Aluminum alloy ingot preparation process parameter dynamic optimization method and equipment

Abstract

The invention is suitable for the technical field of technological parameter optimization design, and particularly relates to an aluminum alloy ingot preparation technological parameter dynamic optimization method and device.The method comprises the steps that on the basis of cooling strength data and technological constraint data, a current liquid forming section is analyzed to obtain a plurality of to-be-optimized cooling sub-sections; based on the temperature data, the process constraint data and the superheat degree compensation amount of the first cooling sub-section, determining cooling intensity adjustment data of the first cooling sub-section; on the basis of the cooling intensity adjustment data of the second cooling sub-section, performing connection processing on the cooling intensity adjustment data of the first cooling sub-section to obtain an adjustment parameter of each optimization point in the first cooling sub-section; and optimizing the cooling process of the first cooling sub-section based on the adjustment parameter of each optimization point in the first cooling sub-section. According to the dynamic optimization method for the aluminum alloy ingot preparation process parameters, the technical problem that real-time parameter regulation and control cannot be achieved can be solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of process parameter optimization design, and particularly relates to an aluminum alloy ingot preparation process parameter dynamic optimization method and device. BACKGROUND

[0002] Aluminum alloy is obtained by adding one or more elements (such as Mg, Si, Cu, Zn, Mn, Li, etc.) to an aluminum matrix to improve strength, hardness, corrosion resistance, weldability and other properties. Compared with pure aluminum, aluminum alloy has significant improvement in strength, stiffness and durability.

[0003] In the traditional aluminum alloy ingot preparation process, the optimization parameters of the current liquid forming section are usually adjusted according to the solidification state reflected after the cooling process, resulting in a certain time between the problem learned from the solidification result and the actual change in the next stage, and real-time parameter regulation cannot be achieved. SUMMARY

[0004] The aluminum alloy ingot preparation process parameter dynamic optimization method and device provided by the embodiments of the application can solve the technical problem that in the traditional aluminum alloy ingot preparation process, the optimization parameters of the current liquid forming section are usually adjusted according to the solidification state reflected after the cooling process, resulting in a certain time between the problem learned from the solidification result and the actual change in the next stage, and real-time parameter regulation cannot be achieved.

[0005] In a first aspect, the embodiments of the application provide an aluminum alloy ingot preparation process parameter dynamic optimization method, comprising: based on cooling intensity data and process constraint data, analyzing a current liquid forming section to obtain a plurality of cooling sub-sections to be optimized; wherein the cooling intensity data is used to indicate adjustment of the cooling water flow or the action intensity of the coolant; and the process constraint data is used to reflect the safe temperature condition that the casting blank can accept; optimizing each of the cooling sub-sections to be optimized respectively, determining cooling intensity adjustment data of a first cooling sub-section based on temperature data of the first cooling sub-section, the process constraint data and a superheat compensation amount; wherein the superheat compensation amount is used to adjust the temperature data of the first cooling sub-section; based on the cooling intensity adjustment data of a second cooling sub-section, performing connection processing on the cooling intensity adjustment data of the first cooling sub-section to obtain adjustment parameters of each optimization point in the first cooling sub-section; wherein the second cooling sub-section is a previous cooling sub-section of the first cooling sub-section; and the connection processing is used to indicate that the cooling intensity adjustment data of the front end of the first cooling sub-section is connected with the cooling intensity adjustment data of the rear end of the second cooling sub-section; optimizing a cooling process of the first cooling sub-section based on the adjustment parameter of each optimization point in the first cooling sub-section.

[0006] The technical solutions described above in the embodiments of the present application have at least the following technical effects: The aluminum alloy ingot preparation process parameter dynamic optimization method provided in the present application is based on cooling intensity data and process constraint data to analyze the current liquid forming section to obtain a plurality of cooling sub-sections to be optimized. Each of the cooling sub-sections to be optimized is optimized, and the cooling intensity adjustment data of the first cooling sub-section is determined based on the temperature data, the process constraint data and the superheat compensation amount of the first cooling sub-section. The cooling intensity adjustment data of the first cooling sub-section is connected based on the cooling intensity adjustment data of the second cooling sub-section to obtain the adjustment parameter of each optimization point in the first cooling sub-section. The cooling process of the first cooling sub-section is optimized based on the adjustment parameter of each optimization point in 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 through the temperature data, the process constraint data and the superheat compensation amount of the first cooling sub-section, and then the first cooling sub-section is independently optimized, and then the first sub-section is connected based on the adjustment data of the second cooling sub-section to seamlessly match the regulation and control of the front end of the first cooling sub-section with the regulation and control of the rear end of the second cooling sub-section in the cooling optimization. The optimization parameters of the current liquid forming section do not need to be adjusted again according to the solidification state reflected after the cooling process, and real-time parameter regulation and control can be realized.

[0007] In a possible implementation manner of the first aspect, respectively optimizing each of the cooling sub-sections to be optimized, and determining the cooling intensity adjustment data of the first cooling sub-section based on the temperature data, the process constraint data and the superheat compensation amount of the first cooling sub-section, includes: respectively optimizing each of the cooling sub-sections to be optimized, and obtaining first compensation data based on the temperature data and the superheat compensation amount of the first cooling sub-section; wherein the first compensation data is used to reflect the temperature after the temperature data of the first cooling sub-section is adjusted based on the superheat compensation amount; in a case where the first compensation data exceeds the process constraint data, obtaining the cooling intensity adjustment data of the first cooling sub-section according to the process constraint data and the first compensation data; in a case where the first compensation data does not exceed the process constraint data, using preset cooling intensity adjustment data as the cooling intensity adjustment data of the first cooling sub-section.

