "nozzle group No. 4", and so on, so that the cooling demand of each optimization point is executed by a dedicated nozzle group, avoiding "cross-regional interference". The adjustment parameters of each optimization point in the first cooling sub-segment are converted into corresponding water flow rate commands (e.g., adjustment parameter 0.87 corresponds to a water flow rate of 2.5 m³ / h) and output to the nozzle group controller to complete real-time adjustment.

[0114] With this setup, it is no longer necessary to rely on the solidification state reflected after the cooling process to adjust the optimization parameters of the current liquid forming section, thus enabling real-time parameter control.

[0115] In one possible implementation, the method for dynamically optimizing the process parameters of aluminum alloy ingot preparation also includes:

[0116] S500 derives its first parameter based on cooling intensity data and the real-time temperature at each optimization point. This first parameter is the maximum adjustment parameter.

[0117] It is understandable that the largest adjustment parameter among all optimization points within the first cooling sub-segment is determined as the first parameter.

[0118] S600, for each optimization point within the transition region, if the adjustment coefficient calculated for the optimization point does not exceed the first parameter, the adjustment coefficient calculated for the optimization point is used as the adjustment parameter for the optimization point.

[0119] It is understandable that the adjustment coefficient obtained from the optimization point calculation can be obtained according to step S320. For each optimization point in the transition region, if the adjustment coefficient obtained from the optimization point calculation does not exceed the first parameter, the adjustment coefficient obtained from the optimization point calculation is used as the adjustment parameter of the optimization point.

[0120] Scenario 1: The real-time temperature of some optimization points may be affected by sensor fluctuations (such as the infrared thermometer being affected by water vapor) or oxide scale on the workpiece surface, resulting in "false high temperature". This leads to the calculated adjustment coefficient being too large (not in line with the actual requirements). If this abnormal value is used directly, it will cause unnecessary overcooling. At the same time, it may exceed the process safety limit of the entire first cooling sub-section, disrupt the gradient of cooling intensity, and cause "local temperature jumps".

[0121] This setting, by uniformly setting the upper limit of the adjustment parameters in the transition region to the first parameter, avoids excessive adjustments at certain points due to abnormal calculation results. If individual points are allowed to adjust according to their own calculated values, it may exceed the process safety limit of the entire first cooling sub-segment, disrupt the gradient of cooling intensity changes, and cause "local temperature jumps".

[0122] S700: For each optimization point within the transition region, if the adjustment coefficient calculated for the optimization point exceeds the first parameter, the first parameter will be used as the adjustment parameter for the optimization point.

[0123] It is understandable that the adjustment coefficient obtained from the optimization point calculation can be obtained according to step S320. For each optimization point in the transition region, if the adjustment coefficient obtained from the optimization point calculation exceeds the first parameter, the first parameter is used as the adjustment parameter of the optimization point.

[0124] This setting, by uniformly setting the upper limit of the adjustment parameters in the transition region to the first parameter, avoids excessive adjustments at certain points due to abnormal calculation results. If individual points are allowed to adjust according to their own calculated values, it may exceed the process safety limit of the entire first cooling sub-segment, disrupt the gradient of cooling intensity changes, and cause "local temperature jumps".

[0125] In one possible implementation, the method for dynamically optimizing the process parameters of aluminum alloy ingot preparation also includes:

[0126] The transition region is determined based on a preset region and / or the region corresponding to the maximum temperature within the first cooling sub-segment. The rear end of the transition region is in front of the region corresponding to the maximum temperature within the first cooling sub-segment.

[0127] This is understandable. One approach is to find the region where the maximum temperature falls, or the front end of that region, and then set the rear end of the transition region at that location. Alternatively, one can find the front end of the first cooling segment and locate the rear end of the transition region based on a preset area. For example, the transition region could be set to 10% of the length of the front end of the first cooling segment.

[0128] With this setup, the transition zone ends at the forefront of the maximum temperature region, providing a buffer time for subsequent switching, reducing the risk of exceeding the boundary, and ensuring that there is still enough warm / cool space to cope with disturbances during the transition.

[0129] In one possible implementation, S100, based on cooling intensity data and process constraint data, analyzes the current liquid forming section to obtain multiple cooling sub-segments to be optimized, including:

[0130] S110, obtain the initial temperature data corresponding to the current liquid forming section.

[0131] It is understandable that a temperature sensor (such as a surface thermocouple, a non-contact infrared sensor, etc.) is installed at the entrance of the current section of the billet to obtain the initial temperature data corresponding to the current liquid forming section.

[0132] S120, based on the cooling intensity data, performs cooling calculations on the initial temperature data to obtain the first temperature.

