Self-adaptive optimization method and equipment for low-pressure casting pressure curve of ball valve body

Abstract

The invention is suitable for the technical field of parameter optimization, and particularly relates to a ball valve body low-pressure casting pressure curve self-adaptive optimization method and device, and the method comprises the steps: obtaining condensation data corresponding to a valve body main bearing structure region in a first low-pressure casting stage and a hot spot gradient distribution characteristic in a second low-pressure casting stage; composite structure data associated with the main force bearing structure area of the valve body is determined; determining a space mapping relation according to the condensation missing data, the hot spot gradient distribution characteristics and the composite structure data; determining liquid feeding data of the transition area of the composite structure based on the expansion characteristic of the valve body; phase change pressure data is constructed according to the casting process through the pressure-bearing sealing performance of the valve body and the viscosity-temperature characteristics of molten metal; determining optimization data based on the space mapping relation, the liquid feeding data and the phase change pressure data; according to the self-adaptive optimization method for the low-pressure casting pressure curve of the ball valve body, the problems of splashing gas entrapment caused by high pressure of a thin-wall area and shrinkage porosity caused by low pressure of a thick-wall area are reduced.

Description

Technical Field

[0001] This application belongs to the field of parameter optimization technology, and in particular relates to an adaptive optimization method and equipment for the low-pressure casting pressure curve of a ball valve body. Background Technology

[0002] A ball valve is a type of valve with a ball as its core opening and closing element. It is mainly used to control the on / off state or flow regulation of fluids (such as liquids, gases, and slurries) in pipelines. The valve body is the core pressure-bearing component of the ball valve. As the outer shell housing the ball, seat, sealing components, and other internal structures, its design determines the valve's sealing performance and pressure-bearing capacity. The valve body is typically cast using low-pressure casting technology. The core of low-pressure casting is to use low-pressure gas to force molten metal from a holding furnace into the mold cavity through a riser pipe, maintaining pressure until the molten metal completely solidifies to obtain the casting.

[0003] Low-pressure casting in related technologies only uses overall pressure curve control, which means that when setting parameters, the fixed overall pressure curve can only be used to select parameters at a compromise. This results in the thin-walled area causing splashing and air entrapment due to excessive pressure, or the thick-walled area causing shrinkage and porosity due to insufficient pressure, leading to low reliability of the ball valve. Summary of the Invention

[0004] This application provides an adaptive optimization method and device for the pressure curve of a ball valve body in low-pressure casting, which can solve the problems of splashing and air entrapment in thin-walled areas due to excessive pressure or shrinkage in thick-walled areas due to insufficient pressure caused by a fixed pressure curve.

[0005] In a first aspect, embodiments of this application provide an adaptive optimization method for the low-pressure casting pressure curve of a ball valve body, including: Acquire solidification defect data corresponding to the main load-bearing structural area of ​​the valve body in the first low-pressure casting stage and thermal gradient distribution characteristics in the second low-pressure casting stage; wherein, the solidification defect data includes pressure spectrum and solidification defect spectrum, and the thermal gradient distribution characteristics are used to reflect the distribution of the temperature change rate of the valve body during solidification. Determine composite structure data that is associated with the main load-bearing structural region of the valve body; wherein, the composite structure data is used to reflect the morphology of the composite structure transition region, the composite structure transition region including the flange flow channel intersection and the valve stem mounting boss; The spatial mapping relationship is determined based on the congealing defect data, the thermal gradient distribution characteristics, and the composite structure data; wherein, the spatial mapping relationship is used to indicate the correspondence between the defect concentration area and the transition area of ​​the composite structure; The liquid compensation data of the transition region of the composite structure is determined based on the expansion characteristics of the valve body; wherein, the liquid compensation data includes the pulse pressure increase parameters of the thin-walled junction region at the flange flow channel intersection and the pressure holding strength parameters of the thick-walled boss region of the valve stem mounting boss; The phase change pressure data is constructed based on the valve body's pressure-bearing and sealing performance and the viscosity-temperature characteristics of the molten metal, and according to the casting process. The phase change pressure data is used to indicate the dynamic pressure threshold before the valve body solidifies. The casting process includes a pressure-increasing process, a crystallization process, and a pressure-reducing process. Optimized data is determined based on the spatial mapping relationship, the liquid feeding data, and the phase change pressure data; wherein, the optimized data is used to indicate the optimized low-pressure casting pressure curve of the valve body.

[0006] The adaptive optimization method for the low-pressure casting pressure curve of the ball valve body provided in this application obtains the solidification defect data corresponding to the main load-bearing structural region of the valve body in the first low-pressure casting stage and the thermal gradient distribution characteristics in the second low-pressure casting stage. This method can improve the accuracy of defect identification for the main load-bearing structural region of the valve body during the casting process. By determining the composite structural data associated with the main load-bearing structural region of the valve body, the structural characteristics of the valve body during the casting process can be more accurately reflected. Determining the composite structural data associated with the main load-bearing structural region of the valve body, and establishing spatial mapping relationships based on the solidification defect data, thermal gradient distribution characteristics, and composite structural data, provides a foundation for determining subsequent liquid feeding and phase change pressure data. Based on the expansion characteristics of the valve body, liquid feeding data for the transition region of the composite structure is determined. By analyzing the pressure-bearing and sealing performance of the valve body and the viscosity-temperature characteristics of the molten metal, and constructing phase change pressure data based on the casting process, optimization data is determined based on spatial mapping relationships, liquid feeding data, and phase change pressure data. This can improve the control of local areas during the casting process, avoid defects caused by fixed pressure curves in traditional low-pressure casting methods, and effectively reduce the splashing and air entrapment problems caused by excessive pressure in thin-walled areas and the shrinkage porosity problems caused by insufficient pressure in thick-walled areas, thereby improving the casting quality and reliability of the ball valve body.

[0007] Secondly, embodiments of this application provide an adaptive optimization system for the low-pressure casting pressure curve of a ball valve body, comprising: The acquisition unit is used to acquire solidification defect data corresponding to the main load-bearing structural area of ​​the valve body in the first low-pressure casting stage and thermal gradient distribution characteristics in the second low-pressure casting stage; wherein, the solidification defect data includes a pressure spectrum and a solidification defect spectrum, and the thermal gradient distribution characteristics are used to reflect the distribution of the temperature change rate of the valve body during the solidification process. The first determining unit is used to determine composite structure data associated with the main load-bearing structural region of the valve body; wherein, the composite structure data is used to reflect the morphology of the composite structure transition region, and the composite structure transition region includes the flange flow channel intersection and the valve stem mounting boss; The second determining unit is used to determine a spatial mapping relationship based on the consolidation defect data, the thermal node gradient distribution characteristics, and the composite structure data; wherein the spatial mapping relationship is used to indicate the correspondence between the defect concentration area and the transition area of ​​the composite structure; The third determining unit is used to determine the liquid compensation data of the transition region of the composite structure based on the expansion characteristics of the valve body; wherein, the liquid compensation data includes the pulse pressure increase parameters of the thin-walled junction region at the flange flow channel intersection and the pressure holding strength parameters of the thick-walled boss region of the valve stem mounting boss; A construction unit is used to construct phase change pressure data based on the valve body's pressure-bearing and sealing performance and the viscosity-temperature characteristics of molten metal, and according to the casting process; wherein, the phase change pressure data is used to indicate the dynamic pressure threshold before the valve body solidifies, and the casting process includes a pressurization process, a crystallization process, and a depressurization process; The result unit is used to determine optimized data based on the spatial mapping relationship, the liquid feeding data, and the phase change pressure data; wherein the optimized data is used to indicate the optimized low-pressure casting pressure curve of the valve body.

[0008] Thirdly, embodiments of this application provide an adaptive optimization device for the low-pressure casting pressure curve of a ball valve body, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the method described in any of the first aspects above.

