Aluminum alloy wheel forging process based on automatic control and digital simulation

Abstract

The invention discloses an aluminum alloy wheel forging process based on automatic control and digital simulation, and belongs to the technical field of automobile part forging. The problems that an existing technology is not high in digitization level, a workshop information system is single in function, and the amount of integrated information is small are solved, the aluminum alloy wheel forging technological process and the forging result are fully re-carved through the digital simulation technology by introducing the digital simulation technology and the automatic control technology, and the aluminum alloy wheel forging quality is improved. Therefore, a worker can predict the aluminum alloy wheel forging effect according to current equipment parameters and various monitoring data in a scene, the worker can adjust parameters of forging equipment and scene parameters in advance, and then the aluminum alloy wheel forging precision is improved. And secondly, various sensing devices are arranged in various forging scenes, various data in the forging scenes are monitored through the sensing devices, and therefore it is ensured that the forging environment is suitable for the aluminum alloy wheel forging requirement to the maximum extent, and the aluminum alloy wheel forging precision and effect are further improved.

Description

Technical Field

[0001] The invention relates to the technical field of automobile parts forging, in particular to an aluminum alloy wheel forging process based on automatic control and digital simulation. Background Art

[0002] The continuous improvement of the forging technology level of automobile parts has promoted the rapid development of automobile engineering. People have high requirements for the performance and safety of vehicles. The components of various parts of automobiles must also continue to improve their quality and performance to better meet the current social development needs. In the past, steel wheels were easily affected by external factors during use and had quality problems. However, aluminum alloy wheels have good quality and performance and can be recycled. They have obvious application advantages in automobile wheel production and manufacturing. Aluminum alloy forging technology is an important manufacturing method for processing high-performance aluminum alloy products. In recent years, aluminum alloy wheel forging production technology has developed by leaps and bounds, and a relatively complete aluminum alloy forging production system has been formed.

[0003] Since the production and processing technology of aluminum alloy wheels is relatively complex, in order to complete the aluminum alloy wheel manufacturing work quickly and efficiently, we should focus on the use of advanced technical means to improve the efficiency of wheel production and manufacturing; however, in the existing technology, there is a certain gap in the overall intelligence level of the aluminum alloy wheel forging industry. The main problems are: the digitization level of aluminum alloy forging equipment is not high, the workshop information system has a single function, and the amount of integrated information is small. These problems lead to uncontrollable production processes, unstable product quality, and high operating and maintenance costs for aluminum alloy wheel forging companies.

[0004] Therefore, the existing needs are not met, and we propose an aluminum alloy wheel forging process based on automated control and digital simulation. Summary of the invention

[0005] The purpose of the present invention is to provide an aluminum alloy wheel forging process based on automatic control and digital simulation. By introducing digital simulation technology and automatic control technology, the digital simulation technology is used to fully replicate the aluminum alloy wheel forging process flow and forging results, so that workers can predict the aluminum alloy wheel forging effect according to the current equipment parameters and various monitoring data in the scene, thereby facilitating the workers to adjust the parameters of the forging equipment and the scene parameters in advance; by deploying a variety of sensor devices in various forging scenes, relying on the sensor equipment to monitor various data in the forging scene, it is ensured that the forging environment is most suitable for the needs of aluminum alloy wheel forging, thereby improving the accuracy and effect of aluminum alloy wheel forging, and solving the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The aluminum alloy wheel forging process based on automated control and digital simulation includes the following steps:

[0008] Step 1: Digital simulation: Obtain historical aluminum alloy wheel forging process data, simulate the temperature field distribution, filling and solidification process during the aluminum alloy wheel forging process by using the FEM finite element method, compare the simulated forging results of the aluminum alloy wheel with the actual forging results of the historical aluminum alloy wheel, obtain the simulation results of the temperature field, solidification field, and the distribution of shrinkage and shrinkage defects that are easy to form in the aluminum alloy wheel forging process, and adjust the parameters of the current forging equipment and scene according to the simulation results;

[0009] Step 2: Automatic control: by arranging multiple sensor devices in the forging process equipment to obtain various monitoring data, the operating status of the forging process equipment is determined according to the monitoring data, and each forging equipment is automatically controlled based on the operating status;

[0010] Step 3: Testing process: Conduct comprehensive testing on the chemical composition, crystal structure and mechanical properties of each raw material to ensure the quality of the raw materials;

[0011] Step 4: Forging process: Introduce digital simulation and automatic control technology into the current forging process, cut, heat, forge, cold spin and heat treat the aluminum bars in the raw materials to complete the forging process of aluminum alloy wheels.

