Precision control method, system and equipment for gantry machine tool ram integration casting

Abstract

The application provides a gantry machine tool ram integrated casting precision control method, system and equipment, relates to the casting control technical field, and the method comprises the following steps: setting sectional casting process parameters according to the structural characteristic parameters of the ram assembly of the gantry machine tool equipment; based on the machining die cavity of the gantry machine tool equipment and the thermal expansion coefficient of the ram assembly, a first correction compensation value and a second correction compensation value are obtained; the optimal casting parameter combination obtained by optimization is inversely analyzed into the sectional casting process parameters to generate a casting precision control execution scheme, real-time monitoring data is collected, and a BP neural network is used to perform online fine adjustment on the casting parameter combination. Through the application, the technical problem that the casting precision is unstable due to uneven residual stress distribution and uncontrolled shrinkage in the casting process in the prior art is solved, the sectional casting process parameters are set, the process parameters of each region are accurately controlled in the casting process, and the casting precision is optimized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of casting control, and particularly relates to a gantry machine tool ram integrated casting precision control method, system and equipment. BACKGROUND

[0002] Traditional casting processes usually adopt uniform process parameters to process the entire casting, but for castings with complex structures, such as rams, due to the large difference in thickness of different parts, the solidification and shrinkage behaviors of each part also have large differences, and it is difficult to take into account the different needs of each region, which may lead to the fact that the thin-walled region is completed after solidification, while the thicker region is still in the shrinkage stage. Due to the interaction of thermal stress and shrinkage stress, a huge stress concentration is generated inside the casting, especially in the hot spot area, which is easy to form defects such as shrinkage cavity and shrinkage porosity, further affecting the dimensional accuracy and shape stability of the casting, leading to uncontrollable thermal stress and shrinkage stress during the solidification process of the casting, thereby affecting the casting precision, and leading to the instability of the casting precision.

[0003] In summary, the prior art has the technical problem of instability of casting precision due to uneven distribution of residual stress and uncontrolled shrinkage during the casting process. SUMMARY

[0004] The purpose of the present application is to provide a gantry machine tool ram integrated casting precision control method, system and equipment, to solve the technical problem of instability of casting precision due to uneven distribution of residual stress and uncontrolled shrinkage during the casting process in the prior art.

[0005] In view of the above problems, the present application provides a gantry machine tool ram integrated casting precision control method, system and equipment.

[0006] In the first aspect, the present application provides a gantry machine tool ram integrated casting precision control method, which is realized by a gantry machine tool ram integrated casting precision control system, wherein the gantry machine tool ram integrated casting precision control method comprises: setting segmented casting process parameters associated with a pouring area, a feeding area and a cooling adjustment area according to the structure characteristic parameters of a ram assembly of a gantry machine tool equipment; obtaining a first correction compensation value and a second correction compensation value based on a machining mold cavity of the gantry machine tool equipment and a thermal expansion coefficient of the material of the ram assembly; based on the first correction compensation value and the second correction compensation value, inversely analyzing an optimal casting parameter combination obtained by optimization into the segmented casting process parameters to generate a casting precision control execution scheme, collecting real-time monitoring data of each precision influence area in real time through an industrial Ethernet, and performing online fine tuning on the casting parameter combination by using a BP neural network.

[0007] Optionally, based on the machining die cavity of the gantry machine tool equipment, combined with the casting precision requirement, the size of the cavity, the form and position tolerance are full-size detected to obtain a first correction compensation value; based on the segmented casting process parameters, the flow field distribution of the molten iron filling process is simulated and set by fluid dynamics to obtain the gating flow gradient parameters under the flow stability limitation.

[0008] Optionally, based on the thermal expansion coefficient of the ram assembly material, combined with the historical casting shrinkage, the size shrinkage at different temperature stages in the casting process is dynamically deduced to obtain a second correction compensation value; based on the segmented casting process parameters, the ram assembly is set to be lightweight by topology optimization to obtain the thermal expansion compensation gap under the strength limitation.

[0009] Optionally, through the first correction compensation value and the gating flow gradient parameter, the second correction compensation value and the thermal expansion compensation gap, an associated mapping matrix is constructed; the matrix row dimension of the associated mapping matrix is the cavity size compensation element category associated with the first correction compensation value, the form and position tolerance compensation element category, the second correction compensation value associated with the high-temperature section shrinkage compensation element category and the phase change solidification compensation element category, and the matrix column dimension of the associated mapping matrix is the precision influence area of the ram assembly, including the guide rail mounting surface of the casting area, the internal rib structure of the feeding area, and the end connecting seat of the cooling adjustment area.

[0010] Optionally, based on the associated mapping matrix, combined with the casting precision requirement, the coupling influence coefficient of the associated mapping matrix is taken as the fitness function weight, and the planeness of the guide rail mounting surface of the ram assembly, the internal rib size deviation, and the form and position tolerance of the end connecting seat are taken as the optimization target.

[0011] Optionally, the value range of the first correction compensation value and the gating flow gradient parameter, and the second correction compensation value and the thermal expansion compensation gap are taken as the particle search space, and the iteration optimization is performed by introducing the adaptive inertia weight, the casting parameter combination generated in each round of optimization is input into the casting process simulation model for verification, and if the simulation verification result meets the casting precision requirement, the current casting parameter combination is output as the optimal solution.

[0012] Optionally, if not, based on the associated mapping matrix, the compensation element category with the highest deviation contribution degree is located, the particle search interval of the compensation element category with the highest deviation contribution degree is locally optimized until the iteration number reaches the preset threshold; the optimal casting parameter combination obtained by optimization is inversely analyzed into the segmented casting process parameters to generate the casting precision control execution scheme including the dynamic flow adjustment curve of the casting area, the stepped feeding scheme of the feeding area, and the partition temperature control strategy of the cooling adjustment area.

[0013] Optionally, the parameter sensitivity of the correlation mapping matrix is taken as the network input weight, and the difference from the target value of the casting precision requirement is taken as the network input layer variable; after each round of fine tuning is completed, the corrected casting parameter combination is substituted into the correlation mapping matrix for reverse verification to determine the deviation improvement rate of each precision influence area; if the deviation improvement rate is lower than a preset improvement rate threshold, the particle search interval of the compensation element category with the highest deviation contribution degree is locally optimized to search the space expansion of the strong correlation edge between the compensation element category and each precision influence area.

[0014] In a second aspect, the application further provides a gantry machine tool ram integrated casting precision control system for executing the gantry machine tool ram integrated casting precision control method of the first aspect, wherein the gantry machine tool ram integrated casting precision control system comprises: a parameter setting module configured to set segmented casting process parameters associated with a pouring zone, a feeding zone and a cooling adjustment zone according to structural characteristic parameters of a ram assembly of a gantry machine tool device; a compensation value acquisition module configured to acquire a first correction compensation value and a second correction compensation value based on a machining die cavity of the gantry machine tool device and a material thermal expansion coefficient of the ram assembly; and a parameter adjustment module configured to generate a casting precision control execution scheme by reversely analyzing an optimal casting parameter combination obtained through optimization into the segmented casting process parameters based on the first correction compensation value and the second correction compensation value, and collecting real-time monitoring data of each precision influence area in real time through an industrial Ethernet and performing online fine tuning on the casting parameter combination using a BP neural network.

