A straightening jig and straightening method for a deformation-resistant computer metal alloy fitting

Abstract

The application relates to a shaping jig and shaping method for anti-deformation computer metal alloy accessories, and belongs to the field of computer metal alloy accessory processing, which is used for shaping metal alloy accessories. The shaping jig comprises a base plate, an aluminum alloy pressing block and a fixing piece. The shaping jig is used for pressing the metal alloy accessory through the pressing block and clamping the metal alloy accessory through the fixing piece, and then the metal alloy accessory is placed into an oven for baking. The oven is integrated with an AI temperature control system. The AI temperature control system comprises a sensing module and an algorithm module. The sensing module is used for collecting temperature data. The algorithm module generates a temperature regulation instruction according to the feedback data of the sensing module. The oven adjusts the temperature control parameters according to the temperature regulation instruction, so that the shaping of the metal alloy accessory can be realized, and the shaping precision and consistency are improved.

Description

Technical Field

[0001] This application relates to the field of computer metal alloy parts processing, and in particular to a shaping fixture and shaping method for anti-deformation computer metal alloy parts. Background Technology

[0002] With the rapid development of electronic devices towards thinner, lighter, stronger, and more precise designs, the application of computer metal alloy parts is becoming increasingly widespread. The processing of computer metal alloy parts is a complex process involving multiple collaborative steps. The original metal alloy material is die-cast into a blank. The blank is then de-sprued to remove excess material and burrs generated during the die-casting process. After de-spruing, the blank undergoes preliminary shaping to correct macroscopic deformations that occurred during die-casting. It then enters the precision machining stage, where multi-faceted milling and precision drilling are used to machine the required mounting holes, assembly surfaces, slots, and other precision structures for the parts. After machining, the surface of the parts is polished and ground to remove machining marks, improve surface finish, and meet appearance requirements. Finally, after passing appearance inspection and dimensional inspection to confirm that the parts meet design standards, they can be shipped.

[0003] In related technologies, in the above processing steps, for metal alloy parts that still have residual stress after die casting and preliminary shaping, and for slight deformation caused by stress release after finishing, a baking process is usually added to release the residual stress inside the parts, correct the slight deformation, and ensure the dimensional stability of the parts. The baking process is usually as follows: the metal alloy parts to be baked are placed in the oven using a fixture.

[0004] However, metal alloys have the characteristics of high thermal expansion coefficient and strong thermoplasticity. During the baking process, the temperature rise will cause the metal alloy parts to thermally expand. After the metal alloy parts are baked and cooled, they are prone to irregular deformation, which can reduce the processing yield of metal alloy parts, increase the loss of metal alloy raw materials and production costs, and also affect the subsequent assembly of metal alloy parts, increasing processing steps and processing costs. Summary of the Invention

[0005] To address the aforementioned issues, this application provides a shaping fixture and shaping method for anti-deformation computer metal alloy parts.

[0006] The present application provides a shaping fixture and shaping method for anti-deformation computer metal alloy parts, which adopts the following technical solution: including a base plate, a plurality of holding blocks and a plurality of fixing members. The base plate is used to support and position the metal alloy parts to be shaped. The holding blocks are placed above the base plate and are used to apply downward holding force to a portion of the metal alloy parts. The fixing members are used to detachably fix the metal alloy parts, the holding blocks and the base plate into one unit.

[0007] By adopting the above technical solution, the metal alloy parts to be shaped are supported and positioned by the substrate, ensuring that the metal alloy parts maintain a stable initial position during the baking process. Several holding blocks are set above the substrate, applying downward holding force to specific areas of the metal alloy parts. Combining the high thermal expansion coefficient and strong thermoplasticity of the metal alloy, when the baking temperature rises and the metal alloy parts undergo thermal expansion, the holding blocks form precise pressure constraints on specific areas of the metal alloy parts, causing the thermal expansion of the metal alloy parts to proceed in a preset reasonable direction. At the same time, several fasteners detachably fix the metal alloy parts, holding blocks, and substrate into one unit, ensuring that the holding force acts continuously and evenly on the metal alloy parts throughout the baking and cooling process. This ensures that the metal alloy parts are subjected to balanced forces during the thermal expansion stage, and during the cooling stage, the metal alloy parts can gradually solidify under the holding constraint, reducing stress concentration during thermal expansion, thereby reducing irregular deformation of the metal alloy parts after baking and cooling, improving the processing yield of the metal alloy parts, reducing metal alloy raw material loss and production costs, ensuring the dimensional accuracy of the metal alloy parts, and reducing the overall processing cost.

[0008] Preferably, it also includes an oven, the base plate is provided with at least one limiting post and a hook, the limiting post is used to limit the placement position of the metal alloy parts, the hook is used to suspend the inner cavity of the oven, the base plate is also provided with a positioning hole, and some of the pressing blocks are provided with positioning posts, the positioning posts and the positioning holes are inserted into each other.