[0012] Furthermore, in the step 1, the temperature field distribution, filling and solidification process of the forging process are simulated by the finite element method FEM, which specifically includes the following steps:

[0013] Modeling and meshing: Use UGNX software to model the aluminum alloy wheel hub of the car, and import the 3D model of the aluminum alloy wheel hub established by UGNX into ProCAST software for 2D and 3D meshing;

[0014] Setting parameters: Determine the selection of wheel hub and mold materials, obtain the material's thermophysical properties and high-temperature mechanical properties, and set relevant process parameters, including: pouring temperature, cooling system, and filling pressure, to ensure the simulation results and the quality of the final casting;

[0015] Finite element analysis: The temperature field of the forging model is analyzed using the finite element analysis method, including: analyzing the temperature of each small unit to obtain the temperature distribution of the entire forging model;

[0016] Digital simulation: Use ProCAST software to perform digital simulation of the low-pressure casting process of aluminum alloy wheels, study the temperature field, solidification field, and the distribution of defects that are prone to shrinkage and shrinkage holes in the forging process of aluminum alloy wheels; optimize the casting process, reduce casting defects, and improve casting quality by adjusting process parameters such as pouring temperature, cooling system, and filling pressure;

[0017] Verify results: Compare the simulation results with the experimental data to verify the accuracy of the simulation, including: compare the obtained simulation results with the change rules in the actual forging process, analyze the quality problems of the castings based on the simulation results, and adjust the process parameters according to the analysis results to optimize the process, so as to improve the casting quality and production efficiency and ensure the reliability of the simulation.

[0018] Furthermore, in step 2, multiple sensor devices are arranged in the forging process equipment, specifically including the following steps:

[0019] Data collection: The position data, pressure data, temperature data and forging production images of the forging production process are collected in real time through displacement sensors, pressure sensors, temperature sensors, visual systems and safety light curtain equipment installed in various forging scenes;

[0020] Data processing: receiving various data in each forging scene, comparing and analyzing each data with the threshold value, obtaining the operating status of the process equipment in each forging scene, and feeding back to the industrial computer;

[0021] Equipment control: The industrial computer sends corresponding control signals to each process equipment based on the operating status of the process equipment in each forging scene received, driving and controlling the operation of each process equipment.

[0022] Furthermore, the data receiving operation status of the position data, pressure data and temperature data is monitored in real time, and when the data receiving operation is abnormal, an abnormal operation alarm is issued, including:

[0023] Real-time monitoring of data receiving operation parameters of position data, pressure data and temperature data; wherein the data receiving operation parameters include data receiving delay ratio, data receiving bit error rate and data receiving interruption rate;

[0024] Obtaining a first data reception indicator parameter using the data reception delay ratio and the data reception bit error rate;

[0025] The first data receiving indicator parameter is obtained by the following formula:

[0026]

[0027] Among them, G 01 represents the first data receiving indicator parameter; n represents the number of data receiving times; R i represents the data reception delay rate corresponding to the i-th data reception; W i represents the data reception bit error rate corresponding to the i-th data reception; R b represents the standard deviation of the data reception delay rate corresponding to n data receptions; W brepresents the standard deviation of the data reception bit error rate corresponding to n data receptions; C rw Indicates the maximum value of the difference between the data reception delay rate and the data reception bit error rate corresponding to n data receptions; C 01 represents a preset first difference reference value;

[0028] Comparing the first data reception indicator parameter with a preset first indicator parameter threshold;

[0029] When the first data reception index parameter exceeds a preset first index parameter threshold, the data reception interruption rate is retrieved and combined with the first data reception index parameter to perform an abnormal determination on the data reception operation state.

[0030] Furthermore, when the first data reception indicator parameter exceeds a preset first indicator parameter threshold, the data reception interruption rate is retrieved and combined with the first data reception indicator parameter to perform abnormal determination on the data reception operation state, including:

[0031] When the first data reception indicator parameter exceeds a preset first indicator parameter threshold, the data reception interruption rate is retrieved;

[0032] Obtaining a second data reception indicator parameter using the first data reception indicator parameter and the data reception interruption rate;

[0033] The second data receiving indicator parameter is obtained by the following formula:

[0034]

[0035] Among them, G 02 represents the second data receiving index parameter; n represents the number of data receiving times; Z i represents the data reception interruption rate corresponding to the i-th data reception; R i represents the data reception delay rate corresponding to the i-th data reception; W i represents the data reception bit error rate corresponding to the i-th data reception; C rz Indicates the maximum value of the difference between the data reception delay rate and the data reception interruption rate corresponding to n data receptions; C wz Indicates the maximum value of the difference between the data reception interruption rate and the data reception bit error rate corresponding to n data receptions; C 02 Indicates the preset second difference reference value; C 03 represents a preset second difference reference value;

[0036] Comparing the second data reception indicator parameter with a preset second indicator parameter threshold;

[0037] When the second data reception index parameter exceeds the preset second index parameter threshold, it is determined that the data reception operation state is abnormal, and an abnormal alarm is issued.

[0038] Furthermore, in step 4, the aluminum rod in the raw material is cut, heated, forged, cold spun and heat treated, which specifically includes the following steps:

[0039] Cutting and weighing: Use a fully automatic cutting machine to automatically cut the aluminum bars, and then measure the weight of the cut aluminum bars;

[0040] Heating process: The cut aluminum bars are heated in a heating furnace to obtain the best forgeable temperature for the subsequent forging process of the aluminum bars;

[0041] Forging process: High-tonnage hydraulic presses complete the initial forging, forming forging and expansion processes, making the product have a denser organizational structure under high pressure and improving product performance;

[0042] Strong cold spinning: Use high-performance spinning machines to complete the cold spinning process to ensure that the product's size, precision and appearance quality meet qualified standards;

[0043] Strengthened T6 heat treatment: Through the integrated heat treatment system of high-temperature solid solution, quenching and low-temperature aging, the mechanical strength and hardness of the wheel hub are improved.