[0015] In a third aspect, the application further provides an electronic device, comprising: at least one processor; a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the gantry machine tool ram integrated casting precision control method of any one of the first aspect.

[0016] One or more technical solutions provided in the application have at least the following beneficial effects:

[0017] By setting the segmented casting process parameters associated with the pouring area, feeding area and cooling adjustment area according to the structural characteristic parameters of the ram assembly of the gantry machine tool equipment, based on the machining mold cavity of the gantry machine tool equipment and the thermal expansion coefficient of the material of the ram assembly, the first correction compensation value and the second correction compensation value are obtained; based on the first correction compensation value and the second correction compensation value, the optimal casting parameter combination obtained by optimization is inversely analyzed into the segmented casting process parameters to generate a casting precision control execution scheme, real-time monitoring data of each precision influence area is collected in real time through industrial Ethernet, and online fine tuning of the casting parameter combination is performed by using a BP neural network. That is, by setting the segmented casting process parameters, obtaining the first correction compensation value based on full-size detection of the machining mold cavity, obtaining the second correction compensation value based on the thermal expansion coefficient of the material of the ram assembly, and performing online fine tuning based on the BP neural network, the casting precision of the gantry machine tool ram assembly is accurately controlled, and the casting precision is further optimized.

[0018] The above description is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, the specific embodiments of the present application can be implemented according to the content of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only exemplary, and other drawings can be obtained by those skilled in the art without creating laborious work on the basis of the provided drawings.

[0020] Figure 1 The flowchart of the gantry machine tool ram integrated casting precision control method of the present application.

[0021] Figure 2 The structural schematic diagram of the gantry machine tool ram integrated casting precision control system of the present application.

[0022] Figure 3 The structural schematic diagram of the exemplary electronic device of the present application.

[0023] Explanation of reference numerals: parameter setting module 11, compensation value obtaining module 12, parameter adjusting module 13, bus 300, receiver 301, processor 302, transmitter 303, memory 304, bus interface 305. DETAILED DESCRIPTION

[0024] The application provides a gantry machine tool ram integrated casting precision control method, system and device, solves the technical problem that the casting precision is unstable due to uneven residual stress distribution and uncontrolled shrinkage in the casting process in the prior art. By setting segmented casting process parameters, obtaining a first correction compensation value based on full-size detection of a machining mold cavity, obtaining a second correction compensation value based on the thermal expansion coefficient of the ram assembly, and performing online fine tuning based on a BP neural network, the casting precision of the gantry machine tool ram assembly is accurately controlled, and the casting precision is further optimized.

[0025] The technical solutions in the application will be described clearly and completely below with reference to the drawings. Obviously, the described embodiments are only a part of the embodiments of the application, rather than all the embodiments of the application. It should be understood that the application is not limited by the example embodiments described herein. Based on the embodiments of the application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the application. In addition, it should be noted that, for convenience of description, only parts related to the application are shown in the drawings, rather than all parts.

[0026] Embodiment one, please refer to the accompanying Figure 1 The application provides a gantry machine tool ram integrated casting precision control method, wherein the gantry machine tool ram integrated casting precision control method is executed by a gantry machine tool ram integrated casting precision control system, and the gantry machine tool ram integrated casting precision control method specifically comprises the following steps:

[0027] According to the structure characteristic parameters of the ram assembly of the gantry machine tool equipment, segmented casting process parameters associated with the pouring zone, the feeding zone and the cooling adjustment zone are set.

[0028] Specifically, before casting the gantry machine tool ram assembly, first, the structure characteristic parameters of the ram assembly are obtained, that is, the quantifiable parameters for describing the geometry and material characteristics of the ram, including overall shape size, wall thickness distribution, rib plate arrangement and thickness, hot spot position and modulus, material grade, chemical composition range, liquid density, liquidus / solidus temperature, linear expansion coefficient, etc. After obtaining the structure characteristic parameters of the ram, the thickness equivalent surface analysis and hot spot identification of the wall thickness and rib plate are performed, the modulus of each key position and the thickness transition position are calculated, and accordingly the casting is divided into the pouring zone, the feeding zone and the cooling adjustment zone. The total throttle area is inversely calculated according to the required volume flow, the total throttle section is arranged at the bottom of the sprue, and a non-pressure pouring system ratio such as 1:2:2 is used. A plurality of ingates are arranged in the pouring zone, so that the thin-walled rib plate is filled preferentially without slag entrapment.

[0029] The heat generating and heat preserving riser is arranged in the feeding area of the hot spot at the intersection of the main rail seat and the main rib according to the criterion that the riser modulus is greater than or equal to 1.2 times the hot spot modulus, and the neck of the riser is optimized to shorten the feeding channel and prolong the solidification time of the riser; in the cooling regulation area, the graphite / iron cold iron is attached to the thick part to accelerate heat dissipation, and the heat preservation felt is covered in the thin wall area to slow down the cooling, and meanwhile, the partition opening / tempering timing and the ventilation cooling rhythm are regulated to make the temperature drop curves of the areas tend to be consistent in the key time period, such as the end of solidification and the 400 to 600 ℃ over-temperature period.

[0030] The pouring area is the area where the mold filling and initial solidification mainly occur, which corresponds to the key area of the inner gate arrangement and the flow control of the molten iron; the feeding area is the area where the thick section and the hot spot are located, and the feeding area needs to be continuously fed by the riser (heat preservation / heat generating riser) to avoid shrinkage holes and shrinkage; the cooling regulation area is the area where the cooling rate and temperature drop curve of each part are "aligned" through the setting of cold iron, heat preservation cover layer, opening time, local heat insulation / heat conduction measures. The segmented casting process parameters refer to a set of parameters including the pouring temperature and time, the total throttle area and the ratio, the number and single area of the inner gate, the riser size and modulus, the neck size, the heat preservation / heat generating sleeve type, the cold iron material and specification, the sand / covered sand heat conduction grade, the opening and tempering timing, etc.