[0009] Fourthly, embodiments of this application provide a computer program product that, when running on a ball valve body low-pressure casting pressure curve adaptive optimization device, causes the ball valve body low-pressure casting pressure curve adaptive optimization device to execute the ball valve body low-pressure casting pressure curve adaptive optimization method described in any of the first aspects above.

[0010] It is understood that the beneficial effects of the second to fourth 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

[0011] 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.

[0012] Figure 1 This is a schematic diagram of the overall structure of a ball valve provided in one embodiment of this application; Figure 2 This is a cross-sectional view of a ball valve provided in an embodiment of this application; Figure 3 This is a flowchart illustrating an adaptive optimization method for the low-pressure casting pressure curve of a ball valve body provided in an embodiment of this application. Figure 4 This is a schematic diagram of the implementation process of step S300 in the adaptive optimization method for low-pressure casting pressure curve of ball valve body provided in an embodiment of this application; Figure 5 This is a schematic diagram of the implementation process of step S400 in the adaptive optimization method for low-pressure casting pressure curve of ball valve body provided in an embodiment of this application; Figure 6 This is a schematic diagram of another implementation process of step S400 in the adaptive optimization method for low-pressure casting pressure curve of ball valve body provided in an embodiment of this application; Figure 7 This is a schematic diagram of the implementation process of step S500 in the adaptive optimization method for low-pressure casting pressure curve of ball valve body provided in an embodiment of this application; Figure 8 This is a schematic diagram of the implementation process of step S600 in the adaptive optimization method for low-pressure casting pressure curve of ball valve body provided in an embodiment of this application; Figure 9 This is a schematic diagram of the adaptive optimization system for the low-pressure casting pressure curve of the ball valve body provided in the embodiments of this application; Figure 10 This is a schematic diagram of the structure of the adaptive optimization device for the low-pressure casting pressure curve of the ball valve body provided in the embodiments of this application.

[0013] The following are the labeling elements in the figure: 100. Ball valve; 10. Valve body; 20. Handwheel; 30. Limit block; 40. Bolt; 50. Fixed housing; 60. Threaded rod; 11. Connecting hole. Detailed Implementation

[0014] 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.

[0015] 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.

[0016] 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.

[0017] 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 detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0018] 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.

[0019] 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.

[0020] Currently, the industry generally uses low-pressure casting to produce ball valve bodies. This process involves introducing low-pressure gas (0.02-0.15MPa) into a sealed molten metal furnace to promote the smooth filling of the mold. Compared with traditional gravity casting, it can significantly reduce defects such as air entrapment and incomplete filling, making it the mainstream technology for valve body casting. However, in long-term production practice, the R&D team found that the low-pressure casting process has always been unable to overcome the bottleneck of high defect rates in key areas of the valve body. The root cause of this problem is mainly due to the fixed overall pressure curve control.

[0021] Low-pressure casting technology is mainly used for castings with simple structures (such as aluminum alloy wheels and small pipe fittings). These castings have uniform wall thickness and no obvious "hot spots" (i.e., thick-walled parts with slow heat dissipation and long solidification time). Therefore, technicians have developed a "holistic pressure control" approach. For a specific valve body specification, a fixed "time-pressure" curve is set, covering the entire process from "molten metal lifting (from furnace to mold) → filling the mold cavity → holding pressure (compensating for solidification shrinkage) → depressurizing (mold opening and part removal)". There are two main reasons for adopting this approach: First, the control system of early low-pressure casting machines had low precision and only supported single pressure timing output, making it impossible to achieve "regional, dynamic pressure adjustment"; second, the overall pressure curve is easy to debug. Technicians only need to go through one or two rounds of trial and error to find a parameter that can roughly adapt to most areas, and then mass production can begin without investing time in analyzing the structural differences of the valve body. This method works reasonably well when dealing with simple castings, but when applied to ball valve bodies with complex structures, the contradictions begin to emerge. Because the ball valve body is not a uniform wall thickness part, when setting parameters, the fixed overall pressure curve can only be used to select parameters at a compromise. This can easily lead to the thin-walled area causing splashing and air entrapment due to excessive pressure, or the thick-walled area causing shrinkage and porosity due to insufficient pressure, resulting in low reliability of the ball valve.

[0022] To address the aforementioned issues, this application provides an adaptive optimization method and device for the low-pressure casting pressure curve of a ball valve body.

[0023] In this method, the adaptive optimization method for the low-pressure casting pressure curve of the ball valve body provided in this application obtains the solidification defect data corresponding to the main load-bearing structural region of the valve body in the first low-pressure casting stage and the thermal gradient distribution characteristics in the second low-pressure casting stage. This can improve the defect identification accuracy for the main load-bearing structural region of the valve body during the casting process. By determining the composite structural data associated with the main load-bearing structural region of the valve body, the structural characteristics of the valve body during the casting process can be reflected more accurately. Determining the composite structural data associated with the main load-bearing structural region of the valve body, and determining the spatial mapping relationship based on the solidification defect data, thermal gradient distribution characteristics, and composite structural data, can provide a foundation for the subsequent determination of liquid feeding and phase change pressure data. Based on the expansion characteristics of the valve body, liquid feeding data for the transition region of the composite structure is determined. By analyzing the pressure-bearing and sealing performance of the valve body and the viscosity-temperature characteristics of the molten metal, and constructing phase change pressure data based on the casting process, optimization data is determined based on spatial mapping relationships, liquid feeding data, and phase change pressure data. This can improve the control of local areas during the casting process, avoid defects caused by fixed pressure curves in traditional low-pressure casting methods, and effectively avoid splashing and air entrapment problems caused by excessive pressure in thin-walled areas and shrinkage porosity problems caused by insufficient pressure in thick-walled areas, thereby improving the casting quality and reliability of the ball valve body.

[0024] The adaptive optimization method for the low-pressure casting pressure curve of the ball valve body provided in this application embodiment can be applied to the adaptive optimization device for the low-pressure casting pressure curve of the ball valve body. In this case, the adaptive optimization device for the low-pressure casting pressure curve of the ball valve body is the executing subject of the adaptive optimization method for the low-pressure casting pressure curve of the ball valve body provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of the adaptive optimization device for the low-pressure casting pressure curve of the ball valve body.

[0025] For example, Figure 1 The overall structure diagram of the ball valve is shown. Figure 2 A cross-sectional view of a ball valve is shown. The ball valve 100 includes a valve body 10, a handwheel 20, a limiting block 30, a bolt 40, a fixed housing 50, a threaded rod 60, and a connecting hole 11. The valve body 10 is the main body of the ball valve 100 and has a specific internal flow channel for controlling the flow path. The threaded rod 60 is connected to the handwheel 20; the threaded rod 60 passes through the central hole of the fixed housing 50, and the limiting block 30 is fitted (or snap-fitted) onto the middle of the threaded rod 60, forming a circumferential limiting fit with the inner wall of the fixed housing 50, restricting the circumferential rotation of the threaded rod 60 and allowing only axial movement; rotation of the handwheel 20 directly drives the threaded rod 60 to rotate; the threaded rod 60 is connected to the valve body 10, and rotating the handwheel 20 can drive the valve core inside the valve body to move, thereby changing the flow path's on / off state. The limiting block 30 is provided on the valve body 10 to limit the rotation angle of the handwheel 20 and prevent damage from excessive rotation. Bolt 40 is used to securely install the ball valve 100 onto a pipeline or other equipment, ensuring the stability and reliability of the ball valve. Connection hole 11 is provided on the valve body 10 for connecting to other pipelines or components to achieve fluid transmission and control. The ball valve body low-pressure casting pressure curve adaptive optimization device communicates with the casting equipment; the ball valve body low-pressure casting pressure curve adaptive optimization device can be a terminal such as a tablet computer, laptop computer, netbook, desktop computer, smart screen, smart TV, computer, laptop computer, or handheld computing device.

