A precision casting method based on edge pouring and edge vibrating

Abstract

The present application relates to the field of casting manufacturing, and discloses a precision casting method based on edge pouring and edge vibrating, which is used for the precision casting of castings. The method comprises the following steps: constructing a process database containing multiple historical cases, recording the combination of working conditions and vibration parameters, matching a similar case set after receiving the current task working condition parameters, comprehensively processing the reference value of the vibration parameters in the case set, recalibrating the vibration parameters, driving the vibration equipment to operate at the vibration parameters during the pouring process, and completing the molding of the castings. The present application realizes the accurate determination and dynamic adjustment of the vibration parameters in the casting of castings, which helps to improve the quality of castings, reduce the waste rate, and improve the production efficiency and reliability of precision casting.

Description

Technical Field

[0001] This invention relates to the field of casting manufacturing, and more particularly to a precision casting method based on simultaneous pouring and vibration. Background Technology

[0002] With the increasing demand for weight reduction and energy conservation in the automotive, aerospace, and high-end equipment industries, the application of high-strength, high-toughness, and lightweight die-cast aluminum alloys for structural components has become crucial. The quality and mechanical properties of these castings directly determine the reliability and safety of the final product. However, traditional casting and forming methods are prone to problems such as porosity, shrinkage porosity, and coarse grains when dealing with high-strength, high-toughness, and lightweight die-cast aluminum alloys for structural components. These components often have complex thin-walled structures and extremely high requirements for comprehensive mechanical properties (high strength and high toughness). This makes it difficult to meet increasingly stringent quality standards. Therefore, how to accurately control process parameters during casting, especially by introducing and controlling vibration parameters, to improve the crystallization process of the alloy melt and optimize the microstructure and forming quality of the castings, has become a critical issue that urgently needs to be addressed in this field.

[0003] For die-cast aluminum alloys used in high-strength, high-toughness, and lightweight structural components, vibration plays an irreplaceable role in several aspects during the forming process: it can significantly improve the filling ability of molten aluminum alloy into complex thin-walled cavities, break up primary dendrites to refine the grain structure (which is key to improving strength and toughness), and promote gas discharge to reduce internal defects.

[0004] However, the optimal setting of vibration parameters is profoundly influenced by various working conditions, such as the solidification characteristics of specific aluminum alloys, complex mold structures, pouring temperature, and pouring speed. Different working conditions require different combinations of vibration parameters to maximize the strength and toughness potential of such aluminum alloys. Currently, in actual production, the determination of vibration parameters mainly relies on experienced engineers manually adjusting them based on past experience. This method is not only inefficient but also makes it difficult to guarantee accurate matching of ideal vibration parameters under various complex working conditions. Consequently, the quality of die-cast aluminum alloys for high-strength, high-toughness, and lightweight structural components is unstable, resulting in a high scrap rate and hindering their large-scale, efficient application.

[0005] Therefore, we propose a precision casting method based on simultaneous pouring and vibration to solve the above problems. Summary of the Invention

[0006] This invention provides a precision casting method based on simultaneous pouring and vibration, for the precision casting of castings.

[0007] The first aspect of this invention provides a precision casting method based on simultaneous pouring and vibration. The method includes: constructing a process database comprising multiple historical casting cases, each historical casting case recording a corresponding combination of operating parameters and vibration parameters; obtaining the operating parameters of the current casting task; matching similar historical cases from the process database based on these operating parameters to form a similar case set; processing the vibration parameters recorded in the similar case set to obtain the reference vibration parameters for the current task; calibrating the reference vibration parameters based on the operating parameters of the current casting task to obtain the vibration parameters; and driving a vibration device to operate with the vibration parameters during the pouring process to complete the casting.

[0008] Optionally, in a first implementation of the first aspect of the present invention, constructing the process database includes: determining a set of key parameters for describing casting conditions and vibration effects based on energy threshold theory, forming a key parameter set; collecting process data from multiple completed historical casting cases, extracting corresponding parameter values ​​from the process data of each historical case according to the key parameter set, forming a historical casting dataset; and associating and storing the parameter values ​​extracted from each case in the historical casting dataset with the corresponding casting quality evaluation results.

[0009] Optionally, in a second implementation of the first aspect of the present invention, the method includes: reading vibration parameters recorded in each historical case from the set of similar cases to form an original vibration parameter set; analyzing the original vibration parameter set to identify parameters that meet the vibration validity criteria to form an effective vibration parameter set; and performing comprehensive calculations on the parameter values ​​in the effective vibration parameter set to obtain the reference vibration parameters.

[0010] Optionally, in a third implementation of the first aspect of the present invention, the vibration energy factor corresponding to each vibration parameter in the effective vibration parameter set is calculated; based on the numerical distribution of the vibration energy factor, vibration parameters located in a preset preferred factor range are selected from the effective vibration parameter set to form a core parameter subset; and multiple vibration parameters in the core parameter subset are subjected to synthesis operations on their frequency and amplitude components to obtain reference vibration parameters.

[0011] Optionally, in a fourth implementation of the first aspect of the present invention, the method includes: acquiring the working condition parameters of the current casting task and the reference vibration parameters to form a comprehensive input parameter set; determining the required adjustment direction of the reference vibration parameters based on the comprehensive input parameter set; and performing numerical calibration on the reference vibration parameters according to the adjustment direction to obtain vibration parameters.