[0008] In a possible implementation manner of the first aspect, the optimization is performed on each of the to-be-optimized cooling sub-sections respectively, and the cooling intensity adjustment data of the first cooling sub-section is determined based on the temperature data of the first cooling sub-section, the process constraint data and the superheat compensation amount, and the cooling intensity adjustment data of the first cooling sub-section comprises: The optimization is performed on each of the to-be-optimized cooling sub-sections respectively, and the second compensation data is obtained based on the temperature data of the first cooling sub-section, the correction data and the superheat compensation amount, wherein the correction data is used for dynamically correcting the temperature data of the first cooling sub-section, and the second compensation data is used for reflecting the temperature after the temperature data of the first cooling sub-section is adjusted based on the correction data and the superheat compensation amount; In a case where the second compensation data exceeds the process constraint data, the cooling intensity adjustment data of the first cooling sub-section is obtained according to the process constraint data and the second compensation data; In a case where the second compensation data does not exceed the process constraint data, preset cooling intensity adjustment data is used as the cooling intensity adjustment data of the first cooling sub-section.

[0009] In a possible implementation manner of the first aspect, the cooling intensity adjustment data of the first cooling sub-section is connected and processed based on the cooling intensity adjustment data of the second cooling sub-section, and adjustment parameters of each optimization point in the first cooling sub-section are obtained, and the adjustment parameters of each optimization point in the first cooling sub-section comprise: A transition area of the first cooling sub-section is obtained, wherein a front end of the transition area of the first cooling sub-section is a front end of the first cooling sub-section; The adjustment parameters of each optimization point in the transition area are determined by connecting and processing each optimization point in the transition area based on the cooling intensity adjustment data of the first cooling sub-section and the cooling intensity adjustment data of the second cooling sub-section.

[0010] In a possible implementation manner of the first aspect, the method further comprises: The maximum adjustment parameter among all the optimization points in the first cooling sub-section is determined as the first parameter; For each optimization point in the transition area, in a case where the calculated adjustment coefficient of the optimization point does not exceed the first parameter, the calculated adjustment coefficient of the optimization point is used as the adjustment parameter of the optimization point; For each optimization point in the transition area, in a case where the calculated adjustment coefficient of the optimization point exceeds the first parameter, the first parameter is used as the adjustment parameter of the optimization point.

[0011] In a possible implementation manner of the first aspect, the method further comprises: determine the transition region based on the preset region and / or the region corresponding to the maximum temperature in the first cooling sub-section; wherein a rear end of the transition region is in front of the region corresponding to the maximum temperature in the first cooling sub-section.

[0012] In a possible implementation manner of the first aspect, the current liquid forming section is analyzed based on the cooling intensity data and the process constraint data to obtain the plurality of cooling sub-sections to be optimized, including: obtain initial temperature data corresponding to the current liquid forming section; perform cooling calculation on the initial temperature data based on the cooling intensity data to obtain a first temperature; in a case where a length corresponding to the current liquid forming section exceeds a first length, a liquid forming section with the first temperature greater than the process constraint data is determined as the plurality of cooling sub-sections to be optimized.

[0013] In a possible implementation manner of the first aspect, in a case where a length corresponding to the current liquid forming section exceeds a first length, a liquid forming section with the first temperature greater than the process constraint data is determined as the plurality of cooling sub-sections to be optimized, including: in a case where a length corresponding to the current liquid forming section exceeds a first length, a liquid forming section with the first temperature greater than the process constraint data is obtained, and the liquid forming section with the first temperature greater than the process constraint data is determined as the plurality of cooling sub-sections to be optimized according to the first length.

[0014] In a possible implementation manner of the first aspect, the method further includes: in a case where a length corresponding to the current liquid forming section does not exceed a first length, a liquid forming section with the first temperature greater than the process constraint data is determined as a cooling sub-section to be optimized.

[0015] In a second aspect, an embodiment of the present application provides an aluminum alloy ingot preparation process parameter dynamic optimization system, which is used to implement the aluminum alloy ingot preparation process parameter dynamic optimization method in any of the first aspect, and is applied to an aluminum alloy ingot preparation device. The aluminum alloy ingot preparation process parameter dynamic optimization system includes: an analysis unit configured to analyze a current liquid forming section based on cooling intensity data and process constraint data to obtain a plurality of cooling sub-sections to be optimized; wherein the cooling intensity data is used to indicate an adjustment of cooling water flow or the intensity of a coolant; and the process constraint data is used to reflect a safe temperature condition that a cast blank can accept. The determining unit is configured to respectively optimize each of the to-be-optimized cooling sub-sections, and determine cooling intensity adjustment data of the first cooling sub-section based on temperature data of the first cooling sub-section, the process constraint data, and a superheat compensation amount; wherein the superheat compensation amount is used to adjust the temperature data of the first cooling sub-section. The generating unit is configured to perform connection processing on the cooling intensity adjustment data of the first cooling sub-section based on cooling intensity adjustment data of a second cooling sub-section, to obtain adjustment parameters of each optimization point in the first cooling sub-section; wherein the second cooling sub-section is a preceding cooling sub-section of the first cooling sub-section; and the connection processing is used to connect cooling intensity adjustment data of a front end of the first cooling sub-section with cooling intensity adjustment data of a rear end of the second cooling sub-section. The optimization unit is configured to optimize a cooling process of the first cooling sub-section based on the adjustment parameters of each optimization point in the first cooling sub-section.

[0016] In a third aspect, an embodiment of the present application provides an aluminum alloy ingot preparation process parameter dynamic optimization device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the aluminum alloy ingot preparation process parameter dynamic optimization method of any one of the first aspect when executing the computer program.