[0026] To better understand the adaptive optimization method for the low-pressure casting pressure curve of the ball valve body provided in this application embodiment, the specific implementation process of the adaptive optimization method for the low-pressure casting pressure curve of the ball valve body provided in this application embodiment will be described by way of example below.

[0027] Figure 3 This paper presents a schematic flowchart of an adaptive optimization method for the low-pressure casting pressure curve of a ball valve body provided in an embodiment of this application. The adaptive optimization method for the low-pressure casting pressure curve of a ball valve body includes: S100, acquire solidification defect data corresponding to the main load-bearing structural area of ​​the valve body in the first low-pressure casting stage and thermal gradient distribution characteristics in the second low-pressure casting stage; wherein, solidification defect data includes pressure spectrum and solidification defect spectrum, and thermal gradient distribution characteristics are used to reflect the distribution of temperature change rate of valve body during solidification.

[0028] It can be understood that the first low-pressure casting stage refers to the stage where molten metal fills into the main load-bearing structural area of ​​the valve body and begins initial solidification; the second low-pressure casting stage refers to the stage from initial solidification to complete solidification of the main load-bearing structural area; the main load-bearing structural area of ​​the valve body refers to the core part of the valve body that bears the main working load (e.g., the pressure-bearing wall of the fluid channel or the force-bearing column connected to the actuator); the solidification defect data is a dataset reflecting the correlation between casting defects and pressure in this area.

[0029] For example, obtaining solidification shrinkage defect data corresponding to the main load-bearing structural area of ​​the valve body during the first low-pressure casting stage can be achieved through simulation. Specifically, the three-dimensional casting model of the valve body is imported into casting simulation software (e.g., ProCAST, MAGMAsoft), and the process parameters for the first low-pressure casting stage are set (e.g., pouring temperature 680℃, holding pressure 0.6MPa, pouring speed 50mm / s). After running the simulation, the solidification process data of the main load-bearing structural area of ​​the valve body is exported. Solidification shrinkage defect information for this area is then filtered from the simulation data (e.g., by marking the coordinates of the shrinkage cavity (e.g., X100, Y80, Z50), diameter 3mm, etc.). The distribution range of the pine resin (e.g., X95-105, Y75-85, Z48-52) is compiled into "strain data". The thermal gradient distribution characteristics in the second low-pressure casting stage are obtained by collecting real-time temperature data of each area of ​​the valve body through the temperature field monitoring module of the software (e.g., collecting once every 5 seconds, for a total of 300 sets) after entering the second low-pressure casting stage (10-30 minutes after the molten metal is filled in the simulation). Based on these data, the temperature gradient of the thermal points is calculated, and finally the thermal gradient distribution characteristics are compiled. For example, the thermal gradient of the valve stem mounting boss area is 4℃ / mm, and the thermal gradient of the flange flow channel intersection is 3.5℃ / mm.

[0030] In one possible implementation, S100, acquiring the solidification defect data corresponding to the main load-bearing structural region of the valve body in the first low-pressure casting stage and the thermal gradient distribution characteristics in the second low-pressure casting stage, including: S110, analyze the distribution pattern of solidification shrinkage defects in the main load-bearing structural region of the valve body in the casting simulation results.

[0031] It can be understood that the distribution pattern of solidification shrinkage defects refers to the spatial distribution pattern of defects such as shrinkage cavities and porosity within the main load-bearing structural area of ​​the valve body. For example, they may be concentrated in specific locations or distributed in specific shapes. For example, by observing the spatial location of defects and then analyzing their morphological patterns, a distribution pattern can be obtained based on these patterns. Observing the spatial location of defects can be done by recording whether the defects are concentrated at the connection between the main load-bearing structure and the flange, or at the bottom corner of the main load-bearing structure, and counting the number of defects at each location (e.g., 8 shrinkage cavities at the connection and 5 shrinkage cavities at the bottom corner). Analyzing the morphological patterns of defects can be done by measuring the size of the defects (e.g., shrinkage cavities at the connection are 2-4 mm in diameter and spherical; shrinkage cavities at the bottom corner are net-like and have an area of ​​5-8 mm²), and obtaining the relationship between the defects and the structural wall thickness. The final distribution pattern can be determined as follows: solidification shrinkage defects in the main load-bearing structure area of ​​the valve body are mainly concentrated in the thick-walled parts connected to the flange, with spherical shrinkage cavities as the main feature and net-like shrinkage cavities as a secondary feature.

[0032] S120 generates a pressure spectrum and a solidification defect spectrum based on the distribution pattern of solidification shrinkage defects.

[0033] It can be understood that the pressure spectrum refers to the graph formed by arranging the pressure values ​​at different locations in the main load-bearing structural area of ​​the valve body according to their spatial positions during the casting process (reflecting the correlation between pressure distribution and defects); the solidification defect spectrum refers to the visual graph formed by organizing the types (shrinkage cavities / shrinkage porosity), locations, sizes, and severity of solidification shrinkage defects according to spatial coordinates (intuitively displaying the distribution of defects).

[0034] For example, generating a pressure spectrum can be achieved by exporting real-time pressure data of each coordinate point in the main load-bearing structural area of ​​the valve body from casting simulation software during the first low-pressure casting stage, filtering out the coordinate points of the defect concentration area in the solidification shrinkage defect distribution pattern, extracting the pressure values ​​of these points, plotting a pressure distribution curve with spatial coordinates (X,Y) as the horizontal axis and pressure value (MPa) as the vertical axis, and marking the pressure anomaly segment with pressure below 0.6MPa to form a pressure spectrum. Generating a solidification defect spectrum can be achieved by establishing a system that includes defect type (shrinkage cavity / shrinkage porosity), spatial coordinates (X,Y,Z), size (diameter / area), and severity level (light / medium / heavy, classified by size: less than 2mm in diameter is light, 2 to 4mm is medium, and greater than 4mm is heavy). Then, based on the two-dimensional cross-sectional view of the main load-bearing structure of the valve body, the defect locations are marked on the map (shrinkage cavities are marked with red dots, shrinkage porosity with orange mesh circles), and the defect size and severity level are marked next to them. The marked cross-sectional views are then organized into a series of maps according to the Z-axis height to form a solidification defect spectrum.

[0035] S130 collects the solidification temperature field, calculates the spatial distribution of the temperature change rate based on the solidification temperature field, and determines the characteristics of the thermal gradient distribution.

[0036] It can be understood that the solidification temperature field refers to the spatial distribution field of temperature formed at a certain moment in all positions inside the valve body during the second low-pressure casting stage (such as different coordinate points corresponding to different temperatures); the spatial distribution of temperature change rate refers to the spatial distribution of the temperature change (°C / s) per unit time at different positions.

[0037] For example, the solidification temperature field can be collected by pre-installing 20 type K thermocouples (5mm apart at each location) in the main load-bearing structural area of ​​the valve body mold, the flange flow channel intersection, or / and the valve stem mounting boss, and connecting them to a data acquisition instrument (e.g., Agilent). (34970A), start the second low-pressure casting stage (after the molten metal is filled into the mold), set the data acquisition frequency of the data acquisition instrument to 10 seconds / time, and continuously acquire data for 30 minutes (a total of 180 sets of data), record the position coordinates of each thermocouple (e.g., thermocouple 1: X80, Y60, Z40; thermocouple 2: X85, Y60, Z40) and the temperature value at the corresponding time, organize them into solidification temperature field data, and obtain the acquired solidification temperature field based on the solidification temperature field data; calculate the spatial distribution of temperature change rate. For the temperature data of each thermocouple, calculate the temperature difference between two adjacent time points (e.g., temperature 600℃ at time t1, 580℃ at time t2, temperature difference -20℃), and then divide by the time interval (10 seconds) to obtain the temperature change rate at that location (-2℃ / s). Then, with the valve body spatial coordinates (X, Y) as the horizontal axis, the temperature change rate (℃ / s) is calculated. Using the vertical axis as the ordinate, a rate distribution heatmap is plotted (red indicates slow rate < -1℃ / s, blue indicates fast rate > -3℃ / s), forming a spatial distribution map of the temperature change rate. This rate distribution heatmap can be plotted via communication between an adaptive optimization device for the low-pressure casting pressure curve of the ball valve body and Origin software. Determining the thermal gradient distribution characteristics involves selecting regions with slow temperature change rates (red regions, i.e., thermal junction regions) from the heatmap, calculating the temperature difference between adjacent thermocouples within these regions, dividing by the distance between the two thermocouples to obtain the temperature gradient, and then statistically analyzing the gradient values ​​for all thermal junction regions to obtain the thermal gradient distribution characteristics.