[0044] Furthermore, in modeling and meshing, when modeling the aluminum alloy wheel hub of an automobile, the modeling factors include: the diameter and width of the aluminum alloy wheel hub of the automobile, and the chamfer and groove structural details on the surface of the wheel hub, to ensure the accuracy of the model and the completeness of the details.

[0045] Furthermore, in modeling and meshing, when meshing the three-dimensional model of the aluminum alloy wheel hub, different mesh densities need to be used according to different parts of the model to ensure effective and fine division of contour curves and parts with smaller curvature radii.

[0046] Furthermore, in the verification results, the process parameters were adjusted according to the analysis results, including: comparing the location and degree of shrinkage cavities and shrinkage defects of the aluminum alloy wheel in the simulation results with the actual forging results.

[0047] Furthermore, in the forging process, after the aluminum rod reaches the set temperature, the aluminum rod is taken out, and the preheated aluminum rod is forged into a blank using a forging machine; the blank is then spin-formed by a spinning machine to form the basic shape of the wheel hub; the aluminum wheel hub is heat treated after spinning to improve the performance of the material; the heat-treated aluminum wheel hub is lathe-processed to further accurately shape it; the lathe-processed wheel hub is polished again to make its surface smooth; the wheel hub is punched according to structural requirements, and the punched wheel hub is further refined until it is finally formed.

[0048] Furthermore, during cutting and weighing, it is necessary to ensure that the weight of each product is strictly controlled within ±0.1kg, and unqualified products are eliminated.

[0049] Furthermore, the detection process in step three includes but is not limited to the following equipment: a spectrometer, a metallographic analyzer, a metallographic microscope, a Brinell hardness tester and a tensile testing machine.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] The present invention introduces digital simulation technology and automatic control technology into the existing forging process, and fully reproduces the aluminum alloy wheel forging process flow and forging results by using digital simulation technology, so that workers can predict the aluminum alloy wheel forging effect according to the current equipment parameters and various monitoring data in the scene, thereby facilitating the workers to adjust the parameters of the forging equipment and the scene parameters in advance, thereby improving the accuracy of aluminum alloy wheel forging; secondly, by deploying a variety of sensor devices in various forging scenes, relying on the sensor devices to monitor various data in the forging scenes, it is ensured that the forging environment is most suitable for the needs of aluminum alloy wheel forging, and further improves the accuracy and effect of aluminum alloy wheel forging. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 The present invention is a flowchart of the aluminum alloy wheel forging process based on automatic control and digital simulation. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] In order to solve the current gap in the overall intelligent level of the aluminum alloy wheel forging industry, the main problems are: the digital level of aluminum alloy forging equipment is not high, the workshop information system has a single function, and the amount of integrated information is small. These problems lead to technical problems such as uncontrollable production process, unstable product quality, and high operation and maintenance costs of aluminum alloy wheel forging enterprises. Please refer to Figure 1 , this embodiment provides the following technical solutions:

[0055] The aluminum alloy wheel forging process based on automated control and digital simulation includes the following steps:

[0056] Step 1, digital simulation: obtain historical aluminum alloy wheel forging process data, simulate the temperature field distribution, filling and solidification process during the aluminum alloy wheel forging process by FEM finite element method, compare the simulated forging results of the aluminum alloy wheel with the actual forging results of the historical aluminum alloy wheel, obtain the simulation results of the temperature field, solidification field and the distribution of shrinkage and shrinkage defects that are easy to form in the aluminum alloy wheel forging process, and adjust the parameters of the current forging equipment and scene according to the simulation results; Step 1 simulates the temperature field distribution, filling and solidification process of the forging process by FEM, which specifically includes the following steps:

[0057] Modeling and meshing: Use UGNX software to build a geometric model of the forging model for the aluminum alloy wheel hub. When modeling the aluminum alloy wheel hub, the modeling factors include: the actual diameter and width of the aluminum alloy wheel hub, as well as the chamfer and groove structure details on the wheel hub surface, to ensure the accuracy of the model and the integrity of the details; after the modeling is completed, the 3D model of the aluminum alloy wheel hub built by UGNX is imported into the ProCAST software for 2D and 3D meshing; when meshing the 3D model of the aluminum alloy wheel hub, different mesh densities should be used according to different parts of the model to ensure that the contour curve and the parts with smaller curvature radius are meshed. Carry out effective and fine division; Specifically, mesh division is a key step in digital simulation, which directly affects the accuracy and calculation efficiency of the simulation; Different mesh unit sizes can be set according to the structural characteristics of the aluminum alloy wheel casting; Usually the mesh unit size of the wheel casting is set smaller, while the mesh unit size of the mold is set larger, based on which the simulation of the wheel casting can be effectively reflected, while improving the calculation efficiency; By performing 2D and 3D mesh division, the mesh division of the entire model is finally completed; At the same time, attention should be paid to the continuity between the mesh units to ensure the connection between the nodes, edges, and faces of different parts.