[0017] It can be understood that the beneficial effects of the second aspect to the third aspect can be referred to the related description in the first aspect, which will not be repeated here. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0019] Figure 1 is a flowchart of the aluminum alloy ingot preparation process parameter dynamic optimization method provided by an embodiment of the present application; Figure 2 is an implementation flowchart of determining cooling intensity adjustment data of a first cooling sub-section in the aluminum alloy ingot preparation process parameter dynamic optimization method provided by an embodiment of the present application; Figure 3 is a structural diagram of the aluminum alloy ingot preparation process parameter dynamic optimization system provided by an embodiment of the present application; Figure 4 is a structural diagram of the aluminum alloy ingot preparation device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0020] In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular architectures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application can be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known methods, devices, circuits, and

[0021] It will be understood that the terms "comprises" and / or "comprising," when used in this specification, include the presence of one or more features, integers, steps, operations, elements, and / or components but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0022] It is also to be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items, and that the term "at least one of' denotes one, or a plurality of, or any combination of the listed items.

[0023] As used in the description of the application and the appended claims, the term "if' can be interpreted to mean "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if a described condition or event occurs" can be interpreted to mean "upon determining," or "in response to determining" or "upon detecting," or "in response to detecting" the described condition or event, depending on the context.

[0024] In addition, the terms "first," "second," "third," etc. as used in the description and the appended claims are used only to distinguish one element from another, and do not otherwise limit any elements nor the claims. In the description of the application, the terms "one embodiment" or "some embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the application. The appearances of the phrases "in one embodiment" or "in some embodiments" in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily referring to any particular embodiment, although they can. The terms "comprise," "comprising," "include," "including," "contain," "containing," "have," "having," and the like mean "including but not limited to."

[0025] In the description of the application, the terms "one embodiment" or "some embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the application. The appearances of the phrases "in one embodiment" or "in some embodiments" in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily referring to any particular embodiment, although they can. The terms "comprise," "comprising," "include," "including," "contain," "containing," "have," "having," and the like mean "including but not limited to."

[0026] In the related art, aluminum alloy is obtained by adding one or more elements (such as Mg, Si, Cu, Zn, Mn, Li, etc.) in an aluminum matrix to improve the strength, hardness, corrosion resistance, weldability and other properties through alloying. Compared with pure aluminum, the strength, stiffness and durability of the aluminum alloy are significantly improved.

[0027] In the traditional aluminum alloy ingot preparation process, the optimization parameters of the current liquid forming section are usually adjusted according to the solidification state reflected after the cooling process, resulting in a certain time between the problem of obtaining the solidification result and the actual change in the next stage, and real-time parameter adjustment cannot be achieved. For example, the optimization parameters of the current liquid forming section are adjusted when cracks, inclusion aggregation, coarse grains or uneven distribution are detected in the subsequent solidification process. Moreover, the segmented adjustment guided by the subsequent solidification result, or the analysis and adjustment based on the data of the current liquid forming section, often ignores the connection problem between adjacent liquid forming sections at the boundary (for example, the cooling intensity of the adjacent liquid forming sections suddenly rises or falls, such as high cooling intensity at the rear end of the second cooling sub-section and low cooling intensity at the front end of the first cooling sub-section), resulting in a sudden change in the temperature field of the first cooling sub-section and the second cooling sub-section at the connection, forming a stress concentration area, causing stress difference due to sudden change of the casting blank temperature, and finally forming quality defects such as surface depression and internal micro-cracks.

[0028] To solve the above problems, the embodiments of the present application provide a dynamic optimization method and device for aluminum alloy ingot preparation process parameters.

[0029] In the method, based on the cooling intensity data and the process constraint data, a plurality of cooling sub-sections to be optimized are obtained by analyzing the current liquid forming section. Each cooling sub-section to be optimized is optimized respectively, the cooling intensity adjustment data of the first cooling sub-section is determined based on the temperature data of the first cooling sub-section, the process constraint data and the superheat compensation amount. The cooling intensity adjustment data of the first cooling sub-section is connected based on the cooling intensity adjustment data of the second cooling sub-section, and the adjustment parameters of each optimization point in the first cooling sub-section are obtained. The cooling process of the first cooling sub-section is optimized based on the adjustment parameters of each optimization point in 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 through the temperature data of the first cooling sub-section, the process constraint data and the superheat compensation amount, and then the first cooling sub-section is independently optimized, and then the first sub-section is connected based on the adjustment data of the second cooling sub-section, so that the front end of the first cooling sub-section and the rear end of the second cooling sub-section are seamlessly matched in the cooling optimization. The optimization parameters of the current liquid forming section are not adjusted according to the solidification state reflected after the cooling process, and real-time parameter adjustment can be realized.

[0030] The aluminum alloy ingot preparation process parameter dynamic optimization method provided in the embodiments of the present application can be applied to an aluminum alloy ingot preparation device, and the aluminum alloy ingot preparation device is the execution subject of the aluminum alloy ingot preparation process parameter dynamic optimization method provided in the embodiments of the present application. The embodiments of the present application do not limit the specific type of the aluminum alloy ingot preparation device.

[0031] For example, the aluminum alloy ingot preparation device can include a smelting device (such as an electric furnace / induction furnace, used for melting raw materials), a mold machine (used for primary shaping of the metal liquid of the smelting device), a water cooling machine (used for cooling the primary shaped ingot), a cutting machine (used for cutting the cooled ingot into an appropriate length), and a control device electrically connected with the smelting device, the mold machine, the water cooling machine, and the cutting machine. The control device can control the smelting device to melt the raw materials, then control the mold machine to primary shape the metal liquid of the smelting device, then control the water cooling machine to cool the primary shaped ingot, and finally control the cutting machine to cut the cooled ingot into an appropriate length to obtain the aluminum alloy ingot product.

[0032] For example, the control device can be a single-chip microcomputer, a mobile phone, a tablet computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a desktop computer, a computing device, or a computer connected to a wireless modem, a laptop computer, a handheld communication device, a handheld computing device, and the like.