[0031] For example, if the shape of the ram is 1800mm long, 320mm wide and 280mm high; the wall thickness distribution includes thin wall ribs / shells of 35 to 40mm, and the intersection of the rail seat and the main rib is 90 to 110mm; the material is HT300 gray cast iron (linear expansion coefficient 10.5*10 -6 / K, liquidus about 1150 to 1180℃, liquid density 6900kg / m 3 ); the net weight is about 1050kg, and the total pouring amount is planned to be 1450kg (the estimated yield rate is about 72%). The pouring area parameters are as follows: the target mold filling time is 26s; the required mass flow is 1450 / 26≈55.8kg / s; the volume flow is 0.0081m 3 / s; the effective static pressure head of the pouring liquid surface is 0.60m, and the outflow coefficient is 0.62; the calculated total throttle area is 0.0081 / (0.62*3.43)≈0.00381m 2 (3810mm 2 ); the non-pressure ratio is 1:2:2, so the total area of the cross runner is about 7600mm 2 , the total area of the inner gate is about 7600mm 2 ; the number of inner gates is 6, and the single area is about 1260mm 2, which are distributed at the root of the thin-walled ribs, ensure smooth filling and inhibit slag entrapment; the pouring temperature is 1385℃, and the superheat of the molten iron is about 120℃. The parameters of the feeding zone: the hot spot of the guide rail seat is approximated as a 200*200*180mm block, the hot spot module is 32.1mm, and the riser module should be greater than or equal to 1.2 times the hot spot module, i.e. 38.6mm. A cylindrical heat-generating insulating riser with a size of 200*220mm is selected: the volume is 6.91*10 6 mm 3 ; the outer surface area without contact is 1.70*10 5 mm 2 ; the module is 40.8mm, which is greater than or equal to 38.6mm (satisfies); the number of risers is 2, which are symmetrically arranged, the riser neck is 60*35mm; the equivalent delay of the heat-generating sleeve is greater than or equal to 10min. The parameters of the cooling adjustment zone: 4 blocks of cast iron cold iron with a size of 200*100*25mm are attached to the thick part (transition of the main ribs / guide rail seat); 30mm ceramic fiber insulation felt is covered on the thin-walled area; the sand selected is furan resin sand, and the thermal conductivity coefficient is 0.8-1.0W / (m*K); the sand box is opened in sections for insulation for 3.5h, then the air inlet of the thin-walled area is opened, the sand box is opened in 5.0h, and the sand is removed in 7.0h; K-type thermocouples are arranged at the thin-walled T1, thick T2, and riser neck T3; the typical temperature drop obtained by monitoring is as follows: the thick T2 rises from 1385℃ to 1150℃, and the solidification is completed in 12min, then it drops to 720℃ (42min), and to 400℃ (155min); T1 (thin-walled): 1385℃ drops to 1150℃, solidifies in 8min, then drops to 720℃ (24min), and to 400℃ (98min); the ΔT=T2-T1 is about 46℃ at 120min, and the baseline test before optimization has a ΔT of about 95℃. The experimental results obtained by comparing with the baseline batch with unified parameters are as follows: the ultrasonic / ray shrinkage hole area ratio of the hot spot is 0.22%-0.06%; the flatness of the guide rail mounting surface after initial processing is 0.12mm-0.05mm; the dimensional deviation of the internal main rib end surface is ±0.35mm-±0.15mm; the residual bending after sand removal is 0.78mm-0.31mm.

[0032] By setting the segmented casting process parameters, the solidification process of the casting in each area is accurately controlled, thereby reducing the casting stress and deformation, and improving the dimensional accuracy and shape stability of the casting.

[0033] Based on the machining of the mold cavity of the gantry machine tool device and the thermal expansion coefficient of the material of the ram assembly, a first correction compensation value and a second correction compensation value are obtained.

[0034] Further, the application further comprises the following steps: based on the machining die cavity of the gantry machine tool equipment, combining the casting precision requirement, performing full-size detection on the cavity size, geometric and position tolerances, and obtaining a first correction compensation value; based on the segmented casting process parameters, using fluid dynamics to simulate and set the flow field distribution of the molten iron filling process, and obtaining the gate flow gradient parameters under the flow stability limitation.

[0035] Specifically, the machining die cavity is a cavity inside the casting die corresponding to the shape of the ram assembly, and its geometric size directly determines the outer dimension, surface precision and geometric and position tolerances of the casting product. The casting precision requirement is usually based on the functional requirements of the ram as a key component of the gantry machine tool, and includes the flatness of the guide rail mounting surface, the perpendicularity of the rib plate, the allowable deviation of the overall length, width and thickness dimensions, etc. The cavity size refers to the internal size of the die cavity, including length, width and height, which directly determines the size of the casting. The geometric and position tolerances refer to the shape and position tolerances of the die cavity, such as flatness and perpendicularity, which affect the shape and position accuracy of the casting. According to the casting precision requirement, full-size detection is performed on the cavity size, geometric and position tolerances, and a first correction compensation value is obtained. For example, full-size detection is performed on the ram cavity, such as measuring the actual length of the guide rail mounting surface as 1798.7 mm, while the design value is 1800.0 mm, with a deviation of −1.3 mm; the rib plate perpendicularity is measured as 0.12 mm, while the design tolerance is ≤0.08 mm, with an excess of 0.04 mm, and the first correction compensation value is +1.3 mm for the guide rail direction and −0.04 mm for the rib cavity inclination direction.

[0036] Based on the segmented casting process parameters, the flow field distribution of the molten iron filling process is simulated and set using fluid dynamics simulation software, and the velocity field, pressure field and temperature field are obtained through transient multiphase flow / thermal coupling calculation. The filling model is established in the fluid dynamics software, and the die cavity geometry, gate system, molten iron temperature, superheat and fluid properties are input. Through simulation, the gate flow gradient parameters under the flow stability limitation are obtained. For example, the initial simulation results show that the flow rates of the six gates differ greatly (0.63 to 1.12 m / s), and turbulent flow occurs in some areas, with a proportion of 6.8% of the slag entrapment risk area. By iteratively adjusting the inner gate area, the fast-flow gate is narrowed to 1100 mm 2 , and the slow-flow gate is widened to 1400 mm 2Finally, the flow gradient is uniformly distributed, the flow rate of each gate is between 0.75 and 0.92 m / s, the filling time is kept between 26 and 27 s, the area of the slag entrapment zone is reduced to 1.5%, and the gate flow gradient parameters that meet the flow stability limit are obtained. The gate flow gradient parameter is the distribution of the flow of each ingate during the filling process, which ensures stable flow of molten iron and avoids turbulence and slag entrapment. Through full-size detection and fluid dynamics simulation, the cavity size and shape tolerance during the casting process, as well as the flow state of the molten metal, are accurately controlled, which helps to reduce casting stress and deformation, and improves the dimensional accuracy and shape stability of the casting.

[0037] Further, the application also includes the following steps: based on the material thermal expansion coefficient of the ram assembly, combined with the historical casting shrinkage rate, the size shrinkage at different temperature stages during casting is dynamically deduced to obtain a second correction compensation value; based on the segmented casting process parameters, the ram assembly is set to be lightweight by topology optimization to obtain a thermal expansion compensation gap that meets the strength limit.

[0038] Specifically, the material thermal expansion coefficient is the linear expansion amount of the material when the temperature rises; the historical casting shrinkage rate refers to the empirical data of the size shrinkage of the casting during the cooling process under the same material and process conditions. Based on the material thermal expansion coefficient of the ram assembly, combined with the historical casting shrinkage rate, the size shrinkage at different temperature stages during casting is dynamically deduced, including the pouring temperature, the holding temperature, and the cooling critical temperature, the size change in each temperature interval is calculated segmentally, and a second correction compensation value is obtained. The second correction compensation value is the size correction amount calculated by the thermal expansion coefficient and the historical shrinkage rate, which is used to compensate the final size deviation of the casting after cooling.