[0058] Setting parameters: Determine the selection of wheel hub and mold materials, obtain the material's thermophysical properties and high-temperature mechanical properties, and set relevant process parameters, including: pouring temperature, cooling system, and filling pressure. The setting of these parameters is crucial to the accuracy of the simulation and can effectively ensure the simulation results and the quality of the final castings. Specifically, in the pre-processing stage of the simulation, it is necessary to set the material properties of the wheel hub and mold, and select suitable materials, such as: A356.2 aluminum alloy, because it has good casting properties and mechanical properties and is suitable for low-pressure casting processes. In addition, it is also necessary to set other relevant process parameters, such as: pouring temperature, cooling system, filling pressure, etc. The setting of the above parameters can directly affect the simulation results and the quality of the castings.

[0059] Finite element analysis: The temperature field of the forging model is analyzed by the finite element analysis method, including: analyzing the temperature of each small unit to obtain the temperature distribution of the entire forging model; specifically, when the temperature field of the casting model is analyzed by the finite element method, the distribution of the temperature field is calculated by the numerical analysis method to simulate the process of liquid metal filling the mold, that is, the numerical simulation of the filling process; the distribution of the temperature field has a great influence on the chemical composition, organizational structure, physical properties, etc. of the casting product, so it must be accurately analyzed

[0060] Digital simulation: ProCAST software is used to perform digital simulation of the low-pressure casting process of aluminum alloy wheels, and the temperature field, solidification field and the distribution of defects that are easy to form shrinkage and shrinkage holes in the forging process of aluminum alloy wheels are studied; by adjusting the pouring temperature, cooling system, filling pressure and other process parameters, the casting process is optimized, casting defects are reduced, and the casting quality is improved; it also includes analyzing the temperature of each small unit, and finally obtaining the temperature distribution of the entire forging model; specifically, by simulating the filling and solidification process of the casting through digital simulation technology, various phenomena in the forging process can be predicted, such as: simulating the process of liquid metal filling the mold, that is: filling Numerical simulation of the molding process can help predict and avoid defects in the casting process, such as cold shuts and pores. Another example is the simulation of the solidification process of liquid metal, including temperature drop and phase change. This step is crucial for predicting the quality and performance of castings, and can help optimize the casting process and improve the yield of castings. The stress field in the casting process is analyzed by the finite element analysis method, which can comprehensively simulate the temperature field distribution, filling and solidification process in the casting process, and effectively predict possible stress concentration and deformation, so as to ensure that the quality and performance of the castings meet the requirements, thereby optimizing the production process and improving the yield of castings.

[0061] Verification results: The simulation results are compared with the experimental data to verify the accuracy of the simulation, including: comparing the obtained simulation results with the changing rules in the actual forging process, analyzing the quality problems of the castings based on the simulation results, and adjusting the process parameters according to the analysis results, including: comparing the location and degree of shrinkage holes and shrinkage defects of aluminum alloy wheels in the simulation results with the actual forging results, optimizing the process to achieve the purpose of improving the quality of castings and production efficiency, and ensuring the reliability of the simulation; specifically, when comparing the simulation results with the experimental data, if the simulation results are consistent with the actual production situation, it means that the simulation is effective, then adjust the corresponding process parameters according to the simulation results, such as: adjusting the pouring temperature, cooling system, etc., to reduce casting defects and improve the quality of castings; to ensure the accuracy of the simulation and the quality of castings, multiple iterations of simulation can be performed to take the simulation result with the highest casting quality as the best result, and the parameters in actual production are corrected according to the various parameters set in this simulation result to achieve the best casting quality and the lowest defect rate.

[0062] Based on this, through the above steps, simulation software can be used to numerically simulate the low-pressure casting process of aluminum alloy wheels, optimize process parameters, and improve casting quality and performance.

[0063] Step 2: Automatic control: by arranging multiple sensor devices in the forging process equipment to obtain various monitoring data, judging the operating status of the forging process equipment according to the monitoring data, and automatically controlling each forging equipment based on the operating status; in step 2, by arranging multiple sensor devices in the forging process equipment, the following steps are specifically included:

[0064] Data collection: By installing displacement sensors, pressure sensors, temperature sensors, visual systems and safety light curtains in various forging scenes, the position data, pressure data, temperature data and forging production images in the forging production process are collected in real time; specifically, by connecting the industrial computer with the external control center, the control center receives the above-mentioned data information, and outputs the control signal after analysis and processing; among them, a data communication channel is also set up to be responsible for transmitting data from each slave station to the control center, and the data receiving module sends the control signal to the industrial computer to realize automated production, thereby achieving precise control of the production process.

[0065] Data processing: receiving various data in each forging scene, and comparing and analyzing each data with the threshold value, obtaining the operating status of the process equipment in each forging scene, and feeding back to the industrial control computer; specifically, after receiving the above-mentioned multiple data information, the control center can clean and store the data, so as to form a database in this way; then extract a part of the data as a data sample, and use the extraction of the intermediate value method to obtain the normal threshold value corresponding to each data, and use its threshold value as a reference for data analysis, specifically: comparing each data currently received with the corresponding threshold value, if it is within the normal threshold value, then judging that the current forging scene is normal; comparing each data currently received with the corresponding threshold value, if it exceeds or is lower than the normal threshold value, then judging that the current data is abnormal, and then judging that the forging scene is abnormal and affects the forging quality, and feeding back the abnormal signal to the industrial control computer.