[0009] By adopting the above technical solution, at least one limiting post on the substrate can limit the placement position of the metal alloy parts, ensuring that the metal alloy parts are placed in the same position each time. This ensures that the pressing block can accurately act on a specific area of ​​the metal alloy parts. The hook on the substrate can be suspended in the inner cavity of the oven, allowing the substrate, along with the metal alloy parts and the pressing block, to be suspended inside the oven. This allows all parts of the metal alloy parts to come into contact with a uniform baking temperature, improving the heat uniformity of the metal alloy parts during the baking process. The positioning holes on the substrate can be inserted and matched with the positioning posts on some of the pressing blocks, enabling the precise installation of the pressing blocks on the substrate and ensuring that the installation position of the pressing blocks meets the preset requirements.

[0010] Preferably, the substrate is provided with an array of perforated structures.

[0011] By adopting the above technical solution, the substrate is set with an array of hollow structures, which can increase the circulation area of ​​hot air in the oven, reduce the heat blockage of the substrate on the bottom of the metal alloy parts, and allow hot air to contact the metal alloy parts through the hollow areas, thereby improving the overall heating uniformity of the metal alloy parts and helping to release the residual stress inside the metal alloy parts evenly. The evenly distributed hollow design reduces the heat accumulation of the substrate itself while ensuring the structural strength of the substrate, making the surface temperature distribution of the substrate more uniform and further improving the heating consistency of the metal alloy parts.

[0012] Preferably, the shape of the pressing block is adapted to the shape of the local pressing area of ​​the metal alloy fitting, and the pressing block is provided with an installation indicator mark, which is used to indicate the correct installation direction of each pressing block.

[0013] By adopting the above technical solution, the shape of the pressing block is adapted to the shape of the local pressing area of ​​the metal alloy part, so that the pressing block and the local pressing area of ​​the metal alloy part are fully fitted, increasing the contact area, making the pressing force applied by the pressing block to the metal alloy part more uniform, improving the shaping effect of the metal alloy part, reducing the deformation that may occur after baking, and the installation indicator marks set on the pressing block can clearly indicate the correct installation direction of each pressing block, making it convenient for operators to quickly identify and complete the installation of the pressing block, ensuring that the installation direction of each pressing block meets the preset requirements.

[0014] Preferably, the method includes the following steps: S1: Positioning the metal alloy component to be shaped on the substrate using the limiting post; S2: Connecting the positioning posts of several pressing blocks with the positioning holes to allow the pressing blocks to partially press the metal alloy component; S3: Fixing the metal alloy component, the pressing blocks, and the substrate together to form an assembly using several fixing members; S4: Baking the assembly in an oven to reduce the stress of the metal alloy component and correct the deformation by utilizing the thermoplastic deformation characteristics of the metal alloy component at the baking temperature.

[0015] By adopting the above technical solution, the positioning posts and positioning holes of several pressing blocks are connected and engaged, enabling the pressing blocks to accurately correspond to specific areas of the metal alloy parts and achieve local pressing. This allows the pressing force to be applied precisely and evenly to the parts that need to be shaped. Several fasteners are used to fix the metal alloy parts, pressing blocks, and substrate into an assembly, ensuring that the position of the pressing blocks does not shift during the subsequent baking process and guaranteeing the effectiveness of the pressing constraint. The assembly is then placed in an oven for baking. By utilizing the thermoplastic deformation characteristics of the metal alloy parts at the baking temperature, the residual stress inside the metal alloy parts is gradually released and reduced, thereby correcting the deformation of the metal alloy parts. This achieves precise shaping of the metal alloy parts and improves the standardization and efficiency of clamping and shaping.

[0016] Preferably, the oven integrates an AI temperature control system, which includes a sensing module and an algorithm module. The sensing module is used to collect the ambient temperature inside the oven and the surface temperature of the pressing block. The algorithm module is used to generate temperature control commands based on the feedback data from the sensing module. The oven adjusts the temperature control parameters according to the temperature control commands.

[0017] By adopting the above technical solution, the sensing module can collect the ambient temperature inside the oven and the surface temperature of the pressing block in real time, providing accurate basic data support for temperature control. The algorithm module receives the temperature data fed back by the sensing module and analyzes and processes it, thereby generating a temperature control command adapted to the current baking conditions. The oven dynamically adjusts its own temperature control parameters according to the temperature control command, so that the ambient temperature inside the oven and the surface temperature of the pressing block are kept within a reasonable range suitable for the baking and shaping of the metal alloy parts, while improving the uniformity of temperature distribution inside the oven, so that the various parts of the metal alloy parts are heated more evenly.

[0018] Preferably, the sensing module includes a first temperature acquisition element and a second temperature acquisition element. The inner cavity of the oven is provided with at least five sets of first temperature acquisition elements, and each of the pressing blocks is provided with a second temperature acquisition element. The first temperature acquisition element and the second temperature acquisition element are electrically connected to the algorithm module.