[0033] In order to better understand the aluminum alloy ingot preparation process parameter dynamic optimization method provided in the embodiments of the present application, the specific implementation process of the aluminum alloy ingot preparation process parameter dynamic optimization method provided in the embodiments of the present application is exemplarily introduced below.

[0034] Figure 1 A schematic flowchart of the aluminum alloy ingot preparation process parameter dynamic optimization method provided in the embodiments of the present application is shown, and the aluminum alloy ingot preparation process parameter dynamic optimization method includes: S100, based on the cooling intensity data and the process constraint data, analyzing the current liquid forming section to obtain a plurality of cooling sub-sections to be optimized. The cooling intensity data is used to indicate the adjustment of the cooling water flow or the action intensity of the coolant. The process constraint data is used to reflect the safe temperature condition that the casting blank can accept.

[0035] It can be understood that the cooling intensity data is used to reflect the adjustable cooling capacity parameters in the cooling system. The cooling intensity data can include cooling water flow data (such as water inlet flow, water outlet flow), coolant action intensity data (such as the injection pressure of the coolant, the concentration of the coolant, etc.). The process constraint data is used to define the "safe temperature range" acceptable to the casting blank during the cooling process, and the value of the safe temperature can be determined based on the current liquid forming aluminum alloy ingot material, specification and liquid forming process parameters. The first cooling sub-section is the cooling sub-section that needs to be adjusted and optimized in the current cooling process.

[0036] For example, the initial temperature data corresponding to the current liquid forming section is obtained, the initial temperature data is cooled and calculated based on the cooling intensity data to obtain the first temperature, and the liquid forming section with the first temperature greater than the process constraint data is determined as the multiple cooling sub-sections to be optimized in the case that the length corresponding to the current liquid forming section exceeds the first length. In the case that the length corresponding to the current liquid forming section does not exceed the first length, the liquid forming section with the first temperature greater than the process constraint data is determined as the cooling sub-section to be optimized.

[0037] For example, the cooling intensity data is q=K× × =0.83 (wherein, a is the flow influence coefficient, b is the pressure influence coefficient, for example, a is 0.6, b is 0.3), the process constraint data is 650°C, the initial temperature data corresponding to the current liquid forming section is 730°C, the initial temperature data is cooled and calculated based on the cooling intensity data (i.e. 730×0.83=605.9°C), and the temperature after cooling is still greater than the process constraint data. Then, the liquid forming section (such as along the length direction) greater than the process constraint data is determined as the multiple cooling sub-sections to be optimized.

[0038] In this way, only the sub-sections that continue to overheat are optimized, and the entire liquid forming section does not need to be adjusted, thereby reducing the energy consumption and operation complexity of the cooling system, S200, each cooling sub-section to be optimized is optimized respectively, and the cooling intensity adjustment data of the first cooling sub-section is determined based on the temperature data of the first cooling sub-section, the process constraint data and the overheating degree compensation amount. Wherein, the overheating degree compensation amount is used to adjust the temperature data of the first cooling sub-section.

[0039] It can be understood that the cooling intensity adjustment data is used to indicate the cooling water flow of the water cooling machine or the action intensity of the coolant, for example, to change the water flow or the pressure.

[0040] In the conventional technology, the cooling intensity adjustment data of the first cooling sub-section is usually calculated directly according to the process constraint data and the temperature data of the first cooling sub-section. However, this method has a problem. If the temperature of the subsequent strand fluctuates, such as increases, and the temperature data of the current liquid forming section is slightly higher than the process constraint data (for example, the process constraint data is 650 DEG C, and the temperature of the current liquid forming section is 660 DEG C), the calculated cooling intensity adjustment data is 650 / 660 approximately 0.985 (only slightly enhanced cooling is required); if the temperature increases to 670 DEG C, the temperature after the cooling treatment by the cooling intensity adjustment data will still be greater than the process constraint data, that is, 670*0.985=659.95 DEG C is greater than the process constraint data of 650 DEG C. That is, the cooling intensity adjustment data of the first cooling sub-section calculated directly according to the process constraint data and the temperature data of the first cooling sub-section can only meet the condition that the temperature of the strand does not fluctuate.

[0041] To solve this problem, the temperature data of the first cooling sub-section is adjusted by the superheat compensation amount, and the calculated cooling intensity adjustment data will be less than the cooling intensity adjustment data calculated directly according to the process constraint data and the temperature data of the first cooling sub-section, that is, compared with the conventional method, when the temperature of the strand fluctuates, the temperature after the cooling treatment can also meet the requirements of the process constraint data, and a more conservative cooling intensity adjustment (more intensive cooling enhancement) is realized.

[0042] For example, the temperature data of the first cooling sub-section is modified by the superheat compensation amount to obtain the compensated temperature, and the cooling intensity adjustment data of the first cooling sub-section is determined according to the compensated temperature and the process constraint data. For example, when the process constraint data is 650 DEG C, the superheat compensation amount can be 65 DEG C (that is, 10% of the process constraint data). If the temperature data of the first cooling sub-section is 680 DEG C, the first compensation data is 680+65=745 DEG C, which is greater than the process constraint data 650 DEG C, and then 650 / 745 approximately 0.87. That is, the cooling intensity of the liquid forming section needs to be increased by 13% (by increasing the water flow (by 13% on the basis of the original) or pressure), that is, the cooling intensity adjustment data of the first cooling sub-section is determined.

[0043] In this way, if the cooling intensity is calculated directly based on the current temperature and the process constraint, the process constraint may be exceeded when the temperature of the strand fluctuates. By using the superheat compensation amount, the temperature data is offset to the "conservative target interval", which can correct the subsequent temperature fluctuation in advance, and the obtained cooling intensity adjustment data can still maintain a greater margin for the risk of over-temperature, and reduce the over-temperature or process deviation caused by temperature fluctuation.