[0038] This setup allows for precise location of hot spot areas, providing direct evidence for identifying defects caused by abnormal temperatures. At the same time, the hot spot gradient data can also reflect the impact of the structure on cooling.

[0039] S200, determine the composite structure data that is related to the main load-bearing structural area of ​​the valve body; wherein, the composite structure data is used to reflect the morphology of the composite structure transition area, which includes the flange flow channel intersection and the valve stem mounting boss.

[0040] For example, by determining the characteristics of the flange and the internal flow channel, the intersection of the two (the part where the annular structure of the flange connects to the cylindrical structure of the flow channel) is located. Then, based on the characteristics of the valve stem mounting boss (the protruding cylindrical structure in the model with a mounting hole at the top), the connection position between it and the main load-bearing structure of the valve body is confirmed (e.g., the bottom of the boss connects to the upper surface of the main load-bearing structure). The flange inner diameter, flow channel diameter, transition fillet radius at the intersection, wall thickness at the intersection, distance between the intersection and the main load-bearing structure, valve stem mounting boss height, boss bottom diameter, boss top diameter, boss top mounting hole diameter, fillet radius connecting the boss to the main load-bearing structure, boss wall thickness, etc., are then compared to determine the composite structure data.

[0041] In one possible implementation, S200, determining composite structural data associated with the main load-bearing structural region of the valve body, including: S210, determine the geometric boundary conditions of the flange flow channel intersection and the valve stem mounting boss in the structural model of the valve body.

[0042] It can be understood that geometric boundary conditions refer to the key parameters (including boundary coordinates, size range, shape characteristics, and connection boundaries with other structures) used to define the geometric shape of a structure in engineering analysis (such as casting simulation and structural mechanics analysis). Here, it specifically refers to the geometric boundaries of the flange flow channel intersection and the valve stem mounting boss, that is, the geometric parameters of the outer contour, inner hole, and connection surfaces with other structures of this area.

[0043] For example, to determine the geometric boundary conditions of the flange flow channel intersection and the valve stem mounting boss in the valve body structural model, the valve body structural model can be opened using 3D modeling software (such as SolidWorks, Pro / E). Measurement tools (such as distance, angle, and area measurement tools) can be used to measure the outer contour dimensions (e.g., flange outer diameter, flow channel width, intersection transition fillet radius), inner hole dimensions (e.g., flange inner diameter, flow channel diameter), and connection surface dimensions (e.g., intersection wall thickness, intersection connection surface dimensions with the main load-bearing structure), and the measurement data should be recorded. Simultaneously, the geometric parameters of the valve stem mounting boss should be measured, including boss height, boss bottom diameter, boss top diameter, boss top mounting hole diameter, fillet radius connecting the boss to the main load-bearing structure, and boss wall thickness, and the measurement data should also be recorded. The above measurement data should be processed to obtain the geometric boundary conditions of the flange flow channel intersection and the valve stem mounting boss.

[0044] S220, based on the geometric boundary conditions and the main load-bearing structural region of the valve body, the state is determined to obtain the composite structure data.

[0045] For example, by comparing the geometric parameters of the main load-bearing structural region of the valve body with the geometric boundary conditions of the main load-bearing structural region, the connection state is determined, thereby obtaining composite structural data. Specifically, determining the connection state can be done by coordinate comparison, determining that the connection surface at the intersection completely falls on the upper surface of the main load-bearing structural region, which is a surface-to-surface connection; determining a gradual transition state based on the measured transition length between the wall thickness at the intersection and the wall thickness of the main load-bearing structure; determining that the center coordinates of the bottom of the boss completely coincide with the coordinates of the key stress point of the main load-bearing structure; determining the center positioning and surface coverage connection state by the boss connection surface covering the local upper surface of the main load-bearing structure; and determining a rounded transition state (reducing stress concentration) by the rounded corners at the transition between the wall thickness of the boss and the wall thickness of the main load-bearing structure. The state is then used to form composite structural data, and by determining the state to supplement the connection information, the composite structural data can be made more complete.

[0046] S300, based on the data of condensation defects, the characteristics of thermal gradient distribution, and the data of composite structures, determines the spatial mapping relationship; wherein, the spatial mapping relationship is used to indicate the correspondence between the defect concentration area and the transition area of ​​the composite structure.

[0047] For example, based on the defect location coordinates in the solidification defect data, the hot spot region coordinates in the hot spot gradient distribution characteristics, and the geometric boundary conditions in the composite structure data, feature points are located in three-dimensional space. The defect concentration areas (e.g., shrinkage cavities, shrinkage porosity concentration areas) are then associated with the composite structure transition areas (e.g., the junction of flange flow channels, the connection area between the valve stem mounting boss and the main load-bearing structure), determining their relative positions and spatial relationships. This spatial mapping relationship can be achieved by annotating feature points and drawing connecting lines or surfaces in 3D modeling software, or it can be automatically calculated and generated by an algorithm. By determining the spatial mapping relationship, the correspondence between the defect concentration areas and the composite structure transition areas can be established, providing an important basis for subsequent analysis of defect causes and optimization of the casting process.

[0048] In one possible implementation, please refer to Figure 4 S300, based on condensation defect data, thermal gradient distribution characteristics, and composite structure data, determines the spatial mapping relationship, including: S310, based on the pressure spectrum and solidification defect spectrum included in the solidification defect data, the pressure anomaly data is determined, and the temperature abrupt change zone is determined based on the thermal gradient distribution characteristics; wherein, the pressure anomaly data is used to indicate the pressure anomaly zone.

[0049] For example, based on the pressure below 0.6 MPa marked in the pressure spectrum and the abnormal segment determined by the defect, the pressure abnormal zone is determined according to the abnormal segment, that is, the area in the main load-bearing structure area of ​​the valve body where the pressure value is lower than the set threshold; at the same time, based on the area with a slow rate indicated in red in the spatial distribution map of temperature change rate, the temperature change abrupt zone, that is, the hot spot area, is determined.

[0050] S320 spatially superimposes the pressure abnormality zone and the temperature sudden change zone to obtain the defect area; the defect area is used to indicate the potential defect concentration area of ​​the valve body during the casting process.

[0051] For example, the pressure abnormality area and the temperature sudden change area are superimposed to determine the spatial overlap area between the pressure abnormality area and the temperature sudden change area. These overlapping areas are identified as defect areas, that is, potential defect concentration areas of the valve body during the casting process. In addition, the defect areas can indicate that these areas have both insufficient pressure and slow cooling rate during the casting process.

[0052] S330 analyzes the morphological conditions reflected by the defect area and the composite structure data to obtain the spatial mapping relationship.