[0019] By adopting the above technical solution, at least five sets of first temperature acquisition devices installed in the oven cavity can collect ambient temperature data of different areas of the oven cavity, realizing multi-directional monitoring of the temperature distribution of the oven cavity. The second temperature acquisition device installed on the surface of each pressing block can directly collect the temperature data of the pressing block surface, indirectly reflecting the actual temperature of the specific area where the metal alloy parts are pressed. Both the first and second temperature acquisition devices are electrically connected to the algorithm module, which can transmit the collected multi-dimensional temperature data to the algorithm module in real time, providing the algorithm module with accurate temperature monitoring data support. This allows the algorithm module to accurately grasp the temperature distribution of the oven cavity and the temperature changes in key areas of the metal alloy parts, thereby generating temperature control commands that are more in line with the actual baking conditions.

[0020] Preferably, the algorithm module includes a temperature prediction unit, which integrates a three-dimensional unsteady-state heat conduction heat transfer model and combines it with a long short-term memory network. The temperature prediction unit is used to predict the temperature change trend and global temperature field distribution of the inner cavity of the oven and the surface of the pressure block through the data of the sensing module.

[0021] By adopting the above technical solution, the temperature prediction unit included in the algorithm module integrates a three-dimensional unsteady-state heat conduction heat transfer model and combines it with a long short-term memory network. Relying on the physical prior constraints provided by the three-dimensional unsteady-state heat conduction heat transfer model and the temporal data learning capability of the long short-term memory network, it can accurately predict the temperature change trend and global temperature field distribution of the oven cavity and the surface of the pressure block. This allows the algorithm module to grasp the temperature dynamics during the baking process in advance and provide a scientific basis for subsequent temperature control.

[0022] Preferably, the algorithm module further includes a dynamic control unit, which integrates a data-driven optimization model and a thermal structure coupling model. The data-driven optimization model uses deep reinforcement learning as a solver and interacts with the finite element simulation based on the thermal structure coupling model. The temperature field distribution and temperature change trend output by the temperature prediction unit serve as the core input of the thermal structure coupling model. Based on the analysis results of the finite element simulation, the dynamic control unit integrates the data from the temperature prediction unit to generate multi-objective optimized process parameters, and adjusts the temperature control parameters of the oven based on the multi-objective optimized process parameters.

[0023] By adopting the above technical solution, the dynamic control unit integrates a data-driven optimization model and a thermal structure coupling model. It uses deep reinforcement learning as the solver and interacts with the finite element simulation based on the thermal structure coupling model. It can rely on the accurate temperature field distribution and temperature change trend output by the temperature prediction unit as the core input. The thermal structure coupling model simulates the stress-strain response, plastic deformation, and residual stress relaxation process of metal alloy parts under the constraint of the shaping fixture, quantifying the shaping effect under different process parameters. The data-driven optimization model then integrates temperature evolution data based on the simulation results to generate multi-objective optimized process parameters that take into account the shaping effect of metal alloy parts, energy consumption, and time cost. Based on these parameters, the temperature control parameters of the oven are adjusted to make the temperature distribution inside the oven more uniform and the temperature change more in line with the thermoplastic deformation characteristics of the metal alloy, thereby improving the accuracy and consistency of the shaping of metal alloy parts and improving dimensional accuracy and flatness.

[0024] Preferably, the algorithm module further includes a self-iterative optimization unit, which is used to associate the data of the temperature prediction unit and the dynamic control unit in each oven baking process and feed them back to the algorithm module to optimize the parameters of the algorithm module.

[0025] By adopting the above technical solution, the self-iterative optimization unit correlates the data from the temperature prediction unit and the dynamic control unit during each oven baking process and feeds them back to the algorithm module. This allows the parameters of the algorithm module to be continuously optimized based on actual production data, improving the accuracy and robustness of the temperature prediction unit in predicting the temperature change trend of the oven cavity and the surface of the holding block. It also enhances the adaptability and rationality of the multi-objective optimized process parameters generated by the dynamic control unit, allowing the overall performance of the AI ​​temperature control system to continuously improve with the increase of production batches, and helping to continuously improve the accuracy and consistency of the metal alloy parts shaping.