[0039] Even if the size compensation is done, the casting will still deform unevenly when cooled at high temperature, especially at the junction of the rib plate and the guide rail, which is prone to cracking or internal stress concentration. Based on the segmented casting process parameters, the ram assembly is modeled and designed to be lightweight by topology optimization method. Topology optimization method is a structure optimization method based on finite element analysis, which removes unnecessary material areas to achieve lightweight and reasonable stress distribution. Through finite element analysis, the material in the area that is not important and bears little stress is removed, so that the weight of the casting is reduced, such as reducing the weight by 12%, and the stress path is more reasonable. At key positions, such as the connection between the rib plate and the guide rail, a gap of 0.3 to 0.5 mm is reserved, so that the metal does not expand together at high temperature, avoiding cracking. Lightweight setting refers to reducing the volume and weight of the casting as much as possible under the premise of meeting the strength and stiffness requirements, in order to improve the dynamic response performance of the machine tool. The thermal expansion compensation gap is a small space reserved in the design to ensure that the casting does not produce top dead, cracking or stress concentration when it displaces due to thermal expansion or shrinkage during high-temperature cooling.

[0040] By acquiring the second correction compensation value through dynamic deduction and applying the topology optimization method, the dimensional change in the casting process is accurately controlled, and the lightweight design of the ram assembly is realized, which helps to improve the dimensional accuracy of the casting, reduce the weight of the assembly, and improve the overall performance of the gantry machine tool.

[0041] Based on the first correction compensation value and the second correction compensation value, the optimal casting parameter combination obtained by optimization is inversely analyzed into the segmented casting process parameters to generate a casting precision control execution scheme. Real-time monitoring data of each precision influence area is collected in real time through industrial Ethernet, and online fine tuning of the casting parameter combination is performed using a BP neural network.

[0042] Further, the application further includes the following steps: constructing an associated mapping matrix through the first correction compensation value and the gate flow gradient parameter, and the second correction compensation value and the thermal expansion compensation gap; the matrix row dimension of the associated mapping matrix is the cavity size compensation element category associated with the first correction compensation value, the shape and position tolerance compensation element category, the high-temperature section shrinkage compensation element category associated with the second correction compensation value, and the phase change solidification compensation element category; the matrix column dimension of the associated mapping matrix is the precision influence area of the ram assembly, including the guide rail mounting surface of the casting area, the internal rib structure of the feeding area, and the end connecting seat of the cooling adjustment area.

[0043] Specifically, an associated mapping matrix is constructed according to the first correction compensation value and the gate flow gradient parameter, and the second correction compensation value and the thermal expansion compensation gap. That is, the first correction compensation value, the gate flow gradient parameter, the second correction compensation value, and the thermal expansion compensation gap are associated with the precision influence area of the ram assembly, which is used to quantify the influence intensity and direction of a certain element change on a certain precision area index.

[0044] The row dimension of the associated mapping matrix defines the element categories associated with different correction compensation values, including the cavity size compensation element category associated with the first correction compensation value, the shape and position tolerance compensation element category, the high-temperature section shrinkage compensation element category associated with the second correction compensation value, and the phase change solidification compensation element category. The cavity size compensation element category is related to the difference between the actual size and the design size of the mold, which refers to the influence of mold size correction, such as the adjustment of mold length, width, and height; the shape and position tolerance refers to the accuracy requirements of the surface shape and relative position of the casting, such as flatness and perpendicularity, and the shape and position tolerance compensation element category refers to the correction made to meet these accuracy requirements; during the casting process, the metal expands at high temperature and shrinks when cooled, so the shrinkage process needs to be compensated to avoid errors in the final size of the casting, i.e., the high-temperature section shrinkage compensation element category; during the solidification process of the metal, the volume changes (usually shrinks) when it changes from liquid to solid, and this process needs to be compensated, especially during the phase change stage, i.e., the phase change solidification compensation element category.

[0045] The cavity size compensation element category, the shape and position tolerance compensation element category, the high temperature section shrinkage compensation element category, and the phase change solidification compensation element category correspond to mold size correction, shape and position tolerance correction, thermal expansion correction, and phase change solidification correction, respectively. Each category will affect the accuracy of the casting in different areas, so they need to be quantified and a mapping relationship needs to be established.

[0046] The column dimension of the correlation mapping matrix corresponds to the accuracy influence area of the casting, that is, the parts in the casting that are affected by the casting process and need special attention. The matrix column dimension of the correlation mapping matrix is the accuracy influence area of the ram assembly, including the guide rail mounting surface of the pouring area, the internal rib structure of the feeding area, and the end connecting seat of the cooling adjustment area. The pouring area is the first part of the casting, the area where the molten iron flows in, and the guide rail mounting surface of the pouring area is an area with high accuracy requirements, and any dimensional error may affect the performance of the subsequent machine tool; the feeding area is mainly used to compensate for the voids or defects caused by shrinkage during the cooling process of the casting, and the internal rib structure of the feeding area needs to ensure the correct shape and size during feeding to maintain the stability of the casting; the end connecting seat of the cooling adjustment area bears the thermal stress and cooling speed influence during the cooling process of the casting, and has high accuracy requirements, especially when connected with other parts, it must maintain good shape and position tolerance.

[0047] The steps of constructing the correlation mapping matrix are as follows: through experimental design or simulation analysis, different correction compensation values (such as adjusting the cavity size or flow gradient) are given, and then the effects of these changes on the accuracy influence areas (such as guide rail surface, rib, connecting seat) of the casting are observed. Each modification will affect the size and shape and position tolerance of different areas. Through these modification data, an influence coefficient matrix is obtained, each row represents a correction compensation element, such as size compensation, flow gradient, thermal expansion compensation, etc.; each column represents an accuracy influence area, such as guide rail surface, rib, connecting seat, etc.; each element represents the influence degree of the row element on the accuracy of the column area, and the influence intensity is usually represented by a standardized value.

[0048] Further, the application further includes the following steps: based on the correlation mapping matrix, combining the casting accuracy requirements to perform optimization: taking the coupling influence coefficient of the correlation mapping matrix as the fitness function weight, and taking the flatness of the guide rail mounting surface of the ram assembly, the size deviation of the internal rib, and the shape and position tolerance of the end connecting seat as the optimization target.

[0049] Further, the application further comprises the following steps: taking the first correction compensation value and the gate flow gradient parameter, and the second correction compensation value and the value range of the thermal expansion compensation gap as the particle search space, iteratively optimizing by introducing an adaptive inertia weight, inputting the generated casting parameter combination of each round of optimization into the casting process simulation model for verification, and if the simulation verification result meets the casting precision requirement, outputting the current casting parameter combination as the optimal solution.

[0050] Further, the application further comprises the following steps: if not, locating the compensation element category with the highest deviation contribution degree based on the correlation mapping matrix, locally optimizing the particle search interval of the compensation element category with the highest deviation contribution degree, until the iteration number reaches a preset threshold; and inversely analyzing the optimal casting parameter combination obtained by optimization into the segmented casting process parameters to generate a casting precision control execution scheme including a dynamic flow adjustment curve of the pouring area, a stepped feeding scheme of the feeding area, and a partitioned temperature control strategy of the cooling adjustment area.