[0133] It is understandable that cooling pre-calculations are performed on the initial temperature data based on the cooling intensity data. For example, the temperature exhibited by the ingot after cooling with the current cooling intensity data can be determined based on the cooling medium flow rate (m³ / h), flow velocity (m / s), pressure (kPa), and initial temperature data in the cooling intensity data. For example, the first temperature = initial temperature data - (heat dissipation power per unit area × area × cooling time) ÷ mass of the ingot ÷ specific heat capacity of the ingot material, where the heat dissipation power per unit area is determined based on the cooling intensity data.

[0134] This setting provides a quantitative basis for subsequent parameter adjustments.

[0135] S130, if the length of the current liquid forming segment exceeds the first length, the liquid forming segment with the first temperature greater than the process constraint data is regarded as multiple cooling sub-segments to be optimized.

[0136] It is understandable that when the length of the current liquid forming segment exceeds the first length, the splitting step is initiated. However, not the entire liquid forming segment needs to be split. Only for the local area where the temperature exceeds the limit, the liquid forming segment with the first temperature greater than the process constraint data can be regarded as multiple cooling sub-segments to be optimized.

[0137] With this setup, the split "cooling sub-segments to be optimized" can accurately focus on the problem areas with excessive temperatures, and the "length control" can ensure that the cooling parameters (such as water volume and air speed) of each sub-segment can be optimized independently, avoiding the failure of local temperature control due to excessively long sub-segments.

[0138] In one possible implementation, S130, if the length corresponding to the current liquid forming segment exceeds a first length, the liquid forming segment with a first temperature greater than the process constraint data is designated as multiple cooling sub-segments to be optimized, including:

[0139] If the length of the current liquid forming segment exceeds the first length, obtain the liquid forming segment with the first temperature greater than the process constraint data, and determine the liquid forming segment with the first temperature greater than the process constraint data as multiple cooling sub-segments to be optimized based on the first length.

[0140] It is understandable that when the length of the current liquid forming segment exceeds the first length, the continuous area with excessive temperature is identified from the "current liquid forming segment", and based on the "first length", the continuous area with excessive temperature is divided into several cooling sub-segments.

[0141] This setup allows for precise control of overheating while avoiding overcooling of areas with acceptable temperatures.

[0142] In one possible implementation, the method for dynamically optimizing the process parameters of aluminum alloy ingot preparation also includes:

[0143] If the length of the current liquid forming segment does not exceed the first length, the liquid forming segment with a first temperature greater than the process constraint data is taken as the cooling sub-segment to be optimized.

[0144] It is understandable that if the length of the current liquid forming segment does not exceed the first length, the continuous region with excessive temperature can be directly taken as the cooling segment to be optimized instead of splitting it into several cooling sub-segments.

[0145] This setting provides a quantitative basis for subsequent parameter adjustments.

[0146] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0147] Corresponding to the dynamic optimization method for aluminum alloy ingot preparation process parameters described in the above embodiments, this application also provides a dynamic optimization system for aluminum alloy ingot preparation process parameters. Each unit of this system can realize each step of the dynamic optimization method for aluminum alloy ingot preparation process parameters. Figure 3 The diagram shows a structural block diagram of the dynamic optimization system for aluminum alloy ingot preparation process parameters provided in the embodiments of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0148] Reference Figure 3 The dynamic optimization system for aluminum alloy ingot preparation process parameters includes:

[0149] The analysis unit analyzes the current liquid forming section based on cooling intensity data and process constraint data to obtain multiple cooling sub-segments to be optimized. The cooling intensity data indicates the effectiveness of adjusting the cooling water flow rate or the coolant. The process constraint data reflects the safe temperature range that the cast billet can withstand.

[0150] The determination unit is used to optimize each cooling sub-segment to be optimized separately. Based on the temperature data, process constraint data, and superheat compensation amount of the first cooling sub-segment, it determines the cooling intensity adjustment data of the first cooling sub-segment. Among them, the superheat compensation amount is used to adjust the temperature data of the first cooling sub-segment.

[0151] The generation unit is used to perform a connection process on the cooling intensity adjustment data of the first cooling sub-segment based on the cooling intensity adjustment data of the second cooling sub-segment, to obtain the adjustment parameters for each optimization point within the first cooling sub-segment. The second cooling sub-segment is the preceding cooling sub-segment of the first cooling sub-segment. The connection process is used to instruct the connection between the cooling intensity adjustment data at the beginning of the first cooling sub-segment and the cooling intensity adjustment data at the end of the second cooling sub-segment.

[0152] The optimization unit is used to optimize the cooling process of the first cooling sub-segment based on the adjustment parameters of each optimization point within the first cooling sub-segment.

