Aluminum alloy wheel hub low-pressure casting multi-process parameter optimization method

Abstract

The invention discloses a low-pressure casting multi-process parameter optimization method for an aluminum alloy wheel hub, and relates to the technical field of low-pressure casting of automobile hubs. The low-pressure casting multi-process parameter optimization method for the aluminum alloy wheel hub comprises the following steps: establishing a three-dimensional model of the aluminum alloy wheel hub; setting initial production process parameters; performing numerical simulation in the low-pressure casting process; analyzing mold key point temperature distribution; according to the temperature distribution, production process parameters are adjusted; the steps are repeatedly executed, the production process parameters are further optimized, and an optimal process parameter combination is obtained; acquiring and analyzing actual production data and constructing a model; and performing process parameter optimization by using a dynamic multi-target particle swarm. According to the method, optimization and real-time recommendation of equipment control process parameters can be achieved, it is ensured that the casting in production is free of casting defects, the casting quality is improved, intelligent optimization and recommendation of the production equipment process parameters are achieved, the experiment trial-manufacturing cost is effectively reduced, the production period is shortened, the production efficiency is accelerated, and the method is worthy of being popularized and used in the industry.

Description

Technical Field

[0001] The invention relates to the technical field of automobile wheel hub low-pressure casting, and in particular to a method for optimizing multiple process parameters of low-pressure casting of an aluminum alloy wheel hub. Background Art

[0002] During the low-pressure casting process of aluminum alloy wheel hubs, the temperature control of the mold is one of the key factors affecting the quality of the casting. Factors such as the number of cooling channels, cooling medium (water cooling or air cooling), and cooling channel flow rate will have an important impact on the temperature of key points of the mold, which in turn affects the internal structure and surface quality of the casting, causing major problems for the casting. However, the relevant parameters affecting the mold temperature have not been effectively controlled. Therefore, optimizing the various process parameters in the low-pressure casting process is of great significance to improving the overall performance of the wheel hub casting.

[0003] Therefore, in view of the problems existing in the prior art, the designers of this case, relying on their many years of experience in this industry, actively researched and improved, and thus came up with the present invention, a method for optimizing multiple process parameters for low-pressure casting of aluminum alloy wheel hubs. Summary of the invention

[0004] The purpose of the present invention is to provide a method for optimizing multiple process parameters of low-pressure casting of aluminum alloy wheel hubs in view of the defects in the prior art that, during low-pressure casting of aluminum alloy wheel hubs, the temperature control of the mold directly affects the quality of the casting, while the relevant parameters affecting the mold temperature cannot be effectively controlled.

[0005] To achieve the purpose of the present invention, the present invention provides a method for optimizing multiple process parameters of low-pressure casting of an aluminum alloy wheel hub, the method comprising:

[0006] Execute step S1: establish a three-dimensional model of the aluminum alloy wheel hub, wherein the three-dimensional model contains information including the geometric shape and size of the aluminum alloy wheel hub;

[0007] Execute step S2: set initial production process parameters, wherein the initial production process parameters include the number of cooling channels, the type of cooling medium, and the flow rate of cooling channels;

[0008] Execute step S3: perform numerical simulation of the low-pressure casting process, use computer-aided software, input aluminum alloy material properties, casting temperature, mold preheating temperature, and perform numerical simulation of the low-pressure casting process;

[0009] Execute step S4: analyze the temperature distribution of key points of the mold, observe the isolated liquid phase area and temperature distribution of the aluminum alloy wheel hub according to the simulated porosity defects and temperature distribution results, adjust the initial production process parameters such as the casting temperature of the aluminum alloy wheel hub and the mold preheating temperature, and use the process parameters with the lowest simulated aluminum alloy wheel hub casting defects for actual production;

[0010] Execute step S5: adjust the production process parameters according to the temperature distribution;

[0011] Execute step S6: repeat steps S3 to S5 to further optimize the production process parameters and obtain the optimal process parameter combination;

[0012] Execute step S7: actual production data collection and analysis and model building;

[0013] Execute step S8: use dynamic multi-objective particle swarm to optimize process parameters.

[0014] Optionally, in step S1, the three-dimensional model is established using SolidWorks or UG modeling software.

[0015] Optionally, in step S2, structural features of the aluminum alloy wheel hub are determined according to on-site production, and 17 cooling channels are set.

[0016] Optionally, in step S2, the type of cooling medium is at least one of water cooling or air cooling.

[0017] Optionally, in step S2, the cooling channel flow rate is 8 to 10 L / min when the cooling medium is water-cooled, and 60 to 80 L / min when air-cooled. 3 L / h.