[0044] In one possible implementation, S200, optimization is performed on each cooling sub-section to be optimized respectively, cooling intensity adjustment data of the first cooling sub-section is determined based on the temperature data, the process constraint data and the superheat compensation amount of the first cooling sub-section, including: S210, optimization is performed on each cooling sub-section to be optimized respectively, first compensation data is obtained based on the temperature data and the superheat compensation amount of the first cooling sub-section. The first compensation data is used to reflect the temperature after the temperature data of the first cooling sub-section is adjusted based on the superheat compensation amount.

[0045] It can be understood that along the direction of the movement of the casting blank, the temperature measuring device (such as an infrared temperature measuring instrument) is arranged at the inlet section (for example, 0.2 m away from the starting point of the first cooling sub-section), the middle section (for example, the midpoint of the first cooling sub-section) and the outlet section (for example, 0.2 m away from the end point of the first cooling sub-section) of the first cooling sub-section respectively, and the temperature of each optimization point is recorded. The temperature data corresponding to each optimization point in the first cooling sub-section is superimposed with the superheat compensation amount respectively, and a plurality of first compensation data is obtained, for example, the first compensation data = the superheat compensation amount + the temperature data.

[0046] It should be noted that the calculation formula of the superheat compensation amount ΔTb is ΔTb = k × (ΔTh-ΔT1), wherein k is a compensation coefficient (determined by orthogonal experiment, the value range is 0.3-0.5, the greater the thickness of the casting blank, the greater the value of k, to strengthen the sensitivity adjustment of the superheat of the thick casting blank). When the measured superheat ΔTh (for example, 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 a positive value (indicating that the cooling needs to be strengthened to offset the influence of the high superheat); when ΔTh is lower than ΔT1, ΔTb is a negative value (indicating that the cooling can be appropriately weakened).

[0047] In this way, through the superheat compensation amount, when the temperature fluctuates (such as the superheat increases), the first compensation data will be correspondingly raised, so that the temperature data deviates to the "conservative target interval", which can correct the subsequent temperature jitter in advance, thereby solving the problem of over-temperature or process deviation caused by "only judging the cooling demand according to the surface temperature data" in the traditional method.

[0048] S220, in the case that the first compensation data exceeds the process constraint data, cooling intensity adjustment data of the first cooling sub-section is obtained according to the process constraint data and the first compensation data.

[0049] It can be understood that, in the case that 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 according to the process constraint data and the first compensation data, the cooling intensity adjustment data of the first cooling sub-section for indicating the action intensity of the cooling water flow or the coolant of the water cooling machine is obtained according to the cooling intensity increase requirement (ΔQ), the heat dissipation amount of the cast blank in the first cooling sub-section and the temperature deviation. For example, ΔQ = (c × ρ × V × ΔT) ÷ (S × t × η), wherein c is the specific heat capacity of the aluminum alloy, ρ is the density of the aluminum alloy, V is the volume of the cast blank in the first cooling sub-section, ΔT is the temperature difference between the first compensation data and the process constraint data, S is the effective contact area of the cooling system and the cast blank (determined by the number of nozzles, the spraying angle and the coverage range), t is the residence time of the cast blank in the first cooling sub-section (sub-section length ÷ liquid forming speed), and η is the thermal efficiency of the cooling system (0.85). For example, the process constraint data is 580℃, the first compensation data is 596℃, the temperature deviation ΔT is 16℃, the aluminum alloy is a square ingot, the cross section is 300mm × 500mm, the sub-section length is 2m, and the liquid forming speed is 2.2m / min. Then V = 2m × 0.3m × 0.5m = 0.3m³, S = 2m × (0.3m + 0.5m) × 0.8 (spraying 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 2.0m³ / h + 0.42m³ / h = 2.42m³ / h, that is, the cooling intensity adjustment data reflects that the current flow 2.0m³ is adjusted to 2.42m³ / h.

[0050] In this way, if the cooling intensity is directly calculated based on the current temperature and the process constraint, the process constraint may be exceeded when the temperature of the cast blank fluctuates. By offsetting the temperature data to the "conservative target interval" through the superheat compensation amount, the subsequent temperature jitter can be pre-corrected, and the cooling intensity adjustment data obtained can still maintain a greater margin for the risk of over-temperature, thereby reducing the over-temperature or process deviation caused by temperature fluctuations.

[0051] S230, in the case that 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 of the first cooling sub-section.

[0052] It can be understood that the preset cooling intensity adjustment data refers to a standardized cooling parameter scheme pre-set based on historical production data, process experimental results and the solidification characteristics of the cast blank, and the core role is to maintain the stability and continuity of the cooling process when the temperature of the cast blank is in a safe range, thereby avoiding temperature fluctuations caused by frequent adjustments.

[0053] 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.

[0054] 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.

[0055] 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: 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.

[0056] 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.

[0057] 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.

[0058] 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.

[0059] S250, in a case where the second compensation data exceeds the process constraint data, obtaining cooling intensity adjustment data of the first cooling sub-section according to the process constraint data and the second compensation data.

[0060] It can be understood that, in a case where the second compensation data exceeds the process constraint data, a temperature difference between the second compensation data and the process constraint data can be obtained according to the process constraint data and the second compensation data, and the cooling intensity adjustment data of the second cooling sub-section for indicating the action intensity of the cooling water flow or the coolant of the water cooling machine is obtained according to the cooling intensity requirement (ΔQ) and the heat dissipation amount and temperature deviation of the casting blank in the second cooling sub-section.

[0061] In this way, by offsetting the temperature data to the “conservative target interval” through the superheat compensation amount, the subsequent temperature jitter can be pre-corrected, and the obtained cooling intensity adjustment data can still maintain greater margin for the over-temperature risk, and reduce the over-temperature or process deviation caused by temperature fluctuation, environmental influence and equipment aging.