[0066] Equipment control: The industrial computer receives the operating status of the process equipment in each forging scene as a basis, and sends corresponding control signals to each process equipment to drive and control the operation of each process equipment; specifically, when the industrial computer receives an abnormal signal, such as: the temperature data in the temperature field exceeds the normal threshold through comparison, the industrial computer sends a cooling command to the temperature output device in the temperature field, such as a heater, to reduce the temperature in the temperature field, and the temperature sensor continues to monitor the temperature data until the temperature data in the temperature field is within the normal threshold range, thereby ensuring the quality of the casting and realizing fully automatic and intelligent operation.

[0067] Specifically, the data receiving operation status of the position data, pressure data and temperature data is monitored in real time, and when the data receiving operation is abnormal, an abnormal operation alarm is issued, including:

[0068] Real-time monitoring of data receiving operation parameters of position data, pressure data and temperature data; wherein the data receiving operation parameters include data receiving delay ratio, data receiving bit error rate and data receiving interruption rate;

[0069] Obtaining a first data reception indicator parameter using the data reception delay ratio and the data reception bit error rate;

[0070] The first data receiving indicator parameter is obtained by the following formula:

[0071]

[0072] Among them, G 01 represents the first data receiving indicator parameter; n represents the number of data receiving times; R i represents the data reception delay rate corresponding to the i-th data reception; W i represents the data reception bit error rate corresponding to the i-th data reception; R b represents the standard deviation of the data reception delay rate corresponding to n data receptions; W b represents the standard deviation of the data reception bit error rate corresponding to n data receptions; C rw Indicates the maximum value of the difference between the data reception delay rate and the data reception bit error rate corresponding to n data receptions; C 01 represents a preset first difference reference value;

[0073] Comparing the first data reception indicator parameter with a preset first indicator parameter threshold;

[0074] When the first data reception index parameter exceeds a preset first index parameter threshold, the data reception interruption rate is retrieved and combined with the first data reception index parameter to perform an abnormal determination on the data reception operation state.

[0075] The technical effect of the above technical solution is that the solution can monitor the data receiving operation status of position data, pressure data and temperature data in real time, thereby ensuring the real-time and accuracy of the data. By evaluating the three key parameters of data receiving delay ratio, data receiving bit error rate and data receiving interruption rate, the overall performance and stability of the data receiving system can be fully reflected.

[0076] By calculating the first data reception index parameter, the scheme can comprehensively consider the data reception delay ratio and the data reception bit error rate, so as to more accurately determine whether the data reception is abnormal. The calculation formula of the first data reception index parameter takes into account the number of data receptions, the delay rate and bit error rate of each data reception, and their standard deviations, and also considers the maximum difference between the delay rate and the bit error rate, which helps to capture subtle anomalies in the data reception process. When the first data reception index parameter exceeds the preset first index parameter threshold, the scheme will further retrieve the data reception interruption rate and combine it for abnormal judgment. This strategy takes into account both the real-time and accuracy of data reception and the continuity of data (through the data reception interruption rate), thereby improving the accuracy and reliability of abnormal judgment. Once it is determined that the data reception operation state is abnormal, the scheme can promptly issue an alarm and notify relevant personnel to handle it. This helps to discover and solve problems in a timely manner, prevent data loss or error accumulation, and ensure the stable operation of the system and the integrity of the data. The preset first difference reference value and the first index parameter threshold can be adjusted according to actual needs, so that the scheme can adapt to different application scenarios and performance requirements. In addition, the scheme can be further extended, such as introducing more data reception parameters or adopting more complex algorithms to improve the accuracy and efficiency of anomaly detection.

[0077] In summary, this technical solution can effectively improve the stability and reliability of the data receiving system and ensure the real-time and accuracy of the data by real-time monitoring and comprehensive evaluation of the data receiving operation status, combined with accurate data receiving anomaly detection, flexible anomaly judgment strategy and timely anomaly alarm.

[0078] Specifically, when the first data reception indicator parameter exceeds a preset first indicator parameter threshold, the data reception interruption rate is retrieved and combined with the first data reception indicator parameter to perform abnormal determination on the data reception operation state, including:

[0079] When the first data reception indicator parameter exceeds a preset first indicator parameter threshold, the data reception interruption rate is retrieved;

[0080] Obtaining a second data reception indicator parameter using the first data reception indicator parameter and the data reception interruption rate;

[0081] The second data receiving indicator parameter is obtained by the following formula:

[0082]

[0083] Among them, G 02 represents the second data receiving index parameter; n represents the number of data receiving times; Z i represents the data reception interruption rate corresponding to the i-th data reception; R irepresents the data reception delay rate corresponding to the i-th data reception; W i represents the data reception bit error rate corresponding to the i-th data reception; C rz Indicates the maximum value of the difference between the data reception delay rate and the data reception interruption rate corresponding to n data receptions; C wz Indicates the maximum value of the difference between the data reception interruption rate and the data reception bit error rate corresponding to n data receptions; C 02 Indicates the preset second difference reference value; C 03 represents a preset second difference reference value;

[0084] Comparing the second data reception indicator parameter with a preset second indicator parameter threshold;

[0085] When the second data reception index parameter exceeds the preset second index parameter threshold, it is determined that the data reception operation state is abnormal, and an abnormal alarm is issued.