[0053] For example, the spatial coordinates of the defect area are compared and analyzed with the geometric boundary conditions of the flange flow channel intersection and valve stem mounting boss in the composite structure data to determine whether the defect area falls within the composite structure transition area or has a direct adjacent relationship with the transition area. Simultaneously, based on the relative position of the defect area and the composite structure transition area (e.g., above, below, or to the side of the intersection), and the relative position of the defect area and the boss connection surface (e.g., covering the boss connection surface, having a gap with the boss connection surface, or being adjacent to the boss connection surface), and further, based on the correspondence between the size and shape of the defect area and the size and shape of the composite structure transition area (e.g., the ratio of the defect area's diameter to the flow channel diameter, the relationship between the shape of the defect area and the shape of the transition fillet at the intersection), a spatial mapping relationship is finally obtained. This clearly indicates the correspondence between the defect concentration area and the composite structure transition area, providing precise guidance for subsequent optimization of the casting process.

[0054] This setup comprehensively considers the pressure distribution, temperature changes, and morphological characteristics of the composite structure during the casting process, thereby accurately identifying potential defect concentration areas. This provides strong support for subsequent targeted optimization measures, which can not only improve casting efficiency but also effectively reduce the scrap rate caused by defects, thereby enhancing product quality and overall competitiveness.

[0055] S400, based on the expansion characteristics of the valve body, determines the liquid compensation data of the transition region of the composite structure; wherein, the liquid compensation data includes the pulse pressure boosting parameters of the thin-walled junction region at the flange flow channel intersection and the pressure holding strength parameters of the thick-walled boss region of the valve stem mounting boss.

[0056] For example, based on the thermal expansion characteristics of the valve body material during the casting process, the volume change of the transition region of the composite structure during the solidification stage is analyzed to determine the required amount of liquid metal feeding. For the thin-walled junction area at the flange flow channel intersection, due to the complex structure and thin wall thickness of this area, shrinkage cavities and porosity defects are easily generated during solidification. Therefore, it is necessary to determine the solidification sequence and feeding requirements of this area through simulation analysis, and then set the pulse pressurization parameters, and then inject an appropriate amount of liquid metal into this area to fill the gaps caused by solidification shrinkage. The pulse pressurization parameters should include the pressurization timing, pressurization amplitude, and pressurization frequency to achieve the best feeding effect. For the thick-walled boss area of ​​the valve stem mounting boss, due to its large wall thickness, long solidification time, and tendency to generate shrinkage cavities internally, it is necessary to set appropriate holding pressure parameters to maintain a certain pressure in the later stage of solidification to promote liquid metal feeding into this area. The holding pressure parameters should include the holding pressure start time, holding pressure value, and holding pressure duration to ensure that this area can be fully fed and reduce the generation of defects.

[0057] In one possible implementation, please refer to Figure 5 S400, based on the expansion characteristics of the valve body, determines the liquid feeding data of the transition region of the composite structure, including: S410, based on the expansion characteristics, determine the molten metal flow resistance coefficient of the thin-walled junction zone at the flange flow channel intersection and the solidification shrinkage compensation amount of the thick-walled boss zone of the valve stem mounting boss.

[0058] It can be understood that the thin-walled junction area at the flange flow channel intersection refers to the area where the flange flow channels intersect and connect, and the wall thickness is relatively thin; the thick-walled boss area of ​​the valve stem mounting boss refers to the core area with a relatively thick wall in the valve stem mounting boss. The molten metal flow resistance coefficient is a parameter reflecting the degree of obstruction encountered by molten metal when flowing in the thin-walled junction area; the solidification shrinkage compensation amount is the amount of molten metal that needs to be replenished when the molten metal in the thick-walled boss area solidifies and its volume shrinks.

[0059] For example, based on the expansion characteristic data of the valve body material (e.g., volume change values ​​at different temperatures), a flow channel model of the thin-walled junction area is established using fluid simulation software. The temperature, viscosity, and expansion characteristic data of the molten metal are input, and the flow resistance coefficient is obtained by simulating the flow process of the molten metal. Then, a three-dimensional model of the thick-walled boss area is established, and the volume shrinkage trend during material solidification is input (inversely deduced from the expansion characteristics, the expansion coefficient is negative when the temperature drops, i.e., shrinkage). The solidification process is simulated, and the volume shrinkage difference is calculated. This difference is the solidification shrinkage compensation amount.

[0060] S420 determines the amplitude adjustment range of the pulse boosting parameters based on the flow resistance coefficient.

[0061] For example, based on the flow resistance coefficient, if the coefficient is large (the molten metal is difficult to flow), the minimum pressure value required for the molten metal to overcome the corresponding resistance is determined, and this is taken as the minimum amplitude; then, combined with the structural pressure bearing limit of the thin-walled junction area of ​​the valve body (to avoid cracking), the maximum amplitude is determined, and the range between the two is the amplitude adjustment range of the pulse boosting parameter.

[0062] S430, determine the gradient variation curve of the pressure holding strength parameter based on the solidification shrinkage compensation amount; wherein, the gradient variation curve is used to indicate the variation trend of the pressure holding strength parameter in the thick-walled boss area of ​​the valve stem.

[0063] It is understandable that the gradient change curve is the trend line of the change in pressure holding strength at different locations in the thick-walled boss area, such as the pressure difference between the center and the edge.

[0064] For example, it is determined that the center of the thick-walled boss area has the most severe shrinkage (i.e., the largest compensation amount) and the edge has less shrinkage (i.e., the smaller compensation amount). Then, based on the solidification shrinkage compensation amount, the calculation requirement is to distribute the holding pressure strength values ​​of the center, middle and edge in the way that the larger compensation amount corresponds to the higher holding pressure strength. The coordinates of each position are mapped to the corresponding holding pressure strength value, and a gradient change curve is plotted.

[0065] S440 determines liquid compensation data based on amplitude adjustment range and gradient change curve.

[0066] For example, the amplitude adjustment range (e.g., 0.8-1.2MPa) is combined with the curve (e.g., 1.2MPa for center pressure and 0.8MPa for edge pressure), the pressure holding pressure of each region is determined according to the curve, the pulse pressure boosting start time is determined according to the amplitude range (when the thick-walled area begins to solidify), and the shrinkage compensation amount of each region is calculated according to the solidification shrinkage compensation amount. The pressure, timing and amount are integrated to form liquid shrinkage compensation data.

[0067] This setup allows for the development of suitable liquid feeding schemes tailored to the characteristics of transition areas in composite structures such as flange flow channel intersections and valve stem mounting bosses. This ensures that these areas receive adequate feeding during the casting process, reducing the occurrence of defects. By precisely controlling the pulse boosting parameters and holding pressure parameters, the flow of liquid metal and the feeding effect can be optimized, improving casting quality and efficiency.

[0068] In one possible implementation, please refer to Figure 6 S400, based on the expansion characteristics of the valve body, determines the liquid feeding data of the transition region of the composite structure, including: S401, determine the expansion coefficient variation curve of the valve body material at different temperatures; wherein, the expansion coefficient variation curve is used to indicate the volume expansion trend of the valve body material during heating.

[0069] As can be understood, the coefficient of thermal expansion refers to the relative change in material volume caused by a unit change in temperature, reflecting the tendency of the material to expand in volume during the heating process.

[0070] For example, by acquiring volume expansion data of the valve body material at different temperatures, these data are plotted as curves showing the change in the coefficient of expansion. This curve allows determination of the expansion characteristics of the valve body material at different temperature stages, including changes in the expansion rate and the cumulative amount of expansion.

[0071] S402, determine the volume expansion difference value of the valve body material based on the expansion coefficient change curve; wherein, the volume expansion difference value is used to indicate the magnitude of volume change caused by temperature change.

[0072] For example, the pouring temperature of the molten metal and the room temperature after solidification are determined, the expansion coefficients of these two temperatures are determined from the curves, and the volumes at the two temperatures are calculated using the formula: volume = initial volume × (1 + expansion coefficient × temperature difference). The difference in volume expansion is obtained by subtracting the two values.