[0026] In summary, this application includes at least one of the following beneficial technical effects: 1. Several fasteners detachably fix the metal alloy parts, the holding block and the base plate into one unit, ensuring that the holding force is continuously and evenly applied to the metal alloy parts throughout the baking and cooling process. This makes the metal alloy parts subjected to balanced forces during the thermal expansion stage. During the cooling stage, the metal alloy parts can gradually take shape under the holding constraint, reducing stress concentration generated during thermal expansion, thereby reducing irregular deformation of the metal alloy parts after baking and cooling, and improving the processing yield of the metal alloy parts. 2. By interlocking the positioning pins and positioning holes of several pressing blocks, the pressing blocks can accurately correspond to specific areas of the metal alloy parts and achieve local pressing. This allows the pressing force to be applied precisely and evenly to the parts that need to be shaped. Several fasteners fix the metal alloy parts, pressing blocks, and substrate into an assembly, ensuring that the position of the pressing blocks does not shift during the subsequent baking process, thus ensuring the effectiveness of the pressing constraint. The assembly is then placed in an oven for baking. By utilizing the thermoplastic deformation characteristics of the metal alloy parts at the baking temperature, the residual stress inside the metal alloy parts is gradually released and reduced, thereby correcting the deformation of the metal alloy parts. 3. The sensing module can collect the ambient temperature inside the oven and the surface temperature of the pressing block in real time, providing accurate basic data support for temperature control. The algorithm module receives the temperature data fed back by the sensing module and analyzes and processes it, thereby generating a temperature control command adapted to the current baking conditions. The oven dynamically adjusts its own temperature control parameters according to the temperature control command, so that the ambient temperature inside the oven and the surface temperature of the pressing block are kept within a reasonable range suitable for the baking and shaping of the metal alloy parts, while improving the uniformity of temperature distribution inside the oven, so that the various parts of the metal alloy parts are heated more evenly. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the structure of Embodiment 1 of this application.

[0028] Figure 2 This is a schematic diagram of the structure of Embodiment 1 of this application.

[0029] Figure 3 This is a schematic diagram of the structure of Embodiment 1 of this application.

[0030] Figure 4 This is a schematic diagram of the structure of the substrate and the pressure blocks at the left and right ends in Embodiment 1 of this application.

[0031] Figure 5 This is a location diagram of the first temperature acquisition element in Embodiment 2 of this application.

[0032] Figure 6 This is a system block diagram in Embodiment 2 of this application.

[0033] Explanation of reference numerals in the attached drawings: 1. Base plate; 11. Limiting post; 12. Hook; 13. Hollow structure; 14. Positioning hole; 2. Holding block; 21. Installation indicator; 22. Positioning post; 23. Second temperature acquisition element; 3. Fixing element; 4. Metal alloy fitting; 5. Oven; 51. First temperature acquisition element. Detailed Implementation

[0034] The following is in conjunction with the appendix Figure 1-6 This application will be described in further detail.

[0035] This application discloses a shaping fixture and shaping method for anti-deformation computer metal alloy parts, used to shape metal alloy parts 4. In this application, it is used to shape a magnesium alloy keyboard frame.

[0036] Example 1: Refer to Figure 1 This embodiment provides a shaping fixture for anti-deformation computer metal alloy parts 4, including a base plate 1, several holding blocks 2 and several fixing members 3. In this embodiment, there are four holding blocks 2 and four fixing members 3. The holding blocks 2 are made of aluminum alloy, and the fixing members 3 are dovetail clips. The four fixing members 3 correspond one-to-one with the four holding blocks 2 and are in direct contact, which is used to detachably fix the metal alloy parts 4, the holding blocks 2 and the base plate 1 into a whole to form a stable assembly, ensuring that the position of the holding blocks 2 does not shift during the entire baking and cooling process, and the holding force is continuously and evenly applied to the metal alloy parts 4.

[0037] Reference Figure 1 , Figure 2 as well as Figure 3 Furthermore, the substrate 1 serves as the supporting base of the fixture, used to support and position the metal alloy parts 4 to be shaped. The substrate 1 has a rectangular structure, and four limiting posts 11 are provided on the surface of the substrate 1. The four limiting posts 11 are respectively provided at the upper and lower ends of the substrate 1, with two limiting posts 11 at each end. The two limiting posts 11 at each end are arranged parallel to each other. The magnesium alloy keyboard bracket has a pre-set groove, in which the two limiting posts 11 at the upper end cooperate with the groove to form a positioning, and cooperate with the two limiting posts 11 at the lower end to abut against the side wall of the magnesium alloy keyboard bracket to form a limiting. The four limiting posts 11 can position the metal alloy parts 4 to ensure that the clamping position is consistent each time.

[0038] Furthermore, the four pressing blocks 2 are located on the left, right, top, and bottom of the substrate 1 respectively, according to the structural characteristics of the magnesium alloy keyboard bracket. The pressing blocks 2 are made of aluminum alloy, which has good thermal conductivity, allowing heat to be evenly transferred to the pressing area of ​​the metal alloy accessory 4. The metal alloy accessory 4 helps to release stress evenly. The shape of the pressing surface of the pressing block 2 is adapted to the shape of the local pressing area of ​​the metal alloy accessory 4.

[0039] Meanwhile, the left and right pressure blocks 2 are responsible for pressing the left and right sides of the magnesium alloy keyboard bracket and positioning it through the positioning post 22. The two pressure blocks 2 located above and below are directly placed on specific areas of the magnesium alloy keyboard bracket. The four pressure blocks 2 work together to apply a uniform downward pressing force to specific deformation-sensitive areas of the magnesium alloy keyboard bracket, so that the thermal expansion of the magnesium alloy keyboard bracket during the baking process proceeds in a preset direction. At the same time, each pressure block 2 has an installation indicator mark 21 on its surface, which can indicate the correct installation direction of each pressure block 2.