[0086] The technical effect of the above technical solution is: when the first data reception index parameter exceeds the preset first index parameter threshold, the solution not only takes into account the delay and bit error of data reception, but also further introduces the key parameter of data reception interruption rate. By combining these three parameters, the operating status of data reception can be more comprehensively evaluated, thereby enhancing the ability of anomaly detection. By calculating the second data reception index parameter, the solution can comprehensively consider the mutual influence between the data reception delay rate, the data reception bit error rate and the data reception interruption rate. The calculation formula of the second data reception index parameter includes the maximum difference of these parameters (C rz and C wz ), which helps capture complex abnormal patterns in the data reception process. At the same time, C in the formula 02 and C 03 The preset second difference reference value and the third difference reference value can be adjusted according to the actual application scenario and requirements. This flexibility enables the solution to adapt to different data reception environments and performance requirements. 02 When the preset threshold of the second indicator parameter is exceeded, the solution will determine that the data reception operation status is abnormal and issue an abnormal alarm. This strategy ensures the reliability and timeliness of abnormality determination, and helps to promptly discover and solve problems in the data reception process. By monitoring the operation status of data reception in real time and issuing an alarm in time when an abnormality occurs, the solution can prevent problems such as data loss and error accumulation, thereby improving the stability and reliability of the entire system. The technical framework and algorithm design of the solution are relatively simple and clear, easy to understand and implement. At the same time, the introduction of configurable parameters and flexible abnormality determination strategies makes the solution easier to expand and maintain in the future.

[0087] In summary, this technical solution improves the accuracy and reliability of data reception anomaly detection by introducing the key parameter of data reception interruption rate and combining data reception delay rate and data reception bit error rate for comprehensive evaluation. At the same time, this solution also has the characteristics of flexible parameter configuration, reliable anomaly judgment strategy, and easy expansion and maintenance, which can be applied to various complex data reception environments and application scenarios.

[0088] Step 3. Testing process: Conduct a comprehensive test on the chemical composition, crystal structure and mechanical properties of each raw material to ensure the quality of the raw materials; the testing process includes but is not limited to the following equipment: spectrometer, metallographic analyzer, metallographic microscope, Brinell hardness tester and tensile testing machine; specifically, according to the product manufacturing process and product quality requirements of the digital workshop, before the raw materials go online, after the forging blanks come off the line, after heat treatment, and after machining (pre-machining, machining, finishing), the manufacturing process quality data must be tested through automatic testing equipment to ensure the quality of the raw materials.

[0089] Step 4, forging process: Introduce digital simulation and automatic control technology into the current forging process, cut, heat, forge, cold spin and heat treat the aluminum rod in the raw material, and complete the forging process of the aluminum alloy wheel; In step 4, the aluminum rod in the raw material is cut, heated, forged, cold spun and heat treated, which specifically includes the following steps:

[0090] Cutting and weight measurement: Use a fully automatic cutting machine to automatically cut the aluminum rods, and then check the weight of the cut aluminum rods; ensure that the weight of each product is strictly controlled within ±0.1kg, and remove unqualified products; specifically, before cutting, select an aluminum rod material suitable for forged wheels, which is the basic material for forged wheels, and conduct quality inspection on the selected aluminum rods. After the quality inspection is qualified, grind the aluminum rods to make the surface smooth, prepare for subsequent processing, and cut the aluminum rods with smooth surfaces to make them the size required for manufacturing wheels; cutting is for the initial shaping of the aluminum rods, and measurement is to ensure that the aluminum rods meet the forging weight of aluminum alloy wheels.

[0091] Heating process: The cut aluminum rod is heated in a heating furnace to obtain the best forgeable temperature of the aluminum rod, so as to prepare for the subsequent forging process of the aluminum rod; specifically, the cut aluminum rod is placed in a heating furnace for heating, and after reaching the set temperature, the aluminum rod is taken out for forging.

[0092] Forging process: A high-tonnage hydraulic press completes the initial forging, forming forging and expansion processes, so that the product can obtain a denser organizational structure under high pressure and improve product performance; the aluminum rod is taken out after reaching the set temperature, and the preheated aluminum rod is forged into a blank using a forging press; the blank is then spin-formed by a spinning machine to form the basic shape of the wheel hub; the aluminum wheel hub is heat-treated after spinning to improve the performance of the material; the heat-treated aluminum wheel hub is lathe-processed for further precise shaping; the lathe-processed wheel hub is then polished again to make its surface smooth; the wheel hub is punched according to the structural requirements, and the punched wheel hub is further refined until it is finally formed;

[0093] Powerful cold spinning: Use high-performance spinning machines to complete the cold spinning process to ensure that the product's size, precision and appearance quality meet qualified standards; specifically, the spinning machine model that can be used is: Germany-LE I FEID spinning machine automatically completes the cold spinning process, thereby ensuring that the product's size, precision and appearance quality are superior to the same industry level.