[0073] S403 generates liquid compensation data based on the volume expansion difference value.

[0074] For example, for transition areas of composite structures such as flange flow channel junctions and valve stem mounting bosses, the liquid metal feeding amount corresponding to the magnitude of the volume expansion difference is obtained based on the magnitude of the volume expansion difference, so that these areas can receive sufficient feeding during solidification. Specifically, corresponding feeding parameters can be set, such as feeding timing, feeding pressure, and feeding amount, and these parameters can be integrated to form liquid feeding data.

[0075] This setup allows for a more accurate reflection of the volume changes in the valve body material during the casting process, leading to a more reasonable liquid feeding scheme. After determining the volume expansion difference value, the impact of expansion differences in different regions on the liquid metal feeding requirements can be further analyzed. For example, for regions with large expansion differences, a larger feeding amount and higher feeding pressure may be needed to ensure that the liquid metal can fully fill the voids created by solidification shrinkage. Simultaneously, based on the expansion coefficient variation curve, the thermal stress and deformation that may occur in the valve body during the casting process can also be predicted.

[0076] The S500 uses the valve body's pressure-bearing and sealing performance and the viscosity-temperature characteristics of molten metal to construct phase change pressure data based on the casting process. The phase change pressure data is used to indicate the dynamic pressure threshold before the valve body solidifies. The casting process includes a pressurization process, a crystallization process, and a depressurization process.

[0077] It is understandable that the valve body's pressure-bearing sealing performance refers to the valve body's ability to prevent media leakage when subjected to pressure; the viscosity-temperature characteristics of molten metal refer to the law of viscosity change of molten metal with temperature (viscosity usually increases as temperature decreases). For example, by using valve body pressure sealing performance test data (such as leakage pressure from pressure testing) and molten metal viscosity data at different temperatures, the data is processed in stages according to the casting process. Specifically, the temperature at which the viscosity of the molten metal changes abruptly is recorded during the pressurization stage, the relationship between pressure and the molten metal propulsion speed is recorded during the crystallization stage, and the sealing performance critical value is combined during the depressurization stage. The data from the three stages are correlated to generate a dynamic pressure threshold table that changes with temperature or time, thus obtaining phase change pressure data.

[0078] In one possible implementation, please refer to Figure 7 The S500, based on the valve body's pressure-bearing sealing performance and the viscosity-temperature characteristics of molten metal, and constructed according to the phase change pressure data of the casting process, includes: S510, determine the critical value of the pressure-bearing sealing performance in the design specifications of the valve body; wherein the critical value is used to indicate the requirement for the valve body to maintain a sealing state when subjected to a specific pressure.

[0079] For example, the critical value of pressure-bearing sealing performance can be determined by consulting the valve body design drawings or product standards to obtain its rated sealing pressure, then attaching the valve body sealing surface, slowly pressurizing the valve body, maintaining the pressure at 0.1 MPa for 5 minutes, and observing whether there is leakage on the sealing surface (bubbles can be detected with soapy water). The pressure value at which bubbles first appear is the critical value of pressure-bearing sealing performance.

[0080] S520, during the pressurization process, determines the critical transition point of the viscosity-temperature characteristics of the molten metal; whereby the critical transition point is used to characterize the temperature point at which the viscosity of the molten metal changes significantly with temperature during the solidification process.

[0081] For example, in a pressurized environment (simulating casting pressurization pressure, such as 0.5-1 MPa), the rotational viscometer measures the viscosity value every 20°C when the temperature drops from the molten metal pouring temperature (e.g., 1450°C), records the corresponding data of temperature and viscosity, and then determines the temperature point of viscosity change through the corresponding data. The temperature point of viscosity change is then determined as the critical transition point.

[0082] In one possible implementation, please refer to Figure 2 S520, during the pressurization process, determines the critical transition point of the viscosity-temperature characteristics of the molten metal, including: S521, during the pressurization process, constructs the derivative curve of viscosity change rate as a function of temperature.

[0083] For example, using raw data of different temperatures and viscosities, the viscosity difference between every two adjacent temperature points (viscosity at the later temperature minus viscosity at the earlier temperature) is calculated, and then divided by the temperature difference to obtain the viscosity change rate for each temperature range. By mapping the temperature to the corresponding viscosity change rate, a smooth curve is obtained, which is the derivative curve of the viscosity change rate with temperature.

[0084] S522 identifies the inflection point where the slope of the derivative curve changes abruptly.

[0085] For example, the derivative curve obtained in step S521 is segmented and fitted, the slope of each segment is calculated, and the slope values ​​of adjacent segments are compared. If the slope difference before and after a certain position exceeds a set threshold (for example, the slope suddenly rises from 5 mPa・s / ℃² to 20 mPa・s / ℃²), then that position is the inflection point of the slope change in the derivative curve.

[0086] S523 defines the temperature value corresponding to the inflection point as the critical transition point.

[0087] For example, determining the temperature value corresponding to the inflection point as the critical transition point can be done by drawing a straight line perpendicular to the horizontal axis (temperature axis) along the determined inflection point. The temperature value corresponding to the intersection of the straight line and the horizontal axis is the critical transition point of the viscosity-temperature characteristics of the molten metal.

[0088] S530, during the crystallization process, determine the pressure change data during the metal liquid phase transformation process; among which, the pressure change data is used to reflect the relationship between the propulsion rate and pressure before the valve body solidifies.

[0089] It can be understood that the crystallization process refers to the process by which molten metal cools from a liquid state to a solid state, and the atomic arrangement changes from disorder to order. The pressure change data during the phase transformation of molten metal records the correspondence between the pressure inside the mold and the rate at which the molten metal is propelled (the speed at which the cavity is filled) during the crystallization stage.

[0090] For example, during the casting and crystallization stage, the pressure inside the mold is collected in real time using a pressure sensor (recorded once every 10 seconds). At the same time, based on the process of the molten metal filling the cavity, the molten metal propulsion rate (e.g., 5 mm per second) is calculated through image analysis. The pressure value at the same time point is matched one-to-one with the propulsion rate to obtain the corresponding results. The corresponding results are organized into a pressure propulsion rate correspondence, that is, the correspondence is pressure change data.

[0091] S540 determines phase change pressure data based on pressure change data, critical values, and critical transition points during the depressurization process.

[0092] It is understandable that the depressurization process refers to the process of gradually reducing the pressure inside the mold to atmospheric pressure after the crystallization stage is completed.

[0093] For example, the critical value of pressure sealing is first used as the upper limit of phase change pressure; then, with the critical transition point as the boundary, when the temperature is above 1250℃, the pressure value corresponding to the propulsion rate ≥3mm / s is used as the pressure threshold for that temperature range; when the temperature is below 1250℃, the pressure value corresponding to the propulsion rate ≥2mm / s is used as the threshold. The pressure thresholds of different temperature ranges are then arranged in chronological order to obtain phase change pressure data.

[0094] This design comprehensively considers the valve body's pressure-bearing and sealing performance, the viscosity-temperature characteristics of the molten metal, and the pressurization, crystallization, and depressurization stages during the casting process, resulting in more accurate phase change pressure data. When determining the phase change pressure data, not only are the valve body's design specifications and the physical properties of the molten metal considered, but the actual conditions of the casting process are also taken into account. This ensures that the obtained data more accurately reflects the pressure changes of the valve body during casting. By setting pressure thresholds in segments, the corresponding pressure values ​​can be determined based on the molten metal propulsion rate at different temperature ranges, thus improving casting quality.

[0095] S600 determines optimized data based on spatial mapping relationships, liquid feeding data, and phase change pressure data; among which, the optimized data is used to indicate the optimized low-pressure casting pressure curve of the valve body.