[0040] Reference Figure 4 In addition, a positioning post 22 is provided at both ends of the bottom of the two pressing blocks 2 located in the left and right directions, and a positioning hole 14 is provided at the corresponding position of the substrate 1. The positioning post 22 and the positioning hole 14 can be inserted and matched one by one to ensure the installation accuracy of the two pressing blocks 2 on the substrate 1, and at the same time improve the fit between the two pressing blocks 2 and the magnesium alloy keyboard bracket, ensuring that the pressing force can be evenly applied to the corresponding area of ​​the magnesium alloy keyboard bracket.

[0041] Furthermore, a hook 12 is also provided on the substrate 1. The hook 12 is located on the side wall of the substrate 1 near the upper limit post 11. The substrate 1, together with the clamped metal alloy parts 4 and the pressure block 2, can be suspended in the inner cavity of the oven 5 to improve the uniformity of heating. The substrate 1 adopts an array-type hollow structure 13. The hollow structure 13 is circular. The hollow structure 13 can increase the flow area of ​​hot air in the oven 5 and reduce the heat blockage of the bottom of the magnesium alloy keyboard bracket by the substrate 1, so that the hot air can contact the bottom of the magnesium alloy keyboard bracket through the hollow area and improve the overall uniformity of heating of the parts.

[0042] The implementation principle of a shaping fixture for anti-deformation computer metal alloy parts 4 in this application embodiment is as follows: First, the four limiting posts 11 on the substrate 1 form a double positioning structure by adapting and cooperating with the groove of the magnesium alloy keyboard bracket at the upper end and by abutting and limiting the side wall of the magnesium alloy keyboard bracket at the lower end, ensuring that the placement position of the bracket is accurate and consistent each time it is clamped, laying a stable foundation for subsequent pressure constraint; Second, the four pressure blocks 2 are distributed on the left, right, upper and lower positions of the substrate 1 according to the corresponding area of ​​the magnesium alloy keyboard bracket. The left and right pressure blocks 2 are connected to the positioning posts 22 and the positioning holes 14 to ensure installation accuracy and fit. The upper and lower pressure blocks 2 are directly placed on specific areas of the magnesium alloy keyboard bracket. The four pressure blocks 2 work together to apply a uniform downward pressure force to the bracket. At the same time, the pressure blocks 2 are made of aluminum alloy, which has good thermal conductivity and can transfer heat evenly to the pressure area, guiding the thermal expansion of the magnesium alloy keyboard bracket in the baking process in a preset direction; Furthermore, the four fixing parts 3 are in one-to-one contact with the holding blocks 2 to ensure that the position of the holding blocks 2 does not shift during the entire baking and cooling cycle, and the holding force is continuously and stably applied to the support. The hook 12 of the base plate 1 is designed for suspension and the array-type hollow structure 13 can increase the hot air circulation area inside the oven 5, reduce heat obstruction, and improve the overall heating uniformity of the support. Finally, under the hot environment of the oven 5, the thermoplastic deformation of the magnesium alloy keyboard support is gradually released under the positioning constraint and holding guidance of the fixture, thereby correcting the deformation and improving the flatness and dimensional accuracy of the support.

[0043] Example 2: This example provides a shaping method for anti-deformation computer metal alloy parts 4, based on the shaping fixture of Example 1. The specific steps are as follows: Reference Figure 3 First, the metal alloy component 4 to be shaped is placed on the surface of the substrate 1, so that the two limiting posts 11 at the upper end of the substrate 1 fit with the groove structure of the magnesium alloy keyboard bracket. At the same time, the two limiting posts 11 at the lower end of the substrate 1 abut against the side wall of the magnesium alloy keyboard bracket to form an auxiliary limiting, ensuring that the magnesium alloy keyboard bracket is placed in a precise and consistent position.

[0044] Secondly, the positioning posts 22 at both ends of the bottom of the two pressing blocks 2 located in the left and right directions are inserted into the positioning holes 14 on the substrate 1 one by one, and the two pressing blocks 2 located in the up and down directions are placed directly on the specific area of ​​the magnesium alloy keyboard bracket, so that the four pressing blocks 2 work together to apply a uniform local pressing force to the corresponding area of ​​the magnesium alloy keyboard bracket.

[0045] Next, take four dovetail clips as fixing parts 3 and make contact with the four clamping blocks 2 one by one. The metal alloy parts 4, clamping blocks 2 and substrate 1 are fixed together by the four fixing parts 3 to form a stable assembly, ensuring that the metal alloy parts 4, clamping blocks 2 and substrate 1 are reliably connected during the subsequent baking process.

[0046] Finally, the assembly is placed in oven 5, the oven temperature is set to 240℃, and the baking time is 30 minutes. By utilizing the thermoplastic deformation characteristics of the metal alloy at this baking temperature, the residual stress inside the magnesium alloy keyboard bracket is gradually released and reduced, thereby correcting the deformation.