[0012] Optionally, in a fifth implementation of the first aspect of the present invention, a comprehensive parameter vector representing the current casting state is obtained based on the comprehensive input parameter set; the comprehensive parameter vector is matched with a plurality of pre-stored empirical parameter vectors, each empirical parameter vector being associated with a historically successful parameter adjustment direction; based on the matching result, a parameter adjustment direction suitable for the current casting state is selected from the historically successful parameter adjustment directions associated with the empirical parameter vectors.

[0013] Optionally, in the sixth implementation of the first aspect of the present invention, when the selected parameter adjustment direction is the frequency-boosting and amplitude-preserving direction, the corresponding equipment control value is calculated according to a preset critical vibration penetration power requirement formula, wherein the critical vibration penetration power requirement formula is: ; in: The critical vibration power; Where W is the liquid vibration attenuation constant; and W is the current gross weight of a single casting. This refers to the actual pouring temperature; This refers to the actual shell temperature. This is the inherent liquidus temperature of the alloy.

[0014] Optionally, in the seventh implementation of the first aspect of the present invention, the method includes: obtaining equipment control instructions based on the vibration parameters; executing the equipment control instructions to drive the vibration equipment to operate during the casting process, and simultaneously collecting real-time operating data of the casting process; after the casting is formed, performing a quality evaluation on the casting to obtain a quality evaluation result; associating and integrating the vibration parameters, the real-time operating data, and the quality evaluation result into a casting process record; and storing the casting process record as a new historical case in the process database.

[0015] Optionally, in the eighth implementation of the first aspect of the present invention, the method further includes: obtaining physical property parameters of the casting material based on the working condition parameters of the current casting task, forming a material property parameter set; inputting the vibration parameters and the material property parameter set into a vibration effect evaluation model, and outputting a vibration effect evaluation value; determining whether a parameter correction instruction is obtained based on the comparison result between the vibration effect evaluation value and a preset empirical threshold range; if the parameter correction instruction is obtained, performing a compensation correction on the vibration parameters to obtain the corrected vibration parameters, and using them as vibration parameters for driving the vibration equipment.

[0016] Optionally, in a ninth implementation of the first aspect of the present invention, the vibration effect evaluation value is compared with the boundary value of a preset empirical threshold range to calculate the evaluation value deviation; based on the material property parameter set and the evaluation value deviation, a preset correction rule table is searched to determine the corresponding parameter correction factor; the frequency and amplitude components in the vibration parameters are adjusted using the parameter correction factor to obtain the corrected vibration parameters.

[0017] The mechanism of this invention is as follows: It breaks through the limitations of fixed or empirically set vibration parameters in traditional casting, and realizes real-time and precise coupling between vibration energy and liquid metal filling behavior, thereby significantly suppressing defects such as shrinkage porosity and gas porosity, and obtaining high-quality castings with dense structure and clear contours. Beneficial effects: During the casting process, vibration parameters can be determined not only based on initial working conditions but also by real-time data acquisition and dynamic calibration of parameters using energy threshold theory. A vibration parameter verification step is also included, evaluating the effect and compensating for any discrepancies based on material properties, ensuring that the parameters are always highly adapted to actual working conditions and improving the scientific rigor of casting decisions. Based on the current casting task operating conditions parameters and the reference vibration parameters, a comprehensive input parameter set is formed. By matching with the empirical parameter vector, the adjustment direction is determined and the values ​​are calibrated. The reference vibration parameters can be intelligently adjusted according to different current casting conditions, so that the vibration parameters can better adapt to the actual casting conditions, improve the flexibility and adaptability of the casting process, and ensure that better casting results can be obtained under different operating conditions. Real-time operating data is collected during the casting process, and quality evaluation is performed after the casting is formed. Vibration parameters, real-time operating data, and quality evaluation results are linked and integrated into casting process records and stored in the process database. This enables real-time monitoring and comprehensive recording of the casting process. Through feedback and analysis of each casting result, experience can be continuously accumulated, potential problems can be discovered, and process parameters can be adjusted in a timely manner to continuously optimize the casting process, forming a virtuous cycle and promoting the continuous progress of casting technology. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of an embodiment of the precision casting method based on simultaneous pouring and vibration in this invention. Figure 2 A schematic diagram illustrating the acquisition of process data for historical casting cases; Figure 3 This is a schematic diagram of another embodiment of the precision casting method based on simultaneous pouring and vibration in this invention. Figure 4 This is a schematic diagram of an embodiment of a precision casting equipment based on simultaneous pouring and vibration in this invention. Detailed Implementation

[0019] This invention provides a precision casting method based on simultaneous pouring and vibration for the precision casting of castings. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0020] For ease of understanding, the specific process of the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 1 One embodiment of the precision casting method based on simultaneous pouring and vibration in this invention includes: 101. Construct a process database that includes multiple historical casting cases, with each historical casting case recording the corresponding combination of operating parameters and vibration parameters.

[0021] It is understood that the executing entity of this invention can be a precision casting device based on simultaneous pouring and vibration, or it can be a terminal or a server; no specific limitation is made here. This embodiment of the invention will be described using a server as an example.

[0022] It should be noted that a successful historical casting case of a high-pressure turbine blade for an aero-engine is being entered. This case will be disassembled and stored in the process database. The specific information recorded on the server is as follows: the case number is assigned as 20260328-TB01, which serves as the unique primary key in the database. The casting is clearly characterized as a high-pressure turbine blade, made of a nickel-based superalloy (K4169), with a single piece gross weight of 2.5 kg, a maximum wall thickness of 12 mm, and a minimum wall thickness of 1.5 mm.

[0023] The recorded pouring temperature of the molten metal was 1450 degrees Celsius; the preheating temperature of the mold shell was 1050 degrees Celsius; the vacuum level of the furnace environment during the pouring process was maintained below 0.5 Pascals; and the average pouring rate was controlled at 0.3 kg / s (total pouring time was approximately 8.3 seconds).