[0051] Specifically, by the correlation mapping matrix that has been constructed, optimization is performed in combination with the casting precision requirement, for adjusting different process parameters in the casting process, such as correction compensation values, flow gradients, and feeding gaps, so as to obtain a final product that meets the casting precision requirement. The casting precision requirement usually includes multiple aspects of precision control requirements, such as the planeness of the guide rail installation surface, the size deviation of the rib plate, and the shape and position tolerances of the end connecting seat, etc., to ensure that each key area of the casting meets the precision standard. By the correlation mapping matrix, the influence degree of different correction compensation values and process parameters on these precision requirements is quantified. The optimization process is to select the optimal correction compensation parameter according to the coupling influence coefficient.

[0052] The coupling influence coefficient is a specific value of each element in the correlation mapping matrix, representing the influence degree of a specific process parameter on the influence area of the casting precision, and is used in the fitness function for optimization to guide the optimization algorithm to adjust each process parameter. In the optimization process, the coupling influence coefficient acts as the weight of the fitness function for optimization. The fitness function is used to measure the goodness of the solution, and the higher the fitness, the better the solution. The goal of optimization is to make the key parts of the casting as much as possible to meet the precision requirements. The optimization target includes the flatness of the ram assembly corresponding to the guide rail mounting surface, the size deviation of the internal rib plate, and the shape and position tolerance of the end connecting seat. The flatness of the guide rail mounting surface is the maximum deviation of the casting guide rail mounting surface relative to the ideal plane. The flatness requirement is usually very strict because it directly affects the stability and accuracy of the machine tool. For example, the flatness of the guide rail mounting surface is controlled within 0.05mm / 1000mm. The size deviation of the internal rib plate refers to the deviation of the size of the internal rib plate of the casting relative to the design value. The size accuracy of the rib plate directly affects the structural strength and stability of the casting, and minimizing the size error of the rib plate ensures the functional and structural reliability of the casting. The shape and position tolerance of the end connecting seat refers to the shape and position tolerance of the end connecting seat of the casting, which is used to connect other parts, so the accuracy requirement is high. The shape and position tolerance such as perpendicularity and position must be controlled within the design standard range.

[0053] The fitness function will include the three targets of the guide rail surface flatness, the rib plate size deviation, and the end connecting seat shape and position tolerance, and each target has a corresponding weight (the weight is determined by the coupling influence coefficient of the correlation matrix). An example of the fitness function is f(x) = w1*flatness error + w2*rib plate size deviation + w3*connecting seat shape and position tolerance, where the weights w1, w2, and w3 are calculated by the coupling influence coefficient of the correlation mapping matrix, which represents the importance of each target in the optimization process.

[0054] To optimize the casting parameters, a particle swarm optimization algorithm is used to determine the value range of each process parameter. The particle search space is the value range of each process parameter (such as the first correction compensation value, the flow gradient, the second correction compensation value, and the thermal expansion compensation gap). In particle swarm optimization, the inertia weight controls the exploration and development ability of particles in the search process. A larger inertia weight helps particles quickly jump out of local optimal solutions, and a smaller inertia weight helps particles search for optimal solutions more finely. Adaptive inertia weight means that the inertia weight is dynamically adjusted according to the progress of the search as the iteration progresses. For example, in the early stage, particles need to search the space widely, so the inertia weight is larger; in the later stage, particles need to adjust locally more finely, so the inertia weight gradually decreases.

[0055] The objective of the particle swarm optimization is to find the best combination of casting process parameters that minimize (or maximize) these objective values according to the fitness function. In each round of optimization, the particles update their velocity and position based on the current parameter position and fitness value to find a better solution. The objective of each particle is to find an optimal combination of process parameters that minimizes the precision of the casting (such as flatness, dimensional deviation, etc.). After each round of optimization, the particle swarm generates new combinations of casting parameters, which are input into the simulation model of the casting process for verification.

[0056] If the simulation verification result meets the casting precision requirements, i.e., the flatness, dimensional deviation, and geometric tolerance meet the requirements, the current casting parameter combination is output as the optimal solution. The optimization process ends here. If the simulation verification fails, i.e., the target precision is not met, the optimization continues, focusing on the correction compensation elements with the highest contribution degree in the correlation mapping matrix, adjusting the value range of these process parameters, and performing local optimization. The compensation element category with the highest deviation contribution degree refers to any one or more of the following: the first correction compensation value associated with the cavity size compensation element category, the geometric tolerance compensation element category, the second correction compensation value associated with the high-temperature section shrinkage compensation element category, and the phase change solidification compensation element category. That is, when the global optimization does not find a solution that meets the precision requirements, the search range can be narrowed, and local optimization is a fine adjustment of the particle search interval to quickly find the optimal solution. For example, if the flow gradient has a greater impact on the guide rail surface flatness, adjusting the flow gradient can significantly improve the flatness.

[0057] Once the main process parameters that affect the precision are found, local optimization of their particle search interval can be performed, i.e., the search range is narrowed. For example, if the flow gradient of the sprue has a greater impact on the flatness, and the deviation of the flow is large, a more fine adjustment is made in the particle search interval of this parameter, so that the optimization process is more focused on improving the flatness.

[0058] If no parameter combination that meets the precision requirements is found after multiple optimization iterations, the compensation element category with the highest deviation contribution degree is located according to the correlation mapping matrix, such as a compensation value (such as the flow of the sprue) that has a significant impact on the flatness or dimensional error. Then, focus on adjusting that element. After each iteration, update the parameters and continue verification until the optimal solution is found or the maximum number of iterations is reached.

[0059] The optimal casting parameter combination has been repeatedly adjusted and simulated to ensure that it meets the casting precision requirements, including mold correction compensation values, gate flow gradient, shrinkage compensation, expansion compensation, etc. The optimal casting combination obtained by optimization is inversely analyzed into the segmented casting process parameters, which means that these theoretically optimal parameters are applied to the actual casting process parameters. For example, the optimal gate flow gradient parameter is converted into a specific flow regulation scheme, and the optimized compensation value of the feeding is converted into a specific scheme of the feeding area, and finally an operable casting precision control scheme is formed.

[0060] The dynamic flow regulation curve of the pouring area refers to the change curve of the flow in the pouring area during the casting process. The flow at the gate needs to be dynamically adjusted according to the specific needs of the casting, such as fine adjustment of the flow at different time points and in different areas according to the needs of the filling. The dynamic flow regulation curve is to adjust the flow at the gate in different time periods and in different areas according to the optimal casting parameter setting.

[0061] The casting will shrink during the cooling process, especially in the thick wall part. In order to compensate for this shrinkage, the feeding area uses a stepped scheme, that is, different feeding strategies are adopted at different temperature stages. The stepped feeding scheme of the feeding area controls the feeding amount in stages, reduces the deformation and defects of the casting, and the feeding is carried out at different temperature stages of the casting. The slower the cooling, the more uniform the shrinkage.