[0018] Optionally, in step S5, if the regional temperature is too high, the number of cooling channels is increased or the flow rate of the cooling channels is increased; if the cooling effect is not good, the cooling medium is replaced, such as changing from air cooling to water cooling; if the temperature distribution is uneven, the position of the cooling channels is adjusted or the distribution of the cooling channel flow rate is adjusted.

[0019] Optionally, in step S6, the optimal process parameter combination has the characteristics of uniform temperature distribution at key points of the mold, moderate temperature gradient, and high cooling efficiency.

[0020] Optionally, in step S7, low-pressure casting is carried out using the initially set production process parameters, thermocouples are set at key points of the mold, the process parameters of the equipment and the key point temperatures of the mold are collected during the production process, and the collected process parameters are used to construct the relationship between the opening and closing time of the mold cooling channel, the cooling channel flow rate and the key point temperature of the mold. According to the time series characteristics of the collected parameters, an LSTM time series prediction model is constructed.

[0021] Optionally, in step S8, after constructing the LSTM time series prediction model, the temperatures of key points of each mold of a qualified casting are taken as the key point temperatures of the standard mold, and the process parameters such as the cooling channel are initialized as initial particles, which are input into the constructed LSTM model to obtain the predicted temperatures of the key points of each mold, and the absolute value of the difference between the predicted temperature of each key point and the standard temperature is taken as the objective function of the dynamic multi-objective particle swarm, so as to find the various process parameters of the cooling channel and obtain multiple process parameters of the optimized low-pressure casting of the aluminum alloy wheel hub.

[0022] In summary, the method for optimizing multiple process parameters for low-pressure casting of aluminum alloy wheel hubs of the present invention can not only optimize and recommend the equipment control process parameters in the production process of low-pressure castings of aluminum alloy wheel hubs in real time, ensure that the castings being produced are free of casting defects and improve the quality of castings, but also realize intelligent optimization and recommendation of production equipment process parameters, effectively reduce experimental trial production costs, shorten production cycles, and accelerate production efficiency. At the same time, the method for optimizing multiple process parameters for low-pressure casting of aluminum alloy wheel hubs of the present invention is particularly suitable for low-pressure casting production of aluminum alloy wheel hubs, and can also be promoted and applied to other types of casting production processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 The figure is a flow chart of the multi-process parameter optimization method for low-pressure casting of an aluminum alloy wheel hub of the present invention;

[0024] Figure 2 It is a schematic diagram of the multi-process parameter optimization method of low-pressure casting of aluminum alloy wheel hub of the present invention;

[0025] Figure 3 The three-dimensional model of the aluminum alloy wheel hub of the present invention is shown;

[0026] Figure 4 Shown is a test diagram for determining initial production process parameters based on orthogonal simulation results;

[0027] Figure 5 The figure shows the block diagram of LSTM time series prediction model construction;

[0028] Figure 6 The figure shows the flow chart of LSTM time series prediction model construction and process parameter recommendation algorithm. Specific embodiments

[0029] The technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all of the embodiments. Based on the embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0030] See also Figure 1 , Figure 2 , Figure 1 Shown is a flow chart of the multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hub of the present invention. Figure 2 The figure shows a schematic diagram of a method for optimizing multiple process parameters of low-pressure casting of an aluminum alloy wheel hub according to the present invention. The method for optimizing multiple process parameters of low-pressure casting of an aluminum alloy wheel hub comprises:

[0031] Execute step S1: establish a three-dimensional model of an aluminum alloy wheel hub;

[0032] See also Figure 3 , Figure 3 The three-dimensional model of the aluminum alloy wheel hub of the present invention is shown. The three-dimensional model can be established using SolidWorks or UG modeling software. The information contained in the three-dimensional model includes but is not limited to the geometric shape and size of the aluminum alloy wheel hub.

[0033] Execute step S2: set initial production process parameters;

[0034] The initial production process parameters include the number of cooling channels, the type of cooling medium, and the cooling channel flow rate. More specifically, 17 cooling channels are set according to the structural characteristics of the aluminum alloy wheel hub determined by on-site production. The type of cooling medium is at least one of water cooling or air cooling. The cooling channel flow rate is 8 to 10 L / min when the cooling medium is water cooling, and 60 to 80 L / min when air cooling is used. 3 / h.

[0035] Executing step S3: performing numerical simulation of low pressure casting process;

[0036] Without limitation, the low pressure casting process was numerically simulated using Huazhu CAE computer-aided software, inputting A356.2 aluminum alloy material properties, casting temperature, and mold preheating temperature.