[0096] For example, the liquid feeding data is adjusted by using spatial mapping relationships as constraints (e.g., thick-walled boss areas correspond to higher holding pressure), and then the time distribution of pulse boosting parameters and holding pressure strength parameters is adjusted according to phase change pressure data. The adjusted pressure parameters are then sorted according to the casting time sequence to obtain optimized data.

[0097] In summary, this method can improve the control of local areas during the casting process, avoid the defects caused by the fixed pressure curve in traditional low-pressure casting methods, and effectively avoid the problems of splashing and air entrapment caused by excessive pressure in thin-walled areas and shrinkage porosity caused by insufficient pressure in thick-walled areas, thereby improving the casting quality and reliability of the ball valve body.

[0098] In one possible implementation, please refer to Figure 8 S600 determines optimized data based on spatial mapping relationships, liquid feeding data, and phase change pressure data, including: S610 uses spatial mapping relationships as constraints for the spatial allocation of liquid compensation data.

[0099] It is understandable that the constraints of spatial allocation refer to the spatial rules that must be followed when allocating the amount and pressure of compensation to different areas of the valve body (for example, the amount of compensation in the thick-walled area is greater than that in the thin-walled area, and the compensation pressure in the area near the flow channel is greater than that in the area far from the flow channel).

[0100] For example, based on the liquid feeding data and according to the mapping relationship, 60% of the feeding amount is allocated to the thick-walled boss area and 40% is allocated to the thin-walled area. At the same time, the feeding pressure of the thick-walled area is set to 1.2MPa and the feeding pressure of the thin-walled area is set to 0.8MPa, so as to be able to distribute the feeding amount in accordance with the spatial structure requirements.

[0101] S620, based on the dynamic pressure threshold in the phase change pressure data, adjusts the time-series distribution of the pulse boosting parameters and the pressure holding intensity parameters to obtain the allocation data; wherein, the allocation data is used to indicate the pressure allocation strategy.

[0102] It can be understood that time-series distribution refers to the arrangement order of pulse boosting parameters (such as pressure amplitude and interval time) and holding pressure intensity parameters (such as holding pressure and holding time) on the casting time axis. For example, when the temperature of the molten metal drops to the critical transition point, the viscosity increases significantly. At this time, pulse pressurization needs to be activated to avoid poor filling due to increased viscosity. During the crystallization stage of casting, the holding pressure is dynamically adjusted according to the correspondence between pressure change data and molten metal propulsion rate, so that the molten metal can be smoothly propulsed and fully fill the cavity. During the depressurization stage of casting, the pressure inside the mold is gradually reduced in combination with the critical value of pressure sealing, so that the valve body will not produce defects due to pressure changes during solidification. Furthermore, by adjusting the distribution of pulse pressurization parameters and holding pressure parameters on the time axis, more reasonable allocation data can be obtained.

[0103] S630 integrates allocation data and space allocation results to obtain optimized data.

[0104] For example, the pulse boosting parameters and pressure holding strength parameters in the allocation data are matched one-to-one with the compensation amount and compensation pressure in the spatial allocation results. A curve is plotted according to the allocation data, and the pressure value and rate of change at key time points on the curve are extracted, thus integrating them into optimized data.

[0105] This setup allows the optimized data to conform to the spatial structural characteristics of the valve body and adapt to dynamic pressure changes during the casting process. By constraining the distribution of liquid feeding data through spatial mapping relationships, the feeding needs of different regions can be met, while avoiding over-feeding or under-feeding.

[0106] 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.

[0107] Corresponding to the adaptive optimization method for the low-pressure casting pressure curve of the ball valve body described in the above embodiments, this application also provides an adaptive optimization system for the low-pressure casting pressure curve of the ball valve body. Each unit of this system can implement each step of the adaptive optimization method for the low-pressure casting pressure curve of the ball valve body. Figure 9 The diagram shows a structural block diagram of the adaptive optimization system for the low-pressure casting pressure curve of the ball valve body provided in the embodiments of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0108] Reference Figure 9 The adaptive optimization system for the low-pressure casting pressure curve of the ball valve body includes: The acquisition unit is used to acquire solidification defect data corresponding to the main load-bearing structure area of ​​the valve body in the first low-pressure casting stage and thermal gradient distribution characteristics in the second low-pressure casting stage; wherein, the solidification defect data includes pressure spectrum and solidification defect spectrum, and the thermal gradient distribution characteristics are used to reflect the distribution of the temperature change rate of the valve body during solidification. The first determining unit is used to determine the composite structure data that is associated with the main load-bearing structural area of ​​the valve body; wherein, the composite structure data is used to reflect the morphology of the composite structure transition area, which includes the flange flow channel intersection and the valve stem mounting boss. The second determining unit is used to determine the spatial mapping relationship based on the consolidation defect data, the thermal gradient distribution characteristics, and the composite structure data; wherein, the spatial mapping relationship is used to indicate the correspondence between the defect concentration area and the transition area of ​​the composite structure; The third determining unit is used to determine the liquid compensation data of the transition region of the composite structure based on the expansion characteristics of the valve body; wherein, the liquid compensation data includes the pulse pressure increase parameters of the thin-walled junction region at the flange flow channel intersection and the pressure holding strength parameters of the thick-walled boss region of the valve stem mounting boss; The construction unit is used to construct phase change pressure data based on the valve body's pressure-bearing and sealing performance and the viscosity-temperature characteristics of molten metal, and according to the casting process; wherein, the phase change pressure data is used to indicate the dynamic pressure threshold before the valve body solidifies, and the casting process includes the pressure increase process, the crystallization process, and the pressure release process; The results unit is used to determine the optimization data based on spatial mapping relationships, liquid feeding data, and phase change pressure data; wherein, the optimization data is used to indicate the optimized low-pressure casting pressure curve of the valve body.

[0109] 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.

[0110] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules 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 and modules 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 and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0111] This application also provides an adaptive optimization device for the low-pressure casting pressure curve of a ball valve body. Figure 10 This is a schematic diagram of the structure of an adaptive optimization device for the low-pressure casting pressure curve of a ball valve body provided in an embodiment of this application. Figure 10 As shown, the adaptive optimization device 6 for the low-pressure casting pressure curve of the ball valve body in this embodiment includes: at least one processor 60 ( Figure 10 Only one is shown in the image), at least one memory 61 ( Figure 10 (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 ball valve body low-pressure casting pressure curve adaptive optimization device 6 to implement the steps in any of the above embodiments of the ball valve body low-pressure casting pressure curve adaptive optimization method, or causes the ball valve body low-pressure casting pressure curve adaptive optimization device 6 to implement the functions of each module / unit in the above embodiments of the system.

[0112] For example, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 62 in the ball valve body low-pressure casting pressure curve adaptive optimization device 6.

[0113] The adaptive optimization device 6 for the low-pressure casting pressure curve of the ball valve body can be a desktop computer, laptop, or other computing device. This adaptive optimization device for the low-pressure casting pressure curve of the ball valve body may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 10 This is merely an example of the adaptive optimization device 6 for the low-pressure casting pressure curve of the ball valve body, and does not constitute a limitation on the device 6. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0114] 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.

[0115] In some embodiments, the memory 61 may be an internal storage unit of the ball valve body low-pressure casting pressure curve adaptive optimization device 6, such as a hard disk or memory of the ball valve body low-pressure casting pressure curve adaptive optimization device 6. In other embodiments, the memory 61 may be an external storage device of the ball valve body low-pressure casting pressure curve adaptive optimization device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the ball valve body low-pressure casting pressure curve adaptive optimization device 6. Further, the memory 61 may include both internal storage units and external storage devices of the ball valve body low-pressure casting pressure curve adaptive optimization device 6. The memory 61 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0116] 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.

[0117] This application provides a computer program product that, when running on a ball valve body low-pressure casting pressure curve adaptive optimization device, enables the ball valve body low-pressure casting pressure curve adaptive optimization device to implement the steps in any of the above method embodiments.