[0062] The cooling rate has an important influence on the quality, dimensional stability and surface quality of the casting. Due to the differences in shape, thickness and other factors, the cooling rate of different areas of the casting should also be different. The zoning temperature control strategy of the cooling regulation area sets different cooling rates according to the cooling needs of each area of the casting. For example, the pouring area and the feeding area may need slower cooling to prevent cracks caused by too fast temperature difference; while the cooling regulation area may need faster cooling to control the shape. Through inverse analysis, the optimized cooling regulation scheme is converted into the actual zoning temperature control strategy, including the temperature change curve of each area, the cooling speed, etc., to ensure that the cooling of the casting is controllable during the entire casting process.

[0063] All the optimized parameters and process strategies form a complete casting precision control execution scheme, which includes process parameters such as flow regulation, feeding, cooling, etc. in each area, for real-time monitoring and adjustment of the casting process to ensure that each process stage strictly follows the optimal process parameters, and to ensure that the final precision of the casting meets the requirements. Through the generated casting precision control execution scheme, the key areas of the casting such as the guide rail surface flatness, the rib plate size deviation and the connecting seat shape and position tolerance are effectively controlled, and the design precision requirements are met.

[0064] Further, the application further comprises the following steps: taking the parameter sensitivity of the correlation mapping matrix as the network input weight, and taking the difference value of the target value of the casting precision requirement as the network input layer variable; after completing each round of fine-tuning, the corrected casting parameter combination is substituted into the correlation mapping matrix for reverse verification to determine the deviation improvement rate of each precision influence area; if the deviation improvement rate is lower than the preset improvement rate threshold, the particle search interval of the compensation element category with the highest deviation contribution degree is locally optimized to search the expanded search space of the strong correlation edge between the compensation element category and each precision influence area.

[0065] Specifically, based on the optimized optimal casting parameter combination, the actual production segmented casting process parameters are reversely analyzed, which means that the optimized casting parameters will be converted into specific operation steps, such as generating a dynamic flow adjustment curve in the pouring area, generating a stepped feeding scheme in the feeding area, and developing a partitioned temperature control strategy in the cooling area. Real-time monitoring data of each precision influence area (such as guide rail surface, rib plate, connecting seat, etc.) during the casting process are collected in real time using industrial Ethernet, including flow, temperature, size, etc.

[0066] The real-time collected data are input into the BP neural network to optimize the casting process parameters through neural network fine-tuning. The input weight of the neural network is set by the parameter sensitivity of the correlation mapping matrix. In this way, the network can optimize and adjust different parameters, and perform online fine-tuning according to the result after each round of optimization. Parameter sensitivity refers to the degree of influence of different parameters on casting precision. The BP neural network will adjust the weight based on these sensitivities to guide the optimization process. By inputting the target value difference of the casting precision requirement, such as the difference between the current flatness and the target flatness, the neural network will fine-tune these casting parameters after each round of optimization to make them closer to the target precision.

[0067] After each round of fine-tuning is completed, the optimized casting parameters are input into the casting process simulation model for reverse verification. By substituting the optimized casting parameter combination into the correlation mapping matrix, it is confirmed whether the changes in these parameters have successfully improved the precision requirement. Specifically, the reverse verification will check whether the deviation of each precision area is reduced, such as guide rail surface, rib plate, connecting seat, etc. The simulation model will simulate the actual casting process to check whether the precision of the casting meets the target requirement. According to the corrected parameters, the deviation improvement rate of these areas is calculated. The deviation improvement rate is used to measure the improvement effect of the optimization result. If the precision after simulation verification meets the expected requirement, the deviation improvement rate will show the improvement degree of the error. For example, if the target precision is 0.05 mm and the flatness after fine-tuning is 0.03 mm, the deviation improvement rate is 40%.

[0068] If the deviation improvement rate exceeds the preset improvement rate threshold, it means that the current optimization has reached the expected accuracy target, and the optimization process can be terminated and the current optimal process parameters can be output. If the deviation improvement rate is lower than the preset improvement rate threshold, it means that the current optimization scheme is not sufficient to achieve the target accuracy. The particle swarm optimization algorithm will jump out of the global optimization range, locate the compensation element category with the highest deviation contribution, and perform local optimization on the particle search interval of the compensation element category. For example, if a certain compensation element (such as flow gradient) has the greatest impact on accuracy, the search interval of this parameter can be narrowed down for more precise adjustment, and the strong correlation edge between this compensation element category and the accuracy impact area can be expanded to achieve this. The key to local optimization is to narrow down the particle search interval to better explore and adjust these key process parameters and improve accuracy.

[0069] In local optimization, if fine-tuning of a certain compensation element still does not effectively improve accuracy, the search space will be expanded, i.e. the adjustment range of the compensation element will be increased, so as to explore more optimization schemes until the optimal solution is reached or the target accuracy is met. For example, if a certain compensation element has a strong correlation with a certain accuracy area, the search space will be expanded around these correlated parameters. During optimization, these expanded strong correlation edges are used to help find the optimal solution and ensure that the interactions between different process parameters are fully optimized. If the deviation improvement rate exceeds the preset threshold, the optimization process can be stopped. At this time, the optimized parameter combination will be used as the optimal solution, and the optimal solution will be inversely analyzed into the segmented casting process parameters, which will be finally applied to actual production. For example, assume that the initial optimization target is the guide rail mounting surface flatness and the rib plate size deviation, the first correction compensation value is +1.3 mm, the gate flow gradient is between 0.75 and 1.0 m / s, and the second correction compensation value is +19.5 mm. Through preliminary optimization, the guide rail surface flatness is 0.08 mm / 1000 mm, and the rib plate size deviation is ±0.14 mm. The deviation improvement rate is 25% (which does not meet the preset threshold of 30%). Since the gate flow gradient has the greatest impact on flatness, the particle search interval of the flow gradient is reduced from 0.75 to 1.0 m / s to 0.8 to 0.9 m / s. After local optimization, the guide rail surface flatness is improved to 0.05 mm / 1000 mm, and the rib plate size deviation is reduced to ±0.11 mm. The deviation improvement rate is 35%, which exceeds the preset 30% improvement rate threshold, and the optimization is completed, and the optimal solution is output. By using the BP neural network and particle swarm optimization, the casting process parameters are dynamically fine-tuned to ensure that the accuracy of the castings continuously approaches the target requirements. The guide rail surface flatness, rib plate size deviation, and connecting seat shape and position tolerances of the castings are effectively improved.

[0070] In summary, the gantry machine tool ram integrated casting precision control method provided by the present application has the following beneficial effects: by setting the segmented casting process parameters associated with the pouring zone, feeding zone and cooling adjustment zone according to the structural characteristic parameters of the ram assembly of the gantry machine tool equipment; based on the machining mold cavity of the gantry machine tool equipment and the thermal expansion coefficient of the material of the ram assembly, a first correction compensation value and a second correction compensation value are obtained; based on the first correction compensation value and the second correction compensation value, the optimal casting parameter combination obtained by optimization is inversely analyzed into the segmented casting process parameters to generate a casting precision control execution scheme, real-time monitoring data of each precision influencing area is collected in real time through industrial Ethernet, and online fine tuning of the casting parameter combination is performed using a BP neural network. That is, by setting the segmented casting process parameters, obtaining the first correction compensation value based on full-size detection of the machining mold cavity, obtaining the second correction compensation value based on the thermal expansion coefficient of the material of the ram assembly, and performing online fine tuning based on the BP neural network, the casting precision of the gantry machine tool ram assembly is accurately controlled, and the casting precision is further optimized.