[0062] S260, in a case where the second compensation data does not exceed the process constraint data, adopting preset cooling intensity adjustment data as the cooling intensity adjustment data of the first cooling sub-section.

[0063] For example, the system automatically compares all the second compensation data (inlet, middle and outlet) of the second cooling sub-section with the process constraint data, confirms that all the optimized point temperatures are in the safe range, and that the condition is met for 3 consecutive sampling periods (0.5 seconds per period), and then determines that the second compensation data does not exceed the process constraint data, so that the preset cooling intensity adjustment data can be adopted as the cooling intensity adjustment data of the second cooling sub-section.

[0064] In this way, the stability and continuity of the cooling process can be maintained when the casting blank temperature is in the safe range, and temperature fluctuation caused by frequent adjustment can be avoided.

[0065] S300, based on the cooling intensity adjustment data of the second cooling sub-section, performing connection processing on the cooling intensity adjustment data of the first cooling sub-section to obtain adjustment parameters of each optimized point in the first cooling sub-section. The second cooling sub-section is the cooling sub-section directly in front of the first cooling sub-section in the preparation direction. The connection processing is used to connect the cooling intensity adjustment data of the front end of the first cooling sub-section with the cooling intensity adjustment data of the rear end of the second cooling sub-section.

[0066] It can be understood that the second cooling sub-section is the cooling sub-section directly in front of the first cooling sub-section in the preparation direction, through which the casting blank passes first, that is, the casting blank flows out of the second cooling sub-section and directly enters the first cooling sub-section.

[0067] In the conventional technology, the analysis and adjustment are made based on the data of the current liquid forming section, and the connection problem at the boundary between adjacent liquid forming sections is often ignored. For example, the cooling intensity adjustment data of the second cooling sub-section is 0.5, and the cooling intensity adjustment data of the first cooling sub-section is 0.87, which causes the cooling intensity of the adjacent liquid forming sections to suddenly increase or decrease (for example, the cooling intensity at the rear end of the second cooling sub-section is high, and the cooling intensity at the front end of the first cooling sub-section is low), resulting in a sudden change of the temperature field of the first cooling sub-section and the second cooling sub-section at the connection position, forming a stress concentration area, causing a stress difference due to the sudden change of the temperature of the casting blank, and finally forming quality defects such as surface depression and internal micro-cracks.

[0068] For example, the second cooling sub-section S2 is the previous section, and the first cooling sub-section S1 is the current section. The connection position is between the end point of S2 and the start point of S1. The purpose is to perform connection processing on the front several points of S1 without changing the data of S2, so that there is no obvious jump at the connection position of the two sections. For example, the first cooling sub-section is 1 meter long, and 5 optimization points are divided at the start point of S1 at an interval of 0.2 meters. The cooling intensity adjustment data of the second cooling sub-section is processed by a fixed difference value to obtain the adjustment parameters of each optimization point in the first cooling sub-section. For example, the cooling intensity adjustment data of the second cooling sub-section is 0.5, the fixed difference value is 0.074, the first optimization point in the first cooling sub-section 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 at the connection position between the end point of S2 and the start point of S1.

[0069] In this way, the cooling effect of adjacent sub-sections is "seamless relay", which not only guarantees the cooling demand of the current sub-section, but also inherits the thermal state of the previous sub-section. Therefore, it is not necessary to rely on the solidification state reflected after the cooling process to adjust the optimization parameters of the current liquid forming section, and real-time parameter regulation can be realized.

[0070] In a possible implementation, S300, 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 the adjustment parameters of each optimization point in the first cooling sub-section, including: S310, obtaining the transition region of the first cooling sub-section. The front end of the transition region of the first cooling sub-section is the front end of the first cooling sub-section.

[0071] It can be understood that the instantaneous position of the casting blank just entering the first cooling sub-section after flowing out of the second cooling sub-section is the front end of the transition region. The position where the temperature field enters a relatively stable state or the temperature gradient is obviously reduced is the rear end of the transition region.

[0072] 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).

[0073] 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.

[0074] 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.

[0075] 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).

[0076] In this way, the adjustment data of the second cooling sub-section can be used to link the first sub-section, so that the front end of the first cooling sub-section and the rear end of the second cooling sub-section are seamlessly matched in cooling optimization, the cooling strength mutation is eliminated, and the optimization parameters of the current liquid forming section are not adjusted again according to the solidification state reflected after the cooling process, thereby realizing real-time parameter regulation.

[0077] S400, optimizing the cooling process of the first cooling sub-section based on the adjustment parameters of each optimization point in the first cooling sub-section.

[0078] It can be understood that the "nozzle group" is divided in the length direction of the cast blank (for example, 1 group of nozzles corresponds to every 0.2 meters, including nozzles in the upper, lower and side directions), and the physical position of each optimization point (for example, 0.2 meters from the front end of the first sub-section) needs to be bound with the corresponding "nozzle group number" - for example, the optimization point P1 (front end) of the first sub-section corresponds to the "3rd nozzle group" of the secondary cooling zone. The optimization point P2 (0.2 meters from the front end) corresponds to the "4th nozzle group", and so on, so that the cooling demand of each optimization point is executed by the dedicated nozzle group to avoid "cross-region interference". The adjustment parameters of each optimization point in the first cooling sub-section are converted into corresponding water flow rate instructions (for example, the adjustment parameter 0.87 corresponds to the water flow rate 2.5 m³ / h), and output to the controller of the nozzle group to complete real-time adjustment.

[0079] In this way, the optimization parameters of the current liquid forming section are not adjusted again according to the solidification state reflected after the cooling process, thereby realizing real-time parameter regulation.