[0153] It should be noted that the information interaction and execution process between the above systems / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0154] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units is merely an example. In practical applications, the above functions can be assigned to different functional units as needed, that is, the internal structure of the system can be divided into different functional units to complete all or part of the functions described above. The functional units in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0155] This application also provides an aluminum alloy ingot preparation device. Figure 4 This is a schematic diagram of the structure of an aluminum alloy ingot preparation apparatus provided in one embodiment of this application. Figure 4As shown, the aluminum alloy ingot preparation equipment 6 of this embodiment includes: at least one processor 60 ( Figure 4 Only one is shown in the image), at least one memory 61 ( Figure 4 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, it causes the aluminum alloy ingot preparation equipment 6 to implement the steps in any of the above-described embodiments of the dynamic optimization method for aluminum alloy ingot preparation process parameters, or causes the aluminum alloy ingot preparation equipment 6 to implement the functions of each unit in the above-described system embodiments.

[0156] Exemplarily, the computer program 62 may be divided into one or more units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 62 in the aluminum alloy ingot preparation equipment 6.

[0157] The aluminum alloy ingot preparation equipment 6 may include a melting device (such as an electric furnace / induction furnace for melting raw materials), a casting machine (for initially shaping the molten metal from the melting device), a water cooler (for cooling the initially shaped ingot), a cutting machine (for cutting the cooled ingot into appropriate lengths), and a control device. The control device is electrically connected to the melting device, the casting machine, the water cooler, and the cutting machine, respectively. The control device can control the melting device to melt the raw materials, then control the casting machine to initially shape the molten metal from the melting device, then control the water cooler to cool the initially shaped ingot, and finally control the cutting machine to cut the cooled ingot into appropriate lengths to obtain the finished aluminum alloy ingot. The aluminum alloy ingot preparation equipment 6 may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that… Figure 4 This is merely an example of aluminum alloy ingot preparation equipment 6 and does not constitute a limitation on aluminum alloy ingot preparation equipment 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0158] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0159] In some embodiments, the memory 61 may be an internal storage unit of the aluminum alloy ingot preparation equipment 6, such as a hard disk or memory of the aluminum alloy ingot preparation equipment 6. In other embodiments, the memory 61 may be an external storage device of the aluminum alloy ingot preparation equipment 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the aluminum alloy ingot preparation equipment 6. Further, the memory 61 may include both internal storage units and external storage devices of the aluminum alloy ingot preparation equipment 6. The memory 61 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of the computer program. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0160] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0161] This application provides a computer program product that, when run on an aluminum alloy ingot preparation device, enables the aluminum alloy ingot preparation device to perform the steps described in any of the above method embodiments.

[0162] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to the aluminum alloy ingot preparation equipment, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, such as a USB flash drive, a portable hard drive, a magnetic disk, or an optical disk.

[0163] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0164] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0165] In the embodiments provided in this application, it should be understood that the disclosed aluminum alloy ingot preparation equipment, aluminum alloy ingot preparation process parameter dynamic optimization system, and aluminum alloy ingot preparation process parameter dynamic optimization method can be implemented in other ways. For example, the embodiments of aluminum alloy ingot preparation equipment and aluminum alloy ingot preparation process parameter dynamic optimization system described above are merely illustrative. For example, the division of units is merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0166] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0167] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for dynamic optimization of process parameters in aluminum alloy ingot preparation, characterized in that, The method includes: Based on cooling intensity data and process constraint data, the current liquid forming section is analyzed to obtain several cooling sub-sections to be optimized; wherein, the cooling intensity data is used to indicate the intensity of adjusting the cooling water flow rate or the coolant effect; the process constraint data is used to reflect the safe temperature that the billet can accept; Each cooling sub-segment to be optimized is optimized separately. Based on the temperature data of the first cooling sub-segment, the process constraint data, and the superheat compensation amount, the cooling intensity adjustment data of the first cooling sub-segment is determined; wherein, the superheat compensation amount is used to adjust the temperature data of the first cooling sub-segment. Based on the cooling intensity adjustment data of the second cooling sub-segment, the cooling intensity adjustment data of the first cooling sub-segment is processed to obtain the adjustment parameters of each optimization point within the first cooling sub-segment; wherein, the second cooling sub-segment is the preceding cooling sub-segment of the first cooling sub-segment; the processing is used to indicate that the cooling intensity adjustment data at the front end of the first cooling sub-segment is connected to the cooling intensity adjustment data at the rear end of the second cooling sub-segment. Based on the adjustment parameters of each optimization point within the first cooling sub-segment, the cooling process of the first cooling sub-segment is optimized; Based on the cooling intensity adjustment data of the second cooling sub-segment, the cooling intensity adjustment data of the first cooling sub-segment are processed to obtain the adjustment parameters for each optimization point within the first cooling sub-segment, including: Obtain the transition region of the first cooling sub-segment; wherein, the front end of the transition region of the first cooling sub-segment is the front end of the first cooling sub-segment; Based on the cooling intensity adjustment data of the first cooling sub-segment and the cooling intensity adjustment data of the second cooling sub-segment, a connection process is performed on each optimization point in the transition area to determine the adjustment parameters of each optimization point in the transition area; The method further includes: The transition region is determined based on a preset region and / or the region corresponding to the maximum temperature within the first cooling sub-segment; wherein the rear end of the transition region is in front of the region corresponding to the maximum temperature within the first cooling sub-segment.