[0071] In the second embodiment, based on the same inventive concept as the gantry machine tool ram integrated casting precision control method in the foregoing first embodiment, the present application also provides a gantry machine tool ram integrated casting precision control system, please refer to the accompanying drawings Figure 2 The gantry machine tool ram integrated casting precision control system comprises:

[0072] The parameter setting module 11 is configured to set segmented casting process parameters associated with the pouring zone, feeding zone and cooling adjustment zone according to the structural characteristic parameters of the ram assembly of the gantry machine tool equipment; the compensation value acquisition module 12 is configured to obtain a first correction compensation value and a second correction compensation value based on the machining mold cavity of the gantry machine tool equipment and the thermal expansion coefficient of the material of the ram assembly; and the parameter adjustment module 13 is configured to inversely analyze the optimal casting parameter combination obtained by optimization into the segmented casting process parameters based on the first correction compensation value and the second correction compensation value, generate a casting precision control execution scheme, collect real-time monitoring data of each precision influencing area in real time through industrial Ethernet, and perform online fine tuning of the casting parameter combination using a BP neural network.

[0073] Further, the gantry machine tool ram integrated casting precision control system is also configured to: based on the machining mold cavity of the gantry machine tool equipment, perform full-size detection on the cavity size and geometric tolerance in combination with the casting precision requirement to obtain a first correction compensation value; based on the segmented casting process parameters, simulate and set the flow field distribution of the molten iron filling process using fluid dynamics to obtain a gate flow gradient parameter that meets the flow stability limitation.

[0074] Further, the gantry machine tool ram integrated casting precision control system is further used for: based on the thermal expansion coefficient of the material of the ram assembly, combined with the historical casting shrinkage, the size shrinkage at different temperature stages in the casting process is dynamically deduced to obtain a second correction compensation value; based on the segmented casting process parameters, the ram assembly is set to be lightweight by using topology optimization to obtain a thermal expansion compensation gap that meets the strength limit.

[0075] Further, the gantry machine tool ram integrated casting precision control system is further used for: through the first correction compensation value and the gate flow gradient parameter, the second correction compensation value and the thermal expansion compensation gap, an association mapping matrix is constructed; the matrix row dimension of the association mapping matrix is the first correction compensation value associated cavity size compensation element category, shape and position tolerance compensation element category, the second correction compensation value associated including high temperature section shrinkage compensation element category, phase change solidification compensation element category, the matrix column dimension of the association mapping matrix is the precision influence area of the ram assembly, including the guide rail mounting surface of the casting area, the internal rib structure of the feeding area, and the end connecting seat of the cooling adjustment area.

[0076] Further, the gantry machine tool ram integrated casting precision control system is further used for: based on the association mapping matrix, combined with the casting precision requirement for optimization: taking the coupling influence coefficient of the association mapping matrix as the fitness function weight, taking the corresponding guide rail mounting surface flatness, internal rib size deviation and end connecting seat shape and position tolerance of the ram assembly as the optimization target.

[0077] Further, the gantry machine tool ram integrated casting precision control system is further used for: taking the value range of the first correction compensation value and the gate flow gradient parameter, and the second correction compensation value and the thermal expansion compensation gap as the particle search space, and iteratively optimizing by introducing an adaptive inertia weight, the casting parameter combination generated in each round of optimization is input into the casting process simulation model for verification, if the simulation verification result meets the casting precision requirement, the current casting parameter combination is output as the optimal solution.

[0078] Further, the gantry machine tool ram integrated casting precision control system is further used for: if not, based on the association mapping matrix, the compensation element category with the highest deviation contribution degree is located, the particle search interval of the compensation element category with the highest deviation contribution degree is locally optimized until the iteration number reaches a preset threshold; the optimal casting parameter combination obtained by optimization is inversely analyzed into the segmented casting process parameters to generate a casting precision control execution scheme including the dynamic flow adjustment curve of the casting area, the stepped feeding scheme of the feeding area and the partition temperature control strategy of the cooling adjustment area.

[0079] Further, the gantry machine ram integrated casting precision control system is further used for: taking the parameter sensitivity of the correlation mapping matrix as a network input weight, and taking a difference value between a target value of the casting precision requirement as a network input layer variable; after completing a round of fine tuning, substituting the corrected casting parameter combination into the correlation mapping matrix for reverse verification to determine a deviation improvement rate of each precision influence area; if the deviation improvement rate is lower than a preset improvement rate threshold, then jumping out of the local optimization of the particle search interval of the compensation element category with the highest deviation contribution degree to perform search space expansion on the strong correlation edge constructed between the compensation element category and each precision influence area as a bidirectional node.

[0080] Each embodiment in the specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments. Figure 1 The gantry machine ram integrated casting precision control method and specific examples in embodiment one are also applicable to the gantry machine ram integrated casting precision control system of the present embodiment. Through the foregoing detailed description of the gantry machine ram integrated casting precision control method, those skilled in the art can clearly understand the gantry machine ram integrated casting precision control system in the present embodiment. Therefore, in the interest of brevity, the gantry machine ram integrated casting precision control system in the present embodiment will not be described in detail.

[0081] In embodiment three, based on the same inventive concept as the gantry machine ram integrated casting precision control method in the foregoing embodiment one, the present application further provides an electronic device, which includes: at least one processor; a memory in communication connection with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the steps of the gantry machine ram integrated casting precision control method in any one of the foregoing embodiment one.

[0082] The accompanying drawings are Figure 3 The accompanying drawings are Figure 3In the depicted embodiment, a bus architecture is represented by bus 300, which can include any number of interconnecting buses and bridges needed to support various components of the system. Bus 300 can include a bus 300 that connects various circuits such as one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, and therefore, will not be described further. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 can be the same component, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 can be used for storing data used by processor 302 in executing operational processes.

[0083] The above description of disclosed embodiments provides enabling concepts for making or using the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0084] Obviously, many modifications and changes can be made to the application as set forth above without departing from the broader scope thereof as set forth in the appended claims. Accordingly, the specification is to be regarded in an illustrative rather than a restrictive sense.