[0080] In one possible implementation, the aluminum alloy ingot preparation process parameter dynamic optimization method further includes: S500, obtaining a first parameter according to the cooling intensity data and the real-time temperature of each optimization point. The first parameter is the maximum adjustment parameter.

[0081] It can be understood that the maximum adjustment parameter of all optimization points in the first cooling sub-section is determined as the first parameter.

[0082] S600, for each optimization point in the transition region, if the optimization point calculation obtained adjustment coefficient does not exceed the first parameter, the optimization point calculation obtained adjustment coefficient is used as the adjustment parameter of the optimization point.

[0083] It can be understood that the optimization point calculation obtained adjustment coefficient can be obtained according to step S320, for each optimization point in the transition region, if the optimization point calculation obtained adjustment coefficient does not exceed the first parameter, the optimization point calculation obtained adjustment coefficient is used as the adjustment parameter of the optimization point.

[0084] Scenario 1: Real-time temperature of individual optimization points may be affected by sensor fluctuations (such as infrared thermometer interference by water vapor) or workpiece surface scale, resulting in "false high temperature", causing the calculated adjustment coefficient to be too large (non-real demand). If this abnormal value is directly used, it will cause unnecessary overcooling, and at the same time, it may exceed the process safety upper limit of the entire first cooling sub-section, destroy the change gradient of cooling intensity, and cause the temperature to appear "local jump".

[0085] In this way, by setting the upper limit of the adjustment parameter of the transition area as the first parameter, it is avoided that some points produce excessive adjustment due to abnormal calculation results. If individual points are allowed to adjust according to their own calculation values, it may exceed the process safety upper limit of the entire first cooling sub-section, destroy the change gradient of cooling intensity, and cause the temperature to appear "local jump".

[0086] S700, for each optimization point in the transition area, if the adjustment coefficient calculated by the optimization point exceeds the first parameter, the first parameter is used as the adjustment parameter of the optimization point.

[0087] It can be understood that the adjustment coefficient calculated by the optimization point can be obtained according to step S320. For each optimization point in the transition area, if the adjustment coefficient calculated by the optimization point exceeds the first parameter, the first parameter is used as the adjustment parameter of the optimization point.

[0088] In this way, by setting the upper limit of the adjustment parameter of the transition area as the first parameter, it is avoided that some points produce excessive adjustment due to abnormal calculation results. If individual points are allowed to adjust according to their own calculation values, it may exceed the process safety upper limit of the entire first cooling sub-section, destroy the change gradient of cooling intensity, and cause the temperature to appear "local jump".

[0089] In one possible implementation, the aluminum alloy ingot preparation process parameter dynamic optimization method further includes: The transition area is determined based on the preset area and / or the area corresponding to the maximum temperature in the first cooling sub-section. The rear end of the transition area is in front of the area corresponding to the maximum temperature in the first cooling sub-section.

[0090] It can be understood that the area where the maximum temperature falls or the front end position of the maximum temperature area can be found, and then the rear end of the transition area is set at this position. The front end of the first cooling sub-section can also be found, and the rear end of the transition area is found according to the preset area. For example, the transition area can be set as a range of 10% of the length of the front end of the first cooling sub-section.

[0091] In this way, the transition area ends at the front of the maximum temperature area, leaving a buffer time for subsequent switching, reducing the risk of exceeding the limit, and providing enough warm / cooling space to respond to disturbances when the transition is performed.

[0092] In a possible implementation, S100, based on the cooling intensity data and the process constraint data, the current liquid forming section is analyzed to obtain a plurality of cooling sub-sections to be optimized, including: S110, obtaining initial temperature data corresponding to the current liquid forming section.

[0093] It can be understood that a temperature sensor (such as a surface thermocouple, a non-contact infrared sensor, etc.) is installed at the entrance of the current section where the casting blank enters, to obtain the initial temperature data corresponding to the current liquid forming section.

[0094] S120, performing cooling calculation on the initial temperature data based on the cooling intensity data to obtain a first temperature.

[0095] It can be understood that the initial temperature data is first pre-calculated according to the cooling intensity data, for example, the temperature of the ingot after cooling at the current cooling intensity data can be determined according to the cooling medium flow (m³ / h), flow rate (m / s), pressure (kPa) in the cooling intensity data and the initial temperature data. For example, the first temperature = initial temperature data - (unit area heat dissipation power × area × cooling time) ÷ mass of the casting blank ÷ specific heat capacity of the casting blank material, wherein the unit area heat dissipation power is determined according to the cooling intensity data.

[0096] In this way, a quantitative basis can be provided for subsequent parameter adjustment.

[0097] S130, in a case where the length corresponding to the current liquid forming section exceeds a first length, the liquid forming section with the first temperature greater than the process constraint data is taken as a plurality of cooling sub-sections to be optimized.

[0098] It can be understood that in a case where the length corresponding to the current liquid forming section exceeds the first length, the splitting step is entered, and not the entire liquid forming section needs to be split, only the local area with temperature exceeding the standard can be taken as a plurality of cooling sub-sections to be optimized.

[0099] In this way, the “cooling sub-sections to be optimized” after splitting can not only accurately focus on the problem area of temperature exceeding the standard, but also can ensure that the cooling parameters (such as water quantity, air speed) of each sub-section can be independently optimized through “length control”, avoiding the failure of local temperature control due to the length of the sub-section being too long.

[0100] In a possible implementation, S130, in a case where the length corresponding to the current liquid forming section exceeds a first length, the liquid forming section with the first temperature greater than the process constraint data is taken as a plurality of cooling sub-sections to be optimized, including: In a case where the length corresponding to the current liquid forming section exceeds the first length, the liquid forming section with the first temperature greater than the process constraint data is obtained, and the liquid forming section with the first temperature greater than the process constraint data is determined as a plurality of cooling sub-sections according to the first length.