[0118] 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 methods of the above 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 ball valve body low-pressure casting pressure curve adaptive optimization device, 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. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0119] 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.

[0120] 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.

[0121] In the embodiments provided in this application, it should be understood that the disclosed adaptive optimization system, device, and method for low-pressure casting pressure curve of ball valve body can be implemented in other ways. For example, the embodiments of the adaptive optimization system and device for low-pressure casting pressure curve of ball valve body described above are merely illustrative. For instance, the division of modules or units is only 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 coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0122] 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.

[0123] 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. An adaptive optimization method for the low-pressure casting pressure curve of a ball valve body, characterized in that, include: Acquire solidification defect data corresponding to the main load-bearing structural area of ​​the valve body in the first low-pressure casting stage and thermal gradient distribution characteristics in the second low-pressure casting stage; wherein, the solidification defect data includes pressure spectrum and solidification defect spectrum, and the thermal gradient distribution characteristics are used to reflect the distribution of the temperature change rate of the valve body during solidification. Determine composite structure data that is associated with the main load-bearing structural region of the valve body; wherein, the composite structure data is used to reflect the morphology of the composite structure transition region, the composite structure transition region including the flange flow channel intersection and the valve stem mounting boss; The spatial mapping relationship is determined based on the congealing defect data, the thermal gradient distribution characteristics, and the composite structure data; wherein, the spatial mapping relationship is used to indicate the correspondence between the defect concentration area and the transition area of ​​the composite structure; The liquid compensation data of the transition region of the composite structure is determined based on the expansion characteristics of the valve body; wherein, the liquid compensation data includes the pulse pressure increase parameters of the thin-walled junction region at the flange flow channel intersection and the pressure holding strength parameters of the thick-walled boss region of the valve stem mounting boss; The phase change pressure data is constructed based on the valve body's pressure-bearing and sealing performance and the viscosity-temperature characteristics of the molten metal, and according to the casting process. The phase change pressure data is used to indicate the dynamic pressure threshold before the valve body solidifies. The casting process includes a pressure-increasing process, a crystallization process, and a pressure-reducing process. Optimized data is determined based on the spatial mapping relationship, the liquid feeding data, and the phase change pressure data; wherein, the optimized data is used to indicate the optimized low-pressure casting pressure curve of the valve body.

2. The adaptive optimization method for the low-pressure casting pressure curve of the ball valve body as described in claim 1, characterized in that, The composite structural data that is determined to be associated with the main load-bearing structural region of the valve body includes: Determine the geometric boundary conditions of the flange flow channel intersection and the valve stem mounting boss in the structural model of the valve body; Based on the geometric boundary conditions and the state determination of the main load-bearing structural region of the valve body, the composite structure data is obtained.

3. The adaptive optimization method for the low-pressure casting pressure curve of the ball valve body as described in claim 2, characterized in that, The step of determining the spatial mapping relationship based on the condensation defect data, the thermal nodal gradient distribution characteristics, and the composite structure data includes: Pressure anomaly data determined based on the pressure spectrum and solidification defect spectrum included in the solidification defect data, and temperature abrupt change zones determined based on the thermal gradient distribution characteristics; wherein, the pressure anomaly data is used to indicate pressure anomaly zones; The pressure anomaly zone and the temperature abrupt change zone are spatially superimposed to obtain a defect region; wherein, the defect region is used to indicate the potential defect concentration area of ​​the valve body during the casting process; By analyzing the morphological characteristics of the defective region and the composite structure data, a spatial mapping relationship is obtained.

4. The adaptive optimization method for the low-pressure casting pressure curve of the ball valve body as described in claim 3, characterized in that, The determination of liquid compensation data for the transition region of the composite structure based on the expansion characteristics of the valve body includes: The flow resistance coefficient of molten metal in the thin-walled junction area at the flange flow channel intersection and the solidification shrinkage compensation amount in the thick-walled boss area of ​​the valve stem mounting boss are determined based on the expansion characteristics. The amplitude adjustment range of the pulse boosting parameters is determined based on the flow resistance coefficient. The gradient variation curve of the pressure holding strength parameter is determined based on the solidification shrinkage compensation amount; wherein, the gradient variation curve is used to indicate the variation trend of the pressure holding strength parameter in the thick-walled boss area of ​​the valve stem; The liquid compensation data is determined based on the amplitude adjustment range and the gradient change curve.

5. The adaptive optimization method for the low-pressure casting pressure curve of the ball valve body as described in claim 3 or 4, characterized in that, The determination of liquid compensation data for the transition region of the composite structure based on the expansion characteristics of the valve body includes: Determine the expansion coefficient variation curve of the valve body material at different temperatures; wherein the expansion coefficient variation curve is used to indicate the volume expansion trend of the valve body material during heating. The volume expansion difference value of the valve body material is determined based on the expansion coefficient variation curve; wherein, the volume expansion difference value is used to indicate the magnitude of volume change caused by temperature change; The liquid compensation data is generated based on the volume expansion difference value.

6. The adaptive optimization method for the low-pressure casting pressure curve of the ball valve body as described in claim 5, characterized in that, The method involves analyzing the valve body's pressure-bearing and sealing performance against the viscosity-temperature characteristics of the molten metal, and constructing phase change pressure data based on the casting process, including: Determine the critical value of the pressure-bearing sealing performance in the design parameters of the valve body; wherein the critical value is used to indicate the requirement for the valve body to maintain a sealing state when subjected to a specific pressure; During the pressurization process, the critical transition point of the viscosity-temperature characteristics of the molten metal is determined; wherein, the critical transition point is used to characterize the temperature point at which the viscosity of the molten metal changes significantly with temperature during the solidification process; During the crystallization process, pressure change data during the liquid metal phase transition is determined; wherein, the pressure change data is used to reflect the relationship between the propulsion rate and pressure before the valve body solidifies. During the depressurization process, the phase change pressure data is determined based on the pressure change data, the critical value, and the critical transition point.

7. The adaptive optimization method for the low-pressure casting pressure curve of the ball valve body as described in claim 4, characterized in that, The process of determining optimized data based on the spatial mapping relationship, the liquid replenishment data, and the phase change pressure data includes: The spatial mapping relationship is used as a constraint condition for the spatial allocation of the liquid compensation data; The allocation data is obtained by adjusting the time-series distribution of the pulse boosting parameters and the pressure holding intensity parameters based on the dynamic pressure threshold in the phase change pressure data; wherein, the allocation data is used to indicate the pressure allocation strategy; The optimized data is determined based on the allocated data.

8. The adaptive optimization method for the low-pressure casting pressure curve of the ball valve body as described in claim 6, characterized in that, Determining the critical transition point of the viscosity-temperature characteristics of the molten metal during the pressurization process includes: During the pressurization process, a derivative curve of the viscosity change rate as a function of temperature is constructed; Identify the inflection point where the slope of the derivative curve changes abruptly; The temperature value corresponding to the inflection point is determined as the critical transition point.

9. The adaptive optimization method for the low-pressure casting pressure curve of the ball valve body as described in any one of claims 1 to 8, characterized in that, The acquisition of solidification defect data corresponding to the main load-bearing structural region of the valve body in the first low-pressure casting stage and the thermal gradient distribution characteristics in the second low-pressure casting stage includes: Analyze the distribution pattern of solidification shrinkage defects in the main load-bearing structural region of the valve body as described in the casting simulation results; The pressure spectrum and solidification defect spectrum are generated based on the solidification shrinkage defect distribution pattern. The solidification temperature field is collected, and the spatial distribution of the temperature change rate is calculated based on the solidification temperature field to determine the characteristics of the thermal gradient distribution.

10. An adaptive optimization device for the low-pressure casting pressure curve of a ball valve body, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 9.

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