[0094] Strengthened T6 heat treatment: Through the integrated heat treatment system of high-temperature solid solution, quenching and low-temperature aging, the mechanical strength and hardness of the wheel hub are improved; specifically, by selecting the model: Sanjian brand enhanced T6 heat treatment furnace to carry out continuous high-temperature solid solution, quenching, low-temperature aging, and integrated heat treatment system treatment on the spun blank, the aluminum alloy system inside the product is more stable, and the mechanical strength and hardness of the wheel hub are improved.

[0095] The beneficial effects achieved by the above contents are: by introducing digital simulation technology and automated control technology, using automated control and digital simulation for precise operations, ensuring that the quality and performance of aluminum alloy wheels meet high standards and meet the needs of modern automobiles for lightweight, energy saving and high performance.

[0096] Working principle: By introducing digital simulation technology and automated control technology, digital simulation technology is used to fully replicate the aluminum alloy wheel forging process and forging results, so that workers can predict the aluminum alloy wheel forging effect based on the current equipment parameters and various monitoring data in the scene, thereby facilitating workers to adjust the parameters of the forging equipment and scene parameters in advance; secondly, by deploying a variety of sensor equipment in various forging scenes, relying on sensor equipment to monitor various data in the forging scenes, it is ensured that the forging environment is most suitable for the needs of aluminum alloy wheel forging, thereby improving the accuracy and effect of aluminum alloy wheel forging.

[0097] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0098] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. Aluminum alloy wheel forging process based on automatic control and digital simulation, characterized in that: The following steps are involved: Step 1: Digital simulation: Obtain historical aluminum alloy wheel forging process data, simulate the temperature field distribution, filling and solidification process during the aluminum alloy wheel forging process by using the FEM finite element method, compare the simulated forging results of the aluminum alloy wheel with the actual forging results of the historical aluminum alloy wheel, obtain the simulation results of the temperature field, solidification field, and the distribution of shrinkage and shrinkage defects that are easy to form in the aluminum alloy wheel forging process, and adjust the parameters of the current forging equipment and scene according to the simulation results; Step 2: Automatic control: by arranging multiple sensor devices in the forging process equipment to obtain various monitoring data, the operating status of the forging process equipment is determined according to the monitoring data, and each forging equipment is automatically controlled based on the operating status; Step 3: Testing process: Conduct comprehensive testing on the chemical composition, crystal structure and mechanical properties of each raw material to ensure the quality of the raw materials; Step 4: Forging process: Introduce digital simulation and automatic control technology into the current forging process, cut, heat, forge, cold spin and heat treat the aluminum bars in the raw materials to complete the forging process of aluminum alloy wheels.

2. The aluminum alloy wheel forging process based on automatic control and digital simulation according to claim 1 is characterized in that: In the step 1, the temperature field distribution, filling and solidification process of the forging process are simulated by the finite element method FEM, which specifically includes the following steps: Modeling and meshing: Use UGNX software to model the aluminum alloy wheel hub of the car, and import the 3D model of the aluminum alloy wheel hub established by UGNX into ProCAST software for 2D and 3D meshing; When modeling the aluminum alloy wheel hub of the car, the modeling factors include: the diameter and width of the aluminum alloy wheel hub of the car, and the chamfer and groove structure details on the surface of the wheel hub; When meshing the 3D model of the aluminum alloy wheel hub, different mesh densities should be used according to different parts of the model to ensure effective and fine division of the contour curve and the parts with small curvature radius; Setting parameters: Determine the selection of wheel hub and mold materials, obtain the material's thermophysical properties and high-temperature mechanical properties, and set relevant process parameters, including: pouring temperature, cooling system, and filling pressure, to ensure the simulation results and the quality of the final casting; Finite element analysis: The temperature field of the forging model is analyzed using the finite element analysis method, including: analyzing the temperature of each small unit to obtain the temperature distribution of the entire forging model; Digital simulation: Use ProCAST software to perform digital simulation of the low-pressure casting process of aluminum alloy wheels, study the temperature field, solidification field, and the distribution of defects that are prone to shrinkage and shrinkage holes in the forging process of aluminum alloy wheels; optimize the casting process, reduce casting defects, and improve casting quality by adjusting process parameters such as pouring temperature, cooling system, and filling pressure; Verify results: Compare the simulation results with the experimental data to verify the accuracy of the simulation, including: compare the obtained simulation results with the change rules in the actual forging process, analyze the quality problems of the castings based on the simulation results, and adjust the process parameters according to the analysis results to optimize the process, so as to improve the casting quality and production efficiency and ensure the reliability of the simulation.

3. The aluminum alloy wheel forging process based on automatic control and digital simulation according to claim 1 is characterized in that: In the step 2, a plurality of sensor devices are arranged in the forging process equipment, and specifically includes the following steps: Data collection: The position data, pressure data, temperature data and forging production images of the forging production process are collected in real time through displacement sensors, pressure sensors, temperature sensors, visual systems and safety light curtain equipment installed in various forging scenes; Data processing: receiving various data in each forging scene, comparing and analyzing each data with the threshold value, obtaining the operating status of the process equipment in each forging scene, and feeding back to the industrial computer; Equipment control: The industrial computer sends corresponding control signals to each process equipment based on the operating status of the process equipment in each forging scene received, driving and controlling the operation of each process equipment.