[0047] Reference Figure 5 and Figure 6Furthermore, the oven 5 integrates an AI temperature control system, which includes a sensing module and an algorithm module. The sensing module is equipped with a first temperature acquisition element 51 and a second temperature acquisition element 23. Both the first temperature acquisition element 51 and the second temperature acquisition element 23 are set as temperature acquisition sensors. The inner cavity of the oven 5 is provided with at least five sets of first temperature acquisition elements 51. In this embodiment, the inner cavity of the oven 5 is provided with five sets of first temperature acquisition elements 51, which are respectively arranged above, below, to the left, to the right and on the side away from the opening of the oven 5. This can realize temperature monitoring of the entire space of the inner cavity of the oven 5, eliminate blind spots in local temperature monitoring, and ensure that the collected ambient temperature data can fully reflect the temperature distribution state inside the oven 5. Each pressing block 2 surface is provided with a second temperature acquisition element 23. The second temperature acquisition element 23 is used to collect the temperature of the surface of the pressing block 2, indirectly reflecting the actual temperature of the metal alloy parts 4. The first temperature acquisition element 51 and the second temperature acquisition element 23 are both electrically connected to the algorithm module.

[0048] Furthermore, the algorithm module includes a temperature prediction unit, a dynamic control unit, and a self-iterative optimization unit. The temperature prediction unit integrates a three-dimensional unsteady-state heat conduction heat transfer model and combines it with a long short-term memory network. Relying on the physical prior constraints provided by the heat transfer model, it predicts the temperature change trend of the inner cavity of the oven 5 and the surface of the pressure block 2, providing a scientific basis for control.

[0049] Specifically, the governing equations of the three-dimensional unsteady heat conduction and heat transfer model of the temperature prediction unit are:

[0050] Wherein, T represents the temperature field inside the oven 5 and the metal alloy components. And K represents the density, specific heat capacity, and thermal conductivity of the metal alloy component 4 as a function of temperature. For the heat source term of the oven, the three-dimensional unsteady thermal conductivity model provides physical prior constraints for the long short-term memory network.

[0051] This demonstrates that the governing equations of the three-dimensional unsteady heat conduction and transfer model can describe the evolution of the temperature field inside the oven 5 and the metal alloy parts 4 over time and space. Combining the density, specific heat capacity, and thermal conductivity of the metal alloy parts 4 with temperature changes, as well as the heat source term of the oven 5, the model truly reflects the physical process of heat conduction of the metal alloy parts 4 during baking. This model provides physical prior constraints for the long short-term memory network, allowing the learning process of the long short-term memory network to conform to the real heat transfer law, improving the accuracy and robustness of the temperature prediction unit in predicting the temperature change trend of the inner cavity of the oven 5 and the surface of the pressure block 2. The accurate temperature change trend prediction provides more reliable temperature data support for the dynamic control unit, allowing the multi-objective optimized process parameters generated by the dynamic control unit to better fit the thermoplastic deformation characteristics of the metal alloy parts 4, and helping to uniformly release the residual stress inside the metal alloy parts 4.

[0052] Correspondingly, the dynamic control unit integrates a data-driven optimization model, uses deep reinforcement learning as the solver, and interacts with the finite element simulation based on the thermal structure coupling model. The temperature prediction unit integrates a three-dimensional unsteady heat conduction heat transfer model and combines it with a long short-term memory network to predict the temperature change trend and global temperature field distribution of the inner cavity of oven 5 and the surface of the pressure block 2, which serve as the core temperature field input of the thermal structure coupling model.

[0053] Furthermore, the thermal-structural coupling model adopts a temperature-dependent elastoplastic constitutive model to describe the stress and strain response of the magnesium alloy keyboard bracket during heating, holding, and cooling processes. Under the driving force of the temperature field, the static equilibrium equation is solved to obtain the stress and strain fields. Then, the plastic deformation and residual stress relaxation process of the magnesium alloy keyboard bracket under the constraint of the shaping fixture due to the obstruction of thermal expansion and the yielding of the alloy material are simulated through finite element analysis. Based on the analysis results and the data provided by the temperature prediction unit, the dynamic control unit generates multi-objective optimized process parameters that take into account the shaping effect of the metal alloy parts 4, energy consumption, and time cost. Based on the multi-objective optimized process parameters, the temperature control parameters of the oven 5 are adjusted. The temperature control parameters are the heating power and hot air circulation parameters, so that the temperature distribution in the oven 5 is more uniform and the temperature change is more in line with the thermoplastic deformation characteristics of the metal alloy.

[0054] Furthermore, the objective function of the data-driven optimization model is:

[0055] As a weighting factor, FlatnessError corresponds to the flatness error of the metal alloy part 4 after shaping, Energy corresponds to the energy consumption during the baking process in the oven 5, and Time corresponds to the time cost during the baking process in the oven 5. Therefore, FlatnessError, corresponding to the flatness error of the metal alloy part 4 after shaping, directly reflects whether the shaping effect meets the standard. The weighting factor corresponding to FlatnessError is... It will be set to the highest weight to prioritize the flatness accuracy after correction during the optimization process. Energy refers to the energy consumption during the baking process of oven 5, and Time corresponds to the time cost during the baking process of oven 5. These are cost and efficiency indicators in the production process and are the targets for auxiliary optimization.