[0037] Execute step S4: analyze the temperature distribution of key points of the mold;

[0038] See also Figure 4 , Figure 4 The figure shows the test diagram of the initial production process parameters determined by the orthogonal simulation results. According to the simulation results of the loose holes and temperature distribution, the isolated liquid phase area and temperature distribution of the aluminum alloy wheel hub are observed, and the initial production process parameters such as the casting temperature and mold preheating temperature of the aluminum alloy wheel hub are adjusted. The process parameters with the lowest defects in the simulated aluminum alloy wheel hub casting are used in actual production.

[0039] Execute step S5: adjust the production process parameters according to the temperature distribution;

[0040] More specifically, if the regional temperature is too high, the number of cooling channels is increased or the flow rate of the cooling channels is increased; if the cooling effect is not good, the cooling medium is replaced, such as changing from air cooling to water cooling; if the temperature distribution is uneven, the position of the cooling channels is adjusted or the distribution of the cooling channel flow is adjusted.

[0041] Execute step S6: repeat steps S3 to S5 to further optimize the production process parameters and obtain the optimal process parameter combination;

[0042] The optimal process parameter combination has the characteristics of uniform temperature distribution at each key point of the mold, moderate temperature gradient, and high cooling efficiency. Based on this, it is determined that the first stage filling pressure is 0.02MPa, which lasts for 10s; the second stage filling pressure is 0.035MPa, which lasts for 30s; the third stage filling pressure is 0.095MPa, which lasts for 40s; and 0.095MPa is used for subsequent holding pressure; the initial die casting temperature is 695-705℃, and the solidification time is 125s-135s.

[0043] Execute step S7: actual production data collection and analysis and model building;

[0044] See also Figure 5 , Figure 5 The figure shows the construction block diagram of the LSTM time series prediction model. The low-pressure casting is carried out using the initially set production process parameters, and thermocouples are set at the key points of the mold to collect the process parameters of the equipment and the key point temperature of the mold during the production process. The collected process parameters are used to build the relationship between the mold cooling channel opening and closing time, cooling channel flow and the key point temperature of the mold. According to the time series characteristics of the collected parameters, the LSTM time series prediction model is built;

[0045] Execute step S8: use dynamic multi-objective particle swarm to optimize process parameters.

[0046] See also Figure 6 , Figure 6 The figure shows the flow chart of the LSTM time series prediction model construction and process parameter recommendation algorithm. After the LSTM time series prediction model is constructed, the temperature of each key point of the mold of the qualified casting is used as the standard mold key point temperature, and the process parameters such as the cooling channel are initialized as the initial particles, which are input into the constructed LSTM model to obtain the predicted temperature of each key point of the mold. The absolute value of the difference between the predicted temperature of each key point and the standard temperature is used as the objective function of the dynamic multi-objective particle swarm to find the various process parameters of the cooling channel and obtain multiple process parameters of the optimized aluminum alloy wheel hub low-pressure casting.

[0047] As a person skilled in the art, it is easy to know that the aluminum alloy wheel hub low-pressure casting multi-process parameter optimization method of the present invention can not only realize the optimization and real-time recommendation of the equipment control process parameters in the aluminum alloy wheel hub low-pressure casting production process, ensure that the castings being produced have no casting defects and improve the quality of the castings, but also realize the intelligent optimization and recommendation of the production equipment process parameters, effectively reduce the experimental trial production cost, shorten the production cycle, and accelerate the improvement of production efficiency. At the same time, the aluminum alloy wheel hub low-pressure casting multi-process parameter optimization method of the present invention is particularly suitable for the low-pressure casting production of aluminum alloy wheel hubs, and can also be promoted and applied to other types of casting production processes.

[0048] In summary, the method for optimizing multiple process parameters for low-pressure casting of aluminum alloy wheel hub of the present invention can not only optimize and recommend the equipment control process parameters in the production process of low-pressure casting of aluminum alloy wheel hub in real time, ensure that the castings being produced are free of casting defects, and improve the quality of castings, but also realize intelligent optimization and recommendation of production equipment process parameters, effectively reduce the cost of experimental trial production, shorten the production cycle, and accelerate the improvement of production efficiency. At the same time, the method for optimizing multiple process parameters for low-pressure casting of aluminum alloy wheel hub of the present invention is particularly suitable for low-pressure casting production of aluminum alloy wheel hub, and can also be extended to other types of casting production processes. Those skilled in the art should understand that various modifications and variations can be made to the present invention without departing from the spirit or scope of the present invention. Therefore, if any modification or variation falls within the scope of protection of the attached claims and equivalents, it is considered that the present invention covers these modifications and variations.