4. The aluminum alloy wheel forging process based on automatic control and digital simulation according to claim 3 is characterized in that: Monitor the data receiving operation status of position data, pressure data and temperature data in real time, and issue an abnormal operation alarm when the data receiving operation is abnormal, including: Real-time monitoring of data receiving operation parameters of position data, pressure data and temperature data; wherein the data receiving operation parameters include data receiving delay ratio, data receiving bit error rate and data receiving interruption rate; Obtaining a first data reception indicator parameter using the data reception delay ratio and the data reception bit error rate; The first data receiving indicator parameter is obtained by the following formula: Among them, G 01 represents the first data receiving indicator parameter; n represents the number of data receiving times; R i represents the data reception delay rate corresponding to the i-th data reception; W i represents the data reception bit error rate corresponding to the i-th data reception; R b represents the standard deviation of the data reception delay rate corresponding to n data receptions; W b represents the standard deviation of the data reception bit error rate corresponding to n data receptions; C rw Indicates the maximum value of the difference between the data reception delay rate and the data reception bit error rate corresponding to n data receptions; C 01 represents a preset first difference reference value; Comparing the first data reception indicator parameter with a preset first indicator parameter threshold; When the first data reception index parameter exceeds a preset first index parameter threshold, the data reception interruption rate is retrieved and combined with the first data reception index parameter to perform an abnormal determination on the data reception operation state.

5. The aluminum alloy wheel forging process based on automatic control and digital simulation according to claim 4 is characterized in that: When the first data reception indicator parameter exceeds a preset first indicator parameter threshold, the data reception interruption rate is retrieved and combined with the first data reception indicator parameter to perform abnormal determination on the data reception operation state, including: When the first data reception indicator parameter exceeds a preset first indicator parameter threshold, the data reception interruption rate is retrieved; Obtaining a second data reception indicator parameter using the first data reception indicator parameter and the data reception interruption rate; The second data receiving indicator parameter is obtained by the following formula: Among them, G 02 represents the second data receiving index parameter; n represents the number of data receiving times; Z i represents the data reception interruption rate corresponding to the i-th data reception; R i represents the data reception delay rate corresponding to the i-th data reception; W i represents the data reception bit error rate corresponding to the i-th data reception; C rz Indicates the maximum value of the difference between the data reception delay rate and the data reception interruption rate corresponding to n data receptions; C wz Indicates the maximum value of the difference between the data reception interruption rate and the data reception bit error rate corresponding to n data receptions; C 02 Indicates the preset second difference reference value; C 03 represents a preset second difference reference value; Comparing the second data reception indicator parameter with a preset second indicator parameter threshold; When the second data reception index parameter exceeds the preset second index parameter threshold, it is determined that the data reception operation state is abnormal, and an abnormal alarm is issued.

6. The aluminum alloy wheel forging process based on automatic control and digital simulation according to claim 1 is characterized in that: In the step 4, the aluminum rod in the raw material is cut, heated, forged, cold spun and heat treated, which specifically includes the following steps: Cutting and weighing: Use a fully automatic cutting machine to automatically cut the aluminum bars, and then measure the weight of the cut aluminum bars; Heating process: The cut aluminum bars are heated in a heating furnace to obtain the best forgeable temperature for the subsequent forging process of the aluminum bars; Forging process: High-tonnage hydraulic presses complete the initial forging, forming forging and expansion processes, making the product have a denser organizational structure under high pressure and improving product performance; Strong cold spinning: Use high-performance spinning machines to complete the cold spinning process to ensure that the product's size, precision and appearance quality meet qualified standards; Strengthened T6 heat treatment: Through the integrated heat treatment system of high-temperature solid solution, quenching and low-temperature aging, the mechanical strength and hardness of the wheel hub are improved.

7. The aluminum alloy wheel forging process based on automatic control and digital simulation according to claim 2 is characterized in that: In the verification results, the process parameters were adjusted according to the analysis results, including: comparing the location and degree of shrinkage holes and shrinkage defects of the aluminum alloy wheels in the simulation results with the actual forging results.

8. The aluminum alloy wheel forging process based on automatic control and digital simulation according to claim 6 is characterized in that: In the forging process, the aluminum rod is taken out after it reaches the set temperature, and the preheated aluminum rod is forged into a blank using a forging machine, and then the blank is spin-formed by a spinning machine to form the basic shape of the wheel hub. The aluminum hub is heat treated after spinning, and the heat-treated aluminum hub is lathe-processed, and then the lathe-processed hub is polished again, and the hub is punched according to structural requirements, and the punched hub is further refined until it is finally formed.

9. The aluminum alloy wheel forging process based on automatic control and digital simulation according to claim 6 is characterized in that: During cutting and weighing, it is necessary to ensure that the weight of each product is strictly controlled within ±0.1kg, and unqualified products are eliminated.

10. The aluminum alloy wheel forging process based on automatic control and digital simulation according to claim 1, characterized in that: The detection process in step three includes but is not limited to the following equipment: a spectrometer, a metallographic analyzer, a metallographic microscope, a Brinell hardness tester and a tensile testing machine.

Images