[0056] Meanwhile, the objective function of the data-driven optimization model takes the flatness error of the metal alloy parts after shaping as the core optimization objective, while also considering the energy consumption and time cost during the baking process, through weighting coefficients. The dynamic adjustment balances the priority of multi-objective optimization, enabling the data-driven optimization model to generate multi-objective optimization process parameters that adapt to different production needs. This provides the dynamic control unit with accurate decision-making basis, allowing the dynamic control unit to adjust the heating power and hot air circulation parameters of oven 5, thereby improving the accuracy and consistency of the metal alloy parts 4 shaping, optimizing the energy consumption and processing efficiency of the baking process, further improving the processing yield of metal alloy parts 4, and reducing the loss of metal alloy raw materials and production costs.

[0057] Correspondingly, the governing equations of the thermal-structural coupling model are: Under the drive of the temperature field T, the static equilibrium equations are: Where F is the volume force dominated by thermal stress, and is determined by the strain decomposition formula. The global stress field of the magnesium alloy keyboard bracket was calculated. With strain field Furthermore, through finite element analysis, the plastic deformation and residual stress relaxation process of the magnesium alloy keyboard bracket under the constraint of the straightening fixture due to the obstruction of thermal expansion and the yielding of the alloy material were simulated, and the straightening effect corresponding to different temperature process parameters was quantified.

[0058] Correspondingly, the self-iterative optimization unit associates the data from the temperature prediction unit and the dynamic control unit during each baking process. In this embodiment, the self-iterative optimization unit is based on the Bayesian optimization framework. By establishing a proxy model between process parameters and calibration result indicators, it continuously searches and updates the optimal hyperparameter set of the algorithm module and feeds it back to the algorithm module, continuously optimizing the parameters of the algorithm module, improving the overall performance of the AI ​​temperature control system, and making the calibration effect of the magnesium alloy keyboard bracket continuously improve with the increase of production batches.

[0059] The implementation principle of the method for straightening a deformation-resistant computer metal alloy accessory 4 in this application embodiment is as follows: The straightening fixture of Embodiment 1 is used to precisely position and multi-directionally press and constrain the magnesium alloy keyboard bracket to be straightened. The bracket to be straightened is positioned by the groove of the upper and lower limit posts 11 of the base plate 1 engaging with the side wall to achieve dual positioning. Then, four pressing blocks 2 apply uniform pressing force in a coordinated manner according to the left, right, upper, and lower directions. The left and right pressing blocks 2 ensure installation accuracy and fit through the insertion of the positioning posts 22 and the positioning holes 14. The upper and lower pressing blocks 2 are directly placed in a specific area of ​​the bracket. Subsequently, four... The fastener 3 secures the magnesium alloy keyboard bracket, the pressure block 2, and the substrate 1 into a stable assembly, ensuring continuous and stable pressure constraint during baking. Then, the assembly is placed in a 240℃ oven 5 and baked for 30 minutes. The AI ​​temperature control system integrated in the oven 5 enables intelligent control of the thermal environment. The sensing module collects the ambient temperature through five sets of first temperature acquisition devices 51 deployed throughout the cavity of the oven 5, and collects the temperature of the pressure block 2 through the second temperature acquisition devices 23 on the surface of each pressure block 2, indirectly reflecting the actual temperature of the magnesium alloy keyboard bracket. The multi-dimensional temperature data is then transmitted to the algorithm module.

[0060] The temperature prediction unit within the algorithm module integrates a three-dimensional unsteady heat conduction and heat transfer model with a long short-term memory network. It uses the governing equations of the heat transfer model to describe the spatiotemporal evolution of the temperature field and provides physical prior constraints, improving the accuracy of the long short-term memory network in predicting the temperature change trend and global temperature field distribution of the oven 5 cavity and the pressure block 2. This prediction result serves as the core input to the thermal structure coupling model. The dynamic control unit uses deep reinforcement learning as the solver and interacts with the finite element simulation based on the thermal structure coupling model. It solves the stress and strain fields of the support through a temperature-related elastoplastic constitutive model and static equilibrium equations, simulating the plastic deformation and residual stress relaxation process of the magnesium alloy keyboard support under the constraint of the shaping fixture, caused by thermal expansion resistance, material yielding, and the resulting stress relaxation. Then, based on a multi-objective optimization function that optimizes flatness error as the core objective while considering energy consumption and time cost, it generates optimal process parameters through dynamic adjustment of weight coefficients. This, in turn, adjusts the heating power and hot air circulation parameters of the oven 5, making the temperature distribution within the oven 5 more closely match the thermoplastic deformation characteristics of the support.