Claims

1. A method for precision control in integrated casting of the slide block of a gantry milling machine, characterized in that, include: Based on the structural characteristic parameters of the slide assembly of the gantry milling machine, segmented casting process parameters associated with the casting zone, feeding zone and cooling adjustment zone are set. After obtaining the structural characteristic parameters of the slide assembly, the wall thickness and stiffeners are analyzed by thickness isosurface analysis and thermal point identification. The module and thickness transition position of each key part are calculated. Based on this, the casting is divided into the casting zone, feeding zone and cooling adjustment zone. The casting zone is the area where filling and initial solidification mainly occur, and it is the key area for the arrangement of the ingate and the control of the molten iron flow. The feeding zone is the area where thick sections and hot spots are located, and it needs to be continuously fed by the riser to avoid shrinkage cavities and porosity. The cooling regulation zone is the area where the cooling rate and temperature drop curve of each part are aligned by setting chills, heat insulation covering layers, the timing of opening risers, and local heat insulation / heat conduction measures. Based on the machining mold cavity of the gantry milling machine and the thermal expansion coefficient of the material of the slide assembly, a first correction compensation value and a second correction compensation value are obtained. Based on the first and second correction compensation values, the optimal casting parameter combination obtained by optimization is back-analyzed into the segmented casting process parameters to generate a casting precision control execution scheme. Real-time monitoring data of each precision-affected area is collected in real time through industrial Ethernet, and the casting parameter combination is fine-tuned online using a BP neural network.

2. The method for precision control of integrated casting of gantry milling machine slide as described in claim 1, characterized in that, Obtaining the first correction compensation value also includes: Based on the machining mold cavity of the gantry milling machine, and in combination with the casting precision requirements, the cavity size and geometric tolerances are fully inspected to obtain the first correction compensation value; Based on the segmented casting process parameters, fluid dynamics is used to simulate and set the flow field distribution during the molten iron filling process, and the gate flow gradient parameters that meet the flow stability constraints are obtained.

3. The method for precision control of integrated casting of gantry milling machine slide as described in claim 2, characterized in that, The method for precision control of integrated casting of gantry milling machine slide also includes: Based on the thermal expansion coefficient of the material of the slide assembly and combined with the historical casting shrinkage rate, the dimensional shrinkage at different temperature stages during the casting process is dynamically extrapolated to obtain a second correction compensation value. Based on the segmented casting process parameters, topology optimization is used to lighten the slide assembly and obtain a thermal expansion compensation gap that meets the strength requirements.

4. The method for precision control of integrated casting of gantry milling machine slide as described in claim 3, characterized in that, The method for precision control of integrated casting of the gantry milling machine slide includes: A correlation mapping matrix is ​​constructed by using the first correction compensation value and the gate flow gradient parameter, and the second correction compensation value and the thermal expansion compensation gap; The matrix row dimension of the correlation mapping matrix is ​​the cavity size compensation element category, the form and position tolerance compensation element category associated with the first correction compensation value, and the high temperature section shrinkage compensation element category and the phase change solidification compensation element category associated with the second correction compensation value. The matrix column dimension of the correlation mapping matrix is ​​the accuracy influence area of ​​the slide assembly, including the guide rail mounting surface of the casting area, the internal stiffening plate structure of the shrinkage compensation area, and the end connecting seat of the cooling adjustment area.

5. The method for precision control of integrated casting of gantry milling machine slide as described in claim 4, characterized in that, The method for precision control of integrated casting of the gantry milling machine slide includes: Based on the correlation mapping matrix, optimization is performed in conjunction with the casting accuracy requirements: the coupling influence coefficient of the correlation mapping matrix is ​​used as the fitness function weight, and the flatness of the guide rail mounting surface, the internal stiffener size deviation, and the end connection seat form and position tolerance of the slide assembly are taken as optimization targets.

6. The method for precision control of integrated casting of gantry milling machine slide as described in claim 5, characterized in that, The method for precision control of integrated casting of the gantry milling machine slide includes: The range of values ​​for the first correction compensation value and the gate flow gradient parameter, and the range of values ​​for the second correction compensation value and the thermal expansion compensation gap are used as the particle search space. Iterative optimization is performed by introducing adaptive inertia weights. The casting parameter combination generated in each round of optimization is input into the casting process simulation model for verification. If the simulation verification result meets the casting accuracy requirements, the current casting parameter combination is output as the optimal solution.

7. The method for precision control of integrated casting of gantry milling machine slide as described in claim 6, characterized in that, The method for precision control of integrated casting of the gantry milling machine slide includes: If not satisfied, the compensation element category with the highest deviation contribution is located based on the correlation mapping matrix, and the particle search interval of the compensation element category with the highest deviation contribution is locally optimized until the number of iterations reaches the preset threshold. The optimal casting parameter combination obtained through optimization is back-analyzed into the segmented casting process parameters to generate a casting accuracy control execution scheme that includes the dynamic flow adjustment curve of the casting zone, the stepped feeding scheme of the feeding zone, and the zoned temperature control strategy of the cooling adjustment zone.

8. The method for precision control of integrated casting of gantry milling machine slide as described in claim 7, characterized in that, A backpropagation (BP) neural network is used to fine-tune the casting parameter combination online, including: The parameter sensitivity of the aforementioned correlation mapping matrix is ​​used as the network input weight, and the difference between the target value and the casting accuracy requirement is used as the network input layer variable. After each round of fine-tuning, the corrected casting parameter combination is substituted into the correlation mapping matrix for reverse verification to determine the deviation improvement rate of each precision-affected area. If the deviation improvement rate is lower than the preset improvement rate threshold, then the particle search interval of the compensation element category with the highest deviation contribution is exited for local optimization, and the search space is expanded by constructing a strong correlation edge with the compensation element category and each accuracy influence area as bidirectional nodes.

9. A precision control system for integrated casting of the slide ram of a gantry milling machine, characterized in that, The step of implementing the gantry milling machine tool slide integrated casting precision control method according to any one of claims 1 to 8, wherein the gantry milling machine tool slide integrated casting precision control system comprises: The parameter setting module is used to set segmented casting process parameters associated with the casting zone, feeding zone and cooling adjustment zone based on the structural characteristic parameters of the slide assembly of the gantry machine tool. After obtaining the structural characteristic parameters of the slide assembly, the thickness isosurface analysis and thermal point identification are performed on the wall thickness and stiffeners. The module and thickness transition position of each key part are calculated, and the casting is divided into the casting zone, feeding zone and cooling adjustment zone accordingly. The casting zone is the area where filling and initial solidification mainly occur, and it is the key area for the arrangement of the ingate and the control of the molten iron flow. The feeding zone is the area where thick sections and hot spots are located, and it needs to be continuously fed by the riser to avoid shrinkage cavities and porosity. The cooling regulation zone is the area where the cooling rate and temperature drop curve of each part are aligned by setting chills, heat insulation covering layers, the timing of opening risers, and local heat insulation / heat conduction measures. The compensation value acquisition module is used to acquire a first correction compensation value and a second correction compensation value based on the machining mold cavity of the gantry milling machine and the thermal expansion coefficient of the material of the slide assembly. The parameter adjustment module is used to reverse analyze the optimal casting parameter combination obtained by optimization into the segmented casting process parameters based on the first correction compensation value and the second correction compensation value, generate a casting accuracy control execution scheme, collect real-time monitoring data of each accuracy-affected area through industrial Ethernet, and use a BP neural network to fine-tune the casting parameter combination online.

10. An electronic device, characterized in that, include: At least one processor; A memory that is communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the steps of the gantry milling machine slide integrated casting precision control method according to any one of claims 1 to 8.

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