[0024] The excitation frequency was set to 120 Hz, using medium-high frequency to break up the initial dendrites and refine the grains; the vibration amplitude was constant at 0.3 mm; the vibration direction was uniaxial directional excitation along the vertical direction; the vibration start time was set to intervene 1.5 seconds after the start of the pouring action to avoid initial splashing of molten metal; the vibration duration was 20 seconds to fully cover the liquid filling period and the early stage of crystallization and solidification.

[0025] Inspection revealed that this batch of blades had no obvious shrinkage cavities or porosity inside, achieved a metallurgical density of 99.5%, and met surface roughness standards. This evaluation indicates that this parameter combination is a set of high-quality data, and the system officially stores it as a benchmark reference in the process database. The server continuously executes this step, adding hundreds or even thousands of similar cases to the database, forming a vast experiential knowledge graph.

[0026] 102. Receive the working condition parameters of the current casting task, and match similar historical cases from the process database based on the working condition parameters to form a similar case set.

[0027] It should be noted that the factory has received a production order for a new type of high-pressure turbine blade. The server analyzes the specific operating parameters of the current task: the material is still K4169 nickel-based alloy, but the gross weight per piece has changed to 2.6 kg, and the maximum wall thickness has increased to 13 mm. The currently set pouring temperature is 1460 degrees Celsius, the shell preheating temperature is 1040 degrees Celsius, the furnace vacuum is maintained at 0.4 Pascals, and the planned average pouring rate is increased to 0.32 kg / s.

[0028] The server, carrying these current parameters, enters the process database for a full-database weighted scan and comparison: a historical case A is matched (i.e., case TB01 in step 101). The system finds that its gross weight of 2.5 kg is extremely close to the current one; the temperature difference between casting and the mold shell is minimal; and the rate deviation is within a reasonable range. With all core parameters highly consistent, the system assigns case A a similarity score as high as 95%.

[0029] Subsequently, a historical case B (a record of a slightly smaller blade) was matched. This case had a smaller deviation in operating conditions, and the system's overall score gave it a similarity score of 98%.

[0030] Then, it was matched to historical case C (a record of a large guide vane). Due to its high gross weight of 5.0 kg and excessive temperature deviation, its reference value was extremely low, and its score was only 45%.

[0031] A similarity score of 90% or higher is preset as a valid reference threshold. After a full database scan, the system automatically removes data with excessively low scores and extracts Case A, Case B, and other high-quality historical cases with a matching score of 90% or higher. These cases and their associated vibration parameter combinations are packaged and categorized to form a similar case set for the current task.

[0032] 103. The vibration parameters recorded in the set of similar cases are comprehensively processed to obtain the reference vibration parameters for the current task.

[0033] It should be noted that the system extracts the most valuable historical case parameters and scores from a set of similar cases: Case B (Core Reference, 98% Similarity): Excitation frequency 118 Hz, amplitude 0.32 mm, start-up delay 1.4 seconds, duration 18 seconds.

[0034] Case A (highly referenced, 95% similarity): excitation frequency 120 Hz, amplitude 0.30 mm, start-up delay 1.5 seconds, duration 20 seconds.

[0035] Case D (marginal reference, 92% similarity): excitation frequency 125 Hz, amplitude 0.28 mm, start-up delay 1.6 seconds, duration 22 seconds.

[0036] To derive the baseline parameters for the current task, the server performs a weighted fusion of these parameters in the background. Taking excitation frequency as an example, the server multiplies the frequency value of each case by its corresponding similarity weight percentage, then sums these products and finally divides by the sum of the weight percentages of all cases. This calculation method ensures that historical experience with higher similarity plays a more dominant role in the final result. The system performs the same fusion process on all dimensions, including amplitude, delay time, and duration.

[0037] After weighted fusion of the data, the server output a preliminary scheme customized for the current 2.6 kg turbine blade, namely the baseline vibration parameters for the current task: excitation frequency of approximately 121 Hz, vibration amplitude of approximately 0.30 mm, vibration start time of 1.5 seconds after the start of pouring, and duration of approximately 20 seconds.

[0038] 104. The working parameters of the current casting task are analyzed using the energy threshold theory, and the reference vibration parameters are calibrated to obtain the vibration parameters.

[0039] It should be noted that the built-in analysis model began its simulation. The system found that the current task's gross weight (2.6 kg) and maximum wall thickness (13 mm) have increased compared to historical baselines, resulting in greater solidification resistance of the molten metal inside the shell. To ensure that the vibration energy can penetrate to the center of the wall thickness and completely break up the initial dendrites, the system calculated that the minimum penetration energy threshold required for the current condition is approximately 5% higher than the baseline. If the baseline parameters (121 Hz, 0.30 mm) are used directly, the resulting excitation energy risks causing micro-shrinkage and loosening in the center of the thick wall.

[0040] Based on energy gap and fluid dynamics analysis, the system performs the following safety calibration: Based on fluid dynamics simulations, it was determined that at the current viscosity, to avoid the risk of violent surface turbulence and air entrapment that might be caused by increased amplitude, increasing the excitation frequency was the preferred option. However, increasing the frequency would also exacerbate fluid disturbances. Therefore, the system calculations confirmed that, under this specific operating condition, the turbulence increment resulting from fine-tuning the frequency from 121Hz to 125Hz was still within a controllable range and could effectively increase the vibration energy to penetrate the thickened wall center. By increasing the vibration frequency, the total input energy reliably exceeded the 5% increase threshold requirement.