Claims

1. A method for optimizing multiple process parameters of low-pressure casting of aluminum alloy wheel hub, characterized in that: The method for optimizing multiple process parameters of low-pressure casting of an aluminum alloy wheel hub comprises: Execute step S1: establish a three-dimensional model of the aluminum alloy wheel hub, wherein the three-dimensional model contains information including the geometric shape and size of the aluminum alloy wheel hub; Execute step S2: set initial production process parameters, wherein the initial production process parameters include the number of cooling channels, the type of cooling medium, and the flow rate of cooling channels; Execute step S3: perform numerical simulation of the low-pressure casting process, use computer-aided software, input aluminum alloy material properties, casting temperature, mold preheating temperature, and perform numerical simulation of the low-pressure casting process; Execute step S4: analyze the temperature distribution of key points of the mold, observe the isolated liquid phase area and temperature distribution of the aluminum alloy wheel hub according to the simulated porosity defects and temperature distribution results, adjust the initial production process parameters such as the casting temperature of the aluminum alloy wheel hub and the mold preheating temperature, and use the process parameters with the lowest simulated aluminum alloy wheel hub casting defects for actual production; Execute step S5: adjust the production process parameters according to the temperature distribution; Execute step S6: repeat steps S3 to S5 to further optimize the production process parameters and obtain the optimal process parameter combination; Execute step S7: actual production data collection and analysis and model building; Execute step S8: use dynamic multi-objective particle swarm to optimize process parameters.

2. The method for optimizing multiple process parameters of low-pressure casting of aluminum alloy wheel hub according to claim 1, characterized in that: In step S1, the three-dimensional model is established by using SolidWorks or UG modeling software.

3. The method for optimizing multiple process parameters of low-pressure casting of aluminum alloy wheel hub according to claim 1, characterized in that: In step S2, the structural features of the aluminum alloy wheel hub are determined according to on-site production, and 17 cooling channels are set.

4. The method for optimizing multiple process parameters of low-pressure casting of aluminum alloy wheel hub according to claim 1, characterized in that: In step S2, the type of cooling medium is at least one of water cooling and air cooling.

5. The method for optimizing multiple process parameters of low-pressure casting of aluminum alloy wheel hub according to claim 1, characterized in that: In step S2, the cooling channel flow rate is 8-10 L / min when the cooling medium is water-cooled, and 60-80 L / min when air-cooled. 3 / h.

6. The method for optimizing multiple process parameters of low-pressure casting of aluminum alloy wheel hub according to claim 1, characterized in that: In step S5, if the regional temperature is too high, the number of cooling channels is increased or the flow rate of the cooling channels is increased; if the cooling effect is not good, the cooling medium is replaced, such as changing from air cooling to water cooling; if the temperature distribution is uneven, the position of the cooling channels is adjusted or the distribution of the cooling channel flow rate is adjusted.

7. The method for optimizing multiple process parameters of low-pressure casting of aluminum alloy wheel hub according to claim 1, characterized in that: In step S6, the optimal process parameter combination has the characteristics of uniform temperature distribution at key points of the mold, moderate temperature gradient, and high cooling efficiency.

8. The method for optimizing multiple process parameters of low-pressure casting of aluminum alloy wheel hub according to claim 1, characterized in that: In step S7, low-pressure casting is carried out using the initially set production process parameters, thermocouples are set at key points of the mold, and the process parameters of the equipment and the key point temperatures of the mold are collected during the production process. The collected process parameters are used to construct the relationship between the opening and closing time of the mold cooling channel, the cooling channel flow rate and the key point temperature of the mold. According to the time series characteristics of the collected parameters, an LSTM time series prediction model is constructed.

9. The method for optimizing multiple process parameters of low-pressure casting of aluminum alloy wheel hub according to claim 1, characterized in that: In step S8, after constructing the LSTM time series prediction model, the temperatures of the key points of each mold of the qualified casting are taken as the key point temperatures of the standard mold, and the process parameters such as the cooling channel are initialized as the initial particles, which are input into the constructed LSTM model to obtain the predicted temperatures of the key points of each mold. The absolute value of the difference between the predicted temperature of each key point and the standard temperature is taken as the objective function of the dynamic multi-objective particle swarm, so as to find the various process parameters of the cooling channel and obtain the optimized multiple process parameters of the low-pressure casting of the aluminum alloy wheel hub.

Images