[0101] It can be understood that, in a case where the length corresponding to the current liquid forming section exceeds the first length, a continuous region with temperature exceeding the standard is found from the "current liquid forming section", and the continuous region with temperature exceeding the standard is split into a plurality of cooling sub-sections based on the "first length".

[0102] In this way, the over-temperature problem can be accurately controlled, and excessive cooling of the temperature qualified region can be avoided.

[0103] In a possible implementation, the aluminum alloy ingot preparation process parameter dynamic optimization method further includes: In a case where the length corresponding to the current liquid forming section does not exceed the first length, the liquid forming section with the first temperature greater than the process constraint data is taken as a cooling sub-section to be optimized.

[0104] It can be understood that, in a case where the length corresponding to the current liquid forming section does not exceed the first length, the continuous region with temperature exceeding the standard can not be split into a plurality of cooling sub-sections, but the liquid forming section with the first temperature greater than the process constraint data is directly taken as a cooling sub-section to be optimized.

[0105] In this way, a quantitative basis can be provided for subsequent parameter adjustment.

[0106] It should be understood that the size of the serial number of each step in the above embodiments does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0107] Corresponding to the aluminum alloy ingot preparation process parameter dynamic optimization method described in the above embodiments, the embodiments of the present application also provide an aluminum alloy ingot preparation process parameter dynamic optimization system. Each unit of the system can implement each step of the aluminum alloy ingot preparation process parameter dynamic optimization method. Figure 3 The structural block diagram of the aluminum alloy ingot preparation process parameter dynamic optimization system provided by the embodiments of the present application is shown, and only the parts related to the embodiments of the present application are shown for ease of illustration.

[0108] Referring to Figure 3 , the aluminum alloy ingot preparation process parameter dynamic optimization system includes: 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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 device 6 of this embodiment includes at least one processor 60 (only one is shown in the figure), Figure 4 at least one memory 61 (only one is shown in the figure), Figure 4 and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60, wherein the processor 60 executes the computer program 62 to enable the aluminum alloy ingot preparation device 6 to implement the steps in any of the above-described various embodiments of the aluminum alloy ingot preparation process parameter dynamic optimization method, or to enable the aluminum alloy ingot preparation device 6 to implement the functions of the units in the above-described various system embodiments.

[0115] By way of example, the computer program 62 can be divided into one or more units, which are stored in the memory 61 and executed by the processor 60 to complete the present application. The one or more units can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program 62 in the aluminum alloy ingot preparation device 6.

[0116] The aluminum alloy ingot preparation device 6 can include a melting device (such as an electric furnace / induction furnace for melting raw materials), a mold machine (for primary shaping of the molten metal liquid of the melting device), a water cooling machine (for cooling the primary shaped ingot), a cutting machine (for cutting the cooled ingot into appropriate lengths), and a control device electrically connected to the melting device, the mold machine, the water cooling machine, and the cutting machine. The control device can control the melting device to melt the raw materials, then control the mold machine to primary shape the molten metal liquid of the melting device, then control the water cooling machine to cool the primary 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 device 6 can include, but is not limited to, the processor 60, the memory 61. Those skilled in the art can understand that Figure 4 The aluminum alloy ingot preparation device 6 is merely an example and does not constitute a limitation on the aluminum alloy ingot preparation device 6, and can include more or fewer components than shown, or combine certain components, or different components, for example, can also include input / output devices, network access devices, buses, etc.

[0117] The processor 60 can be a central processing unit (CPU), and can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0118] The memory 61 can be an internal storage unit of the aluminum alloy ingot preparation device 6 in some embodiments, for example, a hard disk or a memory of the aluminum alloy ingot preparation device 6. The memory 61 can also be an external storage device of the aluminum alloy ingot preparation device 6 in other embodiments, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 61 can include both the internal storage unit and the external storage device of the aluminum alloy ingot preparation device 6. The memory 61 is used to store an operating system, an application program, a boot loader, data, and other programs, for example, program codes of the computer program, etc. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0119] The embodiments of the present application further provide a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the steps in any of the above method embodiments.

[0120] The embodiments of the present application provide a computer program product. When the computer program product is run on the aluminum alloy ingot preparation device, the aluminum alloy ingot preparation device implements the steps in any of the above method embodiments.

[0121] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the present application can implement all or part of the processes in the above-mentioned embodiment methods through a computer program to instruct relevant hardware to complete, and the computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of each method embodiment described above can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms. The computer readable medium at least includes any entity or device capable of carrying the computer program code to the aluminum alloy ingot preparation equipment, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium. For example, U disk, mobile hard disk, magnetic disk or optical disk, etc.

[0122] In the above embodiments, the description of each embodiment has its own focus, and the parts not described or recorded in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0123] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in connection with the embodiments disclosed herein can be realized by electronic hardware, or a combination of computer software and electronic hardware. Whether the functions are performed 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 the present application.

[0124] In the embodiments provided in the present 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 above-described aluminum alloy ingot preparation equipment, aluminum alloy ingot preparation process parameter dynamic optimization system embodiments are only illustrative, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0125] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may also be distributed to multiple network units. Part or all of the units can be selected to achieve the purpose of the embodiment scheme according to actual needs.

[0126] The above embodiments are only used to illustrate the technical solutions of the present application, but not limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present 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.

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, 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.

5. The method for dynamic optimization of aluminum alloy ingot preparation process parameters as described in claim 4, 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.

6. The method for dynamic optimization of aluminum alloy ingot preparation process parameters as described in claim 4, characterized in that, 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.

7. 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.

8. The method for dynamic optimization of aluminum alloy ingot preparation process parameters as described in claim 7, 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.

9. The method for dynamic optimization of aluminum alloy ingot preparation process parameters as described in claim 7, 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.

10. 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 9.

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