[0041] Secondly, crucial timing adjustments were made. While the increased pouring rate (reaching 0.32 kg / s) slightly shortened the total pouring time (to approximately 8.1 seconds), this higher molten metal flow rate also resulted in a greater initial impact force, causing the initial turbulence at the bottom of the mold cavity to be higher than the baseline condition. To ensure the molten metal surface fully stabilized and to avoid the introduction of gas into the molten metal due to high-frequency excitation during periods of violent surface fluctuation, the system decisively extended the vibration delay time from 1.5 seconds to 1.7 seconds. Simultaneously, to ensure the high-frequency vibration fully engages during the initial solidification phase following the increased wall thickness, the vibration duration was extended from 20 seconds to 22 seconds.

[0042] Server output vibration parameters: excitation frequency 125 Hz, vibration amplitude 0.30 mm, start-up delay 1.7 seconds, duration 22 seconds.

[0043] 105. During the casting process, drive the vibration equipment to operate at vibration parameters to complete the casting, and store the effective process data formed in this casting as a new case in the process database.

[0044] It should be noted that within the vacuum melting furnace workshop, the automated casting system operates according to set conditions. High-temperature molten alloy at 1460 degrees Celsius is injected into the preheated mold at a rate of 0.32 kg / s, and a timer is started. When 1.7 seconds have elapsed, the molten metal has smoothly filled the bottom of the cavity and its kinetic energy has decayed, at which point the servo-driven vibration platform at the bottom intervenes precisely. The platform applies vertical vibration at 125 Hz and 0.30 mm for 22 seconds. This process perfectly covers the filling period and the most critical initial solidification period, with high-frequency vibration effectively promoting the filling of the tiny corner cavities by the molten metal.

[0045] After cooling and shelling, the casting entered quality inspection. The surface was smooth and free of cold shuts, and the dimensional accuracy met requirements. X-ray inspection revealed no internal shrinkage cavities. Metallographic analysis showed fine and uniform grains in the cross-section, with a metallurgical density of 99.7%. The system determined the casting task to be a complete success, and the data was marked as high-quality and valid.

[0046] After confirmation of validity, the server will structure and package the entire set of data, assign a new number, and store it in the process database. The archived files are shown in Table 1 below: Table 1

[0047] The system not only completed the high-quality casting task, but also accumulated valuable new experience for future tasks with similar working conditions.

[0048] Please see Figure 2 and Figure 3 Another embodiment of the precision casting method based on simultaneous pouring and vibration in this invention includes: 201. Construct a process database that includes multiple historical casting cases, with each historical casting case recording the corresponding combination of operating parameters and vibration parameters.

[0049] Specifically, based on the energy threshold theory, a set of key parameters for describing casting conditions and vibration effects is determined to form a key parameter set; process data from multiple completed historical casting cases are collected, and corresponding parameter values ​​are extracted from the process data of each historical case according to the key parameter set to form a historical casting dataset; the parameter values ​​extracted from each case in the historical casting dataset are associated with and stored with the corresponding casting quality evaluation results.

[0050] It should be noted that, for the construction and feature extraction of the A356 aluminum alloy automotive control arm process database, redundant information in the production records needs to be removed. Therefore, the energy threshold theory is introduced. The core criterion of this theory is that, in order to completely break the dendritic lap network in the early stage of molten metal solidification and eliminate internal shrinkage porosity, the effective excitation power input externally must be greater than the sum of the inherent viscous dissipation power of the molten metal and the solidification resistance. Based on this theory, the core variables that truly dominate the casting quality and solidification dynamics are selected, thereby constructing a concise, efficient process database with deep learning value.

[0051] For the precision casting process of A356 aluminum alloy automotive control arms using simultaneous pouring and vibration, the system, based on solidification heat transfer and fluid mechanics, established the following key parameter set: Operating parameters include pouring temperature, shell preheating temperature, and casting gross weight. These three parameters directly determine the initial enthalpy of the molten metal, the temperature gradient at the solidification interface, and the total latent heat that must be released before complete solidification. Secondly, vibration parameters include excitation frequency, vibration amplitude, and the effective vibration intervention duration that must be recorded to ensure closed-loop integrity. These three parameters determine the total mechanical destructive kinetic energy applied to the molten metal by the external system and its period of action.

[0052] The system interfaces with the factory's underlying MES (Manufacturing Execution System) to retrieve the original IoT records of multiple A356 control arm casting batches completed within the past year. Using a set of key parameters as a data filter, the system accurately extracts the required feature vectors from complex reports.

[0053] Taking historical high-scoring batch case number 2026-CA-050 as an example, the specific parameter values ​​extracted by the system are: pouring temperature 715 degrees Celsius, shell preheating temperature 310 degrees Celsius, and casting gross weight 3.2 kg; the corresponding applied servo excitation frequency is 85 Hz, vibration amplitude is 0.40 mm, and effective vibration intervention duration is 15 seconds. After extraction, this highly structured numerical sequence constitutes the core parameter profile of this historical case.

[0054] The process database needs not only process parameters but also instructive feedback. The system automatically retrieved the final inspection report from the non-destructive testing and mechanics laboratory regarding control arm number 2026-CA-050: X-ray inspection showed that the internal pinholes of this batch reached an excellent level (Grade 1); tensile testing of the sample yielded a yield strength of 240 MPa; and microscopic metallographic analysis showed significant deterioration and spheroidization of the eutectic silicon. The overall assessment label was A (Excellent).

[0055] The extracted process feature set is uniquely bound to the quality assessment results using a primary key. The system then uses the same logic to clean, extract, associate, and store massive amounts of historical cases, completing the underlying architecture of the process knowledge graph.

[0056] 202. Receive the working condition parameters of the current casting task, and match similar historical cases from the process database based on the working condition parameters to form a similar case set.

[0057] Specifically, key parameters for similarity evaluation are selected from the working parameters of the current casting task to form a subset of key parameters; for each historical case in the process database, the parameter differences between the historical case and the current task are evaluated based on the subset of key parameters to obtain the corresponding difference evaluation value; based on the difference evaluation value, multiple historical cases are selected from the process database as similar cases to form a set of similar cases.

[0058] Furthermore, based on the material type in the working parameters of the current casting task, the weight coefficients corresponding to each key parameter are obtained from the preset weight configuration rules; for historical cases in the process database, the specific difference between them and the current task on each key parameter is calculated; the specific difference is weighted using the weight coefficients to obtain the weighted difference of each key parameter; the weighted differences of all key parameters are summed to obtain the difference evaluation value that represents the overall difference.

[0059] It should be noted that when faced with a brand new production order, the system does not rely on subjective judgment based on human experience. Instead, it uses a rigorous weighted difference calculation to accurately screen out the combination of past successful cases that best fits the current thermodynamic and kinetic conditions from a vast process database.

[0060] The manufacturing workshop issued a production order for a batch of new A356 aluminum alloy control arms with slightly adjusted dimensions. The system simultaneously received the planned operating parameters for this task: the planned pouring temperature was set at 720 degrees Celsius, the shell preheating temperature was set at 315 degrees Celsius, and due to the slight adjustment in dimensions, the gross weight of a single casting increased to 3.3 kg.

[0061] The system's underlying algorithm identifies the current operating object as A356 aluminum alloy. Given the significant differences in the sensitivity of different alloys to various operating parameters, the system automatically retrieves A356-specific weighting coefficients from the material property knowledge base: for this alloy, pouring temperature has the most significant impact on filling fluidity and secondary dendrite arm spacing, thus assigning it the highest weighting coefficient of 0.5; the shell preheating temperature determines the solidification cooling rate, assigning it a weighting coefficient of 0.3; and the casting gross weight affects the overall heat capacity, assigning it a weighting coefficient of 0.2.

[0062] The parameter list of the current new task is constructed into a target vector, and a full comparison is performed in the database. The following example illustrates this: The excellent historical case 2026-CA-050 entered in step 201 is used as an example. Calculate the absolute differences of each physical quantity under the same dimensions: the difference in pouring temperature is 5 degrees Celsius (720-715), the difference in shell temperature is 5 degrees Celsius (315-310), and the difference in gross weight of casting is 0.1 kg (in order to balance the order of magnitude of each physical quantity, the difference of 0.1 kg is normalized and mapped to the standard value of 10).

[0063] These absolute differences are weighted using the specific weighting coefficients obtained in the first step: the weighted difference for casting temperature is 2.5 (i.e., The weighted difference in shell temperature is 1.5 (i.e.) The weighted difference in gross weight is 2.0 (i.e., the mapped value). ).

[0064] By aggregating and summing the weighted differences, the overall difference evaluation value between the historical case 2026-CA-050 and the current new task is 6.0. In this quantitative evaluation system, the lower the difference evaluation value, the higher the reference value of the historical case for the current task.

[0065] Through high-speed computation, the system traversed the entire database and found another set of similar cases with a difference rating of 3.5, while some cases with large differences in cross-sectional wall thickness or temperature range scored as high as 45. The system triggered a dynamic truncation mechanism, setting a difference rating of ≤10 as the threshold for high similarity, automatically removing all low-quality or irrelevant data, and extracting and packaging multiple high-scoring historical records, including 2026-CA-050, to formally constitute a set of similar cases specific to the current task.

[0066] 203. The vibration parameters recorded in the set of similar cases are comprehensively processed to obtain the reference vibration parameters for the current task.

[0067] Specifically, vibration parameters recorded in each historical case are read from a set of similar cases to form an original set of vibration parameters; the original set of vibration parameters is analyzed based on the energy threshold theory to identify parameters that meet the vibration validity criteria, thus forming an effective set of vibration parameters; the parameter values ​​in the effective set of vibration parameters are comprehensively calculated to obtain the benchmark vibration parameters.

[0068] Furthermore, based on the energy threshold theory, the vibration energy factor corresponding to each vibration parameter in the effective vibration parameter set is calculated; according to the numerical distribution of the vibration energy factor, vibration parameters located in the preset preferred factor range are selected from the effective vibration parameter set to form a core parameter subset; for multiple vibration parameters in the core parameter subset, their frequency and amplitude components are synthesized to obtain the reference vibration parameters.

[0069] It should be noted that the system first selects a reference case pool based on the similarity of operating conditions. However, similar operating conditions may correspond to various different vibration strategies with varying effects. Therefore, before synthesizing the baseline parameters, the system introduces a validity criterion based on energy threshold theory. By calculating the vibration energy factor, a physical quantity characterizing the actual destructive kinetic energy, the system further selects cases from the reference case pool that have vibration energy factors that match the thermodynamic requirements of the operating conditions and have been verified as "excellent" by historical quality results. These cases form a subset of core parameters, ensuring the superiority of the synthesized basis.

[0070] A deep analysis was performed on the similar case set established in step 202, and vibration parameter sequences of four representative historical cases were extracted: Case A (score 3.5, extremely similar): excitation frequency 82 Hz, amplitude 0.42 mm, vibration duration 15 seconds.

[0071] Case B (i.e., the aforementioned CA-050 case): excitation frequency 85 Hz, amplitude 0.40 mm, vibration duration 15 seconds.

[0072] Case C (Satisfactory rating): Excitation frequency 90 Hz, amplitude 0.35 mm, vibration duration 15 seconds.

[0073] Case D (score near threshold boundary): excitation frequency 55 Hz, amplitude 0.50 mm, vibration duration 12 seconds.

[0074] The above four sets of three-dimensional data arrays constitute the original set of vibration parameters to be processed in the current task.

[0075] During dendrite fragmentation and grain refinement, the coupled output of excitation frequency and amplitude determines the energy transfer depth. The system utilizes a built-in algorithm based on energy threshold theory to quantify the physical effectiveness of each parameter set in the original dataset. The formula for calculating the vibration energy factor is defined as follows: ,in For frequency, For amplitude, and An empirical index set according to the material (for A356 alloy, it is usually taken as...). =1.5, =2.0); The calculation results show that the vibration energy factors (representing the effective mechanical breaking kinetic energy transmitted into the melt) of Case A, B, and C are 125, 120, and 115 (dimension unitized), respectively; while Case D, due to its low excitation frequency, cannot form an effective shear wave resistance in the viscous region of the fluid even with a relatively large amplitude, and its comprehensive energy factor is only 75.

[0076] For the new task involving 3.3 kg, the system determined that only parameter combinations with energy factors between 110 and 130 could effectively break up the initial dendritic network without causing violent splashing. Therefore, Case D (energy factor 75) was deemed not to meet the vibration effectiveness criterion and was completely removed from the reference pool; the three sets of parameters A, B, and C passed the review and constituted a high-purity, high-reliability core parameter subset.

[0077] After obtaining a subset of core parameters, the system initiates parallel mathematical smoothing synthesis operations on the three independent components of frequency, amplitude, and duration: Frequency component synthesis: The average value of 82, 85, and 90 Hz is calculated and adaptively weighted to obtain a synthesized average value of 85.6 Hz. The system automatically rounds it to 86 Hz according to the control accuracy of the servo device.

[0078] Amplitude component synthesis: Calculations are performed on 0.42, 0.40, and 0.35 mm, and the smoothed output is 0.39 mm.

[0079] Duration component synthesis: The stable intervention times of the three cases were integrated, and the baseline duration was uniformly determined to be 15 seconds.

[0080] Thus, the system successfully countered historical interference and derived and synthesized a set of reference vibration parameters (excitation frequency 86 Hz, vibration amplitude 0.39 mm, duration 15 seconds) for the current A356 control arm, which are both safe and effective.

[0081] 204. The working parameters of the current casting task are analyzed using the energy threshold theory, and the reference vibration parameters are calibrated to obtain the vibration parameters.

[0082] Specifically, the working conditions and reference vibration parameters of the current casting task are obtained to form a comprehensive input parameter set; the comprehensive input parameter set is analyzed based on the energy threshold theory to determine the adjustment direction required for the reference vibration parameters; the reference vibration parameters are numerically calibrated according to the adjustment direction to obtain the vibration parameters.

[0083] Furthermore, the comprehensive input parameter set is converted into a comprehensive parameter vector representing the current casting state; the comprehensive parameter vector is matched with multiple pre-stored empirical parameter vectors, each empirical parameter vector being associated with a historically successful parameter adjustment direction; based on the matching results, a parameter adjustment direction suitable for the current casting state is selected from the historically successful parameter adjustment directions associated with the empirical parameter vectors.

[0084] It should be noted that by extracting the characteristics of the current task's operating conditions compared to the historical average, the system locks in the macroscopic direction of adjustment, and then directly substitutes them into rigorous physical equations to calculate the critical excitation power required to cope with the current thermodynamic fluctuations, thereby performing precise numerical calibration of the reference parameters.

[0085] The latest working condition data of the current task (gross weight of casting 3.3 kg, pouring temperature 720℃, shell preheating temperature 315℃) is captured and mapped with the newly obtained reference vibration parameters (frequency 86 Hz, amplitude 0.39 mm) to form a comprehensive parameter vector [3.3,720,315,86,0.39] that represents the current casting state.

[0086] The system places this vector into a high-dimensional empirical space for matching and mapping. The results show that the current operating condition exhibits a typical composite characteristic: increased weight leads to a rise in overall solidification resistance, and a widening cooling temperature difference leads to a thickening of the chilled layer. Based on this, the system extracts the general direction of parameter adjustment for this characteristic from past successful experiences: maintaining the amplitude to prevent boundary fluid overflow, and directionally increasing the high-frequency to compensate for the deep solidification resistance.

[0087] In order to translate the macroscopic direction of frequency enhancement and amplitude preservation into specific equipment control values, the system activates the critical vibration penetration power demand formula based on the underlying logic of energy threshold theory:

[0088] in: The critical vibrational power (W) required to completely break the internal dendrite network under this working condition. The system's liquid vibration damping constant is calibrated for A356 aluminum alloy (taken as 2.5W / kg); W is the current gross weight of a single casting (3.3kg). This is the actual pouring temperature (720℃). This is the actual shell temperature (315℃). The intrinsic liquidus temperature of alloy A356 is 615℃.

[0089] The numerator under the square root represents the heat transfer driving force of the entire system. The greater the temperature difference, the faster the cooling, and the higher the power requirement for external kinetic energy. The denominator represents the superheat of the molten metal itself. The lower the superheat, the more viscous the fluid, and the greater the vibration power consumed.

[0090] Substituting the specific values ​​of the current task into the formula: the numerator (heat transfer driving force) is 720-315=405; the denominator (alloy superheat) is 720-615=105. The ratio between the two is approximately 3.857, and taking the square root yields a coefficient of approximately 1.964.

[0091] Calculate the critical power required to ensure high-quality molding. W.

[0092] The system reverse-engineers the baseline parameters. Under the laminar flow assumption, the average power dissipation density generated by vibration in a viscous fluid can be approximately expressed as: ,in Let f be the dynamic viscosity and f be the frequency. The amplitude is given. Based on the physical property calculations of A356 alloy, if the original settings (86 Hz, 0.39 mm) are followed, according to the simplified non-Newtonian fluid dynamics damping model, the effective output power is approximately 14.5 W, which cannot exceed the energy threshold of 16.2 W, and is very likely to cause micro-shrinkage in thick and large parts.

[0093] Adhering strictly to the guidance of the first step, the system was locked at an amplitude of 0.39 mm. Utilizing the positive correlation between excitation power and frequency within the fluid region, the calculation target was directed towards the frequency component. Through reverse engineering, the system precisely increased the frequency to 91 Hz, at which point the expected output power just barely exceeded the safety boundary of 16.2 W. This yielded the preliminary vibration parameters after calibration (excitation frequency 91 Hz, amplitude 0.39 mm).

[0094] 205. During the casting process, drive the vibration equipment to operate at vibration parameters to complete the casting, and store the effective process data formed in this casting as a new case in the process database.

[0095] Specifically, equipment control commands are obtained based on vibration parameters; during the casting process, the equipment control commands are executed to drive the vibration equipment to operate, and real-time operating data of the casting process are collected simultaneously; after the casting is formed, the casting quality is evaluated to obtain the quality evaluation result of this casting task; the vibration parameters, real-time operating data and quality evaluation results are linked and integrated into the casting process record; the casting process record is stored as a new historical case in the process database.

[0096] It should be noted that the edge computing node on the manufacturing site receives the parameter command (excitation frequency 93 Hz, vibration amplitude 0.41 mm) verified in step 206. Through digital-to-analog conversion, this command is compiled into an electrical pulse signal that the servo drive can directly recognize.

[0097] Inside the vacuum casting chamber, a robotic arm holds molten A356 aluminum alloy at 720 degrees Celsius and smoothly and rapidly pours it into a preheated shell at 315 degrees Celsius. The moment the sensors detect that the melt has filled the critical area of ​​the cavity, a servo-driven multi-axis vibration platform on the base is precisely activated. Strictly adhering to the high-frequency micro-amplitude characteristics of 93 Hz and 0.41 mm, the vibration platform applies intense kinetic energy penetration to the shell assembly along the vertical Z-axis and continuously intervenes for a complete 15-second cycle under built-in timing logic. This period perfectly covers the late stage of molten metal filling and the most dangerous stage of coarse primary crystal nucleation. During this time, observation through a stroboscopic vision system shows stable fluctuations in the liquid level on the cavity surface, with no air entrapment or droplet splashing.

[0098] After the molten metal solidifies and cools down, it undergoes a complete set of automated sand removal and standard T6 heat treatment processes. The batch of control arm entities (gross weight up to 3.3 kg) is then sent to the testing center.

[0099] The stringent physical testing report showed that the casting's dimensions perfectly matched the tolerances of the 3D CAD model. Crucially, combined X-ray and ultrasonic testing demonstrated excellent consistency in metallurgical density in the nodal areas, where slow solidification of thick sections could lead to internal porosity; there were no macroscopic defects such as shrinkage cavities or porosity. Subsequent metallographic sectioning and tensile testing revealed that the eutectic silicon structure was thoroughly pulverized and spherically dispersed. The measured yield strength of the casting reached 248 MPa, and the elongation was as high as 9.0%. Based on this data, the system automatically generated a final release rating of Quality Grade A (Excellent).

[0100] After confirming that the physical casting meets the highest industry standards, the server initiates the data closed-loop protocol. The system deeply and structurally binds the actual collected furnace and preheating temperatures, the final corrected vibration execution parameters, and the excellent quality inspection feedback results, integrating them into a completely new set of high-quality casting process records, and directly writes them into the process master library constructed in step 201. The newly implemented structured archive is shown in Table 2 below: Table 2

[0101] 206. After obtaining the vibration parameters, the following vibration parameter verification steps are also included: Based on the working conditions of the current casting task, the physical property parameters of the casting material are obtained to form a material property parameter set; the vibration parameters and the material property parameter set are input into the vibration effect evaluation model constructed based on the energy threshold theory, and the vibration effect evaluation value is output; based on the comparison result between the vibration effect evaluation value and the preset empirical threshold range, it is determined whether a parameter correction instruction is obtained; if a parameter correction instruction is obtained, the vibration parameters are compensated and corrected once according to the energy threshold theory to obtain the corrected vibration parameters, which are then used as the vibration parameters for driving the vibration equipment.

[0102] Furthermore, the vibration effect evaluation value is compared with the boundary value of the preset empirical threshold range to calculate the evaluation value deviation; based on the material property parameter set and the evaluation value deviation, the preset correction rule table is searched to determine the corresponding parameter correction factor; the frequency and amplitude components in the vibration parameters are adjusted using the parameter correction factor to obtain the corrected vibration parameters.

[0103] It should be noted that, as a crucial safeguard connecting the purely theoretical calculations (step 204) and the physical execution (step 205), this step involves retrieving the liquid physical properties of the alloy at a specific temperature and, in conjunction with a finite element digital simulation model, performing a simulation exercise on the newly obtained parameters (91 Hz, 0.39 mm) before their official release. This step aims to capture microscopic property deviations that are difficult to cover by macroscopic thermodynamic formulas and to implement a final, fallback parameter compensation.

[0104] By delving into the material property database, the microscopic properties of A356 aluminum alloy under the current casting environment of 720 degrees Celsius were retrieved. Key physical indicators extracted include: a liquid metal density of 2.38 g / cm³ at this temperature, a dynamic viscosity coefficient as high as 1.2 mPa·s, and an inherent solidification shrinkage rate of approximately 6.1% during bulk phase transformation. These highly sensitive physical property data constitute the set of material property parameters used for simulation verification.

[0105] The parameters to be verified (excitation frequency 91 Hz, vibration amplitude 0.39 mm) output from step 204, along with the aforementioned set of material property parameters, are jointly injected into the vibration effect evaluation model constructed in the background based on the fusion of energy threshold and computational fluid dynamics (CFD). The inputs of this model include current operating condition parameters, material property parameters, and vibration parameters to be verified; its core mechanism is to calculate the transient flow field and temperature field inside the cavity through CFD algorithm, and combine the energy threshold criterion to predict the tendency of shrinkage porosity in the central part; the final output is a quantitative evaluation value characterizing the degree of shrinkage porosity elimination.

[0106] The simulation fully considered the attenuation effect of the inherent viscous drag of A356 aluminum alloy at 1.2 mPa·s at 720℃ on the propagation of high-frequency micro-amplitude vibration waves. After simulated solidification of the casting in a digital environment, the model outputs a comprehensive quantitative index—the comprehensive excitation effectiveness evaluation value. This evaluation value is a normalized dimensionless index, ranging from 0 to 100, representing the expected achievement rate of vibration parameters in eliminating central shrinkage porosity under the current working conditions and material properties. 100 indicates complete elimination, while values ​​below 60 indicate a high risk. Based on extensive historical data, the lower limit of the evaluation value for achieving the "no shrinkage porosity" standard for thick-walled A356 alloy parts is 85. The simulation measured this evaluation value to be 82.

[0107] The system sets a lower bound of the empirical safety threshold of 85 for the absence of shrinkage cavities for this model of thick-walled aluminum alloy control arm. Given that the simulation evaluation value of 82 is lower than the lower bound of 85, the system determines that the parameters derived from the current theory still lack a slight penetration redundancy when facing extreme viscous conditions. It then triggers a hard parameter correction command and accurately calculates the deviation of the evaluation value as 3 (lower bound of threshold 85 minus the measured value 82).

[0108] To address this minor energy shortfall, the system automatically accesses the built-in energy compensation experience correction rule table based on the material type (A356) and the precise deviation of the assessment value (3). The system quickly locates the target range in the rule table, as shown in Table 3 below: Table 3

[0109] Simulation results show an evaluation value of 82, which is below the threshold of 85. The system background will actually initiate an automatic optimization program, starting with the current parameters (91Hz, 0.39mm) and fine-tuning along the gradient direction. After several iterations, when the parameter combination is adjusted to (93Hz, 0.41mm), the evaluation value reaches 86, meeting the safety threshold requirement. The result of this optimization process corresponds to the second-order compensation strategy in the preset correction rule base. To improve the response speed in the industrial field, the system directly uses a lookup table method. The current deviation of 3 clearly falls within the second-order interval of 2.1 to 4.0 in the table, and the instruction forcibly requires the frequency factor to increase by 2 Hz and the amplitude factor to increase by 0.02 mm. The system then superimposes these two compensation factors onto the original parameters.

[0110] At this point, the system had completely eliminated all potential molding hazards and output the corrected vibration parameters (excitation frequency 93 Hz, vibration amplitude 0.41 mm, constant intervention duration 15 seconds) after layers of digital refinement. These parameters were officially approved and issued to the PLC execution layer in the physical workshop.

[0111] Figure 4This is a schematic diagram of a precision casting device based on simultaneous pouring and vibration according to an embodiment of the present invention. The device 300 can vary considerably due to differences in configuration or performance. The device 300 includes a transmitter 301, a receiver 302, and a processor 303. The processor 303 can also be a controller. Figure 4 The device is designated as "controller / processor 303". Optionally, the device 300 may also include a modem processor 305, which may include an encoder 306, a modulator 307, a decoder 308, and a demodulator 309.

[0112] In one example, transmitter 301 modulates (e.g., analog-to-analog conversion, filtering, amplification, and up-conversion, etc.) the output sample to obtain an uplink signal, which is transmitted via an antenna to an access network device. On the downlink, the antenna receives the downlink signal transmitted by the access network device. Receiver 302 modulates (e.g., filtering, amplification, down-conversion, and digitization, etc.) the signal received from the antenna and provides an input sample. In modem processor 305, encoder 306 receives service data and signaling messages to be transmitted on the uplink and processes (e.g., formatting, encoding, and interleaving) the service data and signaling messages. Modulator 307 further processes (e.g., symbol mapping and modulation) the encoded service data and signaling messages and provides an output sample. Demodulator 309 processes (e.g., demodulates) the input sample and provides a symbol estimate. Decoder 308 processes (e.g., deinterleaving and decoding) the symbol estimate and provides decoded data and signaling messages to device 300. Encoder 306, modulator 307, demodulator 309, and decoder 308 can be implemented by a combined modem processor 305. These units perform processing according to the radio access technology adopted by the radio access network (e.g., LTE and other evolved systems access technologies). It should be noted that when device 300 does not include modem processor 305, the above-mentioned functions of modem processor 305 can also be