[0061] Meanwhile, the self-iterative optimization unit, based on the Bayesian optimization framework, associates the data of the temperature prediction unit and the dynamic control unit during each baking process, establishes a proxy model of process parameters and correction results, continuously optimizes the hyperparameter set of the algorithm module, and improves the performance of the AI ​​temperature control system. Finally, under the precise constraint of the fixture and the uniform thermal environment controlled by AI, the magnesium alloy keyboard bracket gradually releases the internal residual stress through thermoplastic deformation, thereby achieving deformation correction.

[0062] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A shaping jig for anti-deformation computer metal alloy parts, characterized in that: The device includes a substrate (1), several holding blocks (2) and several fasteners (3). The substrate (1) is used to support and position the metal alloy fitting (4) to be shaped. The holding blocks (2) are placed above the substrate (1) and are used to apply a downward holding force to a portion of the metal alloy fitting (4). The fasteners (3) are used to detachably fix the metal alloy fitting (4), the holding blocks (2) and the substrate (1) together.

2. The shaping fixture for anti-deformation computer metal alloy parts according to claim 1, characterized in that: It also includes an oven (5), the base plate (1) is provided with at least one limiting post (11) and a hook (12), the limiting post (11) is used to limit the placement position of the metal alloy part (4), the hook (12) is used to suspend it in the inner cavity of the oven (5), the base plate (1) is also provided with a positioning hole (14), and some of the pressing blocks (2) are provided with positioning posts (22), the positioning posts (22) are inserted into the positioning holes (14).

3. The shaping fixture for anti-deformation computer metal alloy parts according to claim 1, characterized in that: The substrate (1) is provided with an array of hollow structures (13).

4. The shaping fixture for anti-deformation computer metal alloy parts according to claim 1, characterized in that: The shape of the pressing block (2) is adapted to the shape of the local pressing area of ​​the metal alloy fitting (4). The pressing block (2) is provided with an installation indicator (21), which is used to indicate the correct installation direction of each pressing block (2).

5. A method for straightening anti-deformation computer metal alloy parts, comprising a straightening fixture for anti-deformation computer metal alloy parts as described in claims 1 to 4, characterized in that: Includes the following steps: S1: Position the metal alloy part (4) to be shaped on the substrate (1) by the limiting post (11); S2: Connect the positioning post (22) of several pressing blocks (2) with the positioning hole (14) so ​​that the pressing block (2) locally presses the metal alloy part (4); S3: Fix the metal alloy part (4), the pressing block (2) and the substrate (1) as a whole by several fixing members (3) to form an assembly; S4: Place the assembly in an oven (5) for baking, and use the thermoplastic deformation characteristics of the metal alloy part (4) at the baking temperature to reduce the stress of the metal alloy part (4) to correct the deformation.

6. The method for straightening computer metal alloy parts for resisting deformation according to claim 5, characterized in that: The oven (5) integrates an AI temperature control system, which includes a sensing module and an algorithm module. The sensing module is used to collect the ambient temperature inside the oven (5) and the surface temperature of the pressing block (2). The algorithm module is used to generate temperature control commands based on the feedback data from the sensing module. The oven (5) adjusts the temperature control parameters according to the temperature control commands.

7. The method for straightening anti-deformation computer metal alloy parts according to claim 6, characterized in that: The sensing module includes a first temperature acquisition element (51) and a second temperature acquisition element (23). The inner cavity of the oven (5) is provided with at least five sets of first temperature acquisition elements (51). Each pressing block (2) surface is provided with a second temperature acquisition element (23). The first temperature acquisition element (51) and the second temperature acquisition element (23) are electrically connected to the algorithm module.

8. The method for straightening computer metal alloy parts for resisting deformation according to claim 6, characterized in that: The algorithm module includes a temperature prediction unit, which integrates a three-dimensional unsteady heat conduction heat transfer model and combines it with a long short-term memory network. The temperature prediction unit is used to predict the temperature change trend and global temperature field distribution of the inner cavity of the oven (5) and the surface of the pressure block (2) through the data of the sensing module.

9. The method for straightening computer metal alloy parts for resisting deformation according to claim 8, characterized in that: The algorithm module also includes a dynamic control unit, which integrates a data-driven optimization model and a thermal structure coupling model. The data-driven optimization model uses deep reinforcement learning as a solver and interacts with the finite element simulation based on the thermal structure coupling model. The temperature field distribution and temperature change trend output by the temperature prediction unit serve as the core input of the thermal structure coupling model. Based on the analysis results of the finite element simulation, the dynamic control unit integrates the data from the temperature prediction unit to generate multi-objective optimized process parameters and adjusts the temperature control parameters of the oven (5) based on the multi-objective optimized process parameters.

10. The method for straightening anti-deformation computer metal alloy parts according to claim 9, characterized in that: The algorithm module further includes a self-iterative optimization unit, which is used to associate the data of the temperature prediction unit and the dynamic control unit in each baking process of the oven (5) and feed them back to the algorithm module to optimize the parameters of the algorithm module.

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