2. The method for dynamic optimization of aluminum alloy ingot preparation process parameters as described in claim 1, characterized in that, Each cooling sub-segment to be optimized is optimized separately. Based on the temperature data of the first cooling sub-segment, the process constraint data, and the superheat compensation amount, the cooling intensity adjustment data of the first cooling sub-segment is determined, including: Each cooling sub-segment to be optimized is optimized separately, and first compensation data is obtained based on the temperature data of the first cooling sub-segment and the superheat compensation amount; wherein, the first compensation data is used to reflect the temperature after adjusting the temperature data of the first cooling sub-segment based on the superheat compensation amount; If the first compensation data exceeds the process constraint data, the cooling intensity adjustment data of the first cooling sub-segment is obtained based on the process constraint data and the first compensation data. If the first compensation data does not exceed the process constraint data, the preset cooling intensity adjustment data is used as the cooling intensity adjustment data for the first cooling sub-segment.

3. The method for dynamic optimization of aluminum alloy ingot preparation process parameters as described in claim 1, characterized in that, Each cooling sub-segment to be optimized is optimized separately. Based on the temperature data of the first cooling sub-segment, the process constraint data, and the superheat compensation amount, the cooling intensity adjustment data of the first cooling sub-segment is determined, including: Each cooling sub-segment to be optimized is optimized separately. Based on the temperature data of the first cooling sub-segment, the correction data, and the superheat compensation amount, second compensation data is obtained. The correction data is used to dynamically correct the temperature data of the first cooling sub-segment. The second compensation data reflects the temperature after the temperature data of the first cooling sub-segment is adjusted based on the correction data and the superheat compensation amount. If the second compensation data exceeds the process constraint data, the cooling intensity adjustment data of the first cooling sub-segment is obtained based on the process constraint data and the second compensation data. If the second compensation data does not exceed the process constraint data, the preset cooling intensity adjustment data is used as the cooling intensity adjustment data for the first cooling sub-segment.

4. The method for dynamic optimization of aluminum alloy ingot preparation process parameters as described in claim 1, characterized in that, The method further includes: The largest adjustment parameter among all the optimization points in the first cooling sub-segment is determined as the first parameter; For each optimization point within the transition region, if the adjustment coefficient calculated for the optimization point does not exceed the first parameter, the adjustment coefficient calculated for the optimization point shall be used as the adjustment parameter for the optimization point. For each optimization point within the transition region, if the adjustment coefficient calculated for the optimization point exceeds the first parameter, the first parameter is used as the adjustment parameter for the optimization point.

5. The method for dynamic optimization of aluminum alloy ingot preparation process parameters as described in claim 1, characterized in that, Based on cooling intensity data and process constraint data, the current liquid forming section is analyzed to identify several cooling sub-sections that need optimization, including: Obtain the initial temperature data corresponding to the current liquid forming section; Based on the cooling intensity data, a cooling calculation is performed on the initial temperature data to obtain a first temperature; If the length of the current liquid forming segment exceeds the first length, the liquid forming segment with the first temperature greater than the process constraint data is regarded as a number of cooling sub-segments to be optimized.

6. The method for dynamic optimization of aluminum alloy ingot preparation process parameters as described in claim 5, characterized in that, If the length of the current liquid forming segment exceeds the first length, the liquid forming segment with the first temperature greater than the process constraint data is designated as multiple cooling sub-segments to be optimized, including: If the length of the current liquid forming segment exceeds the first length, the liquid forming segment with the first temperature greater than the process constraint data is obtained, and the liquid forming segment with the first temperature greater than the process constraint data is determined as a plurality of cooling sub-segments to be optimized according to the first length.

7. The method for dynamic optimization of aluminum alloy ingot preparation process parameters as described in claim 5, characterized in that, The method further includes: If the length of the current liquid forming segment does not exceed the first length, the liquid forming segment with the first temperature greater than the process constraint data is regarded as the cooling sub-segment to be optimized.

8. An aluminum alloy ingot preparation device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as claimed in any one of claims 1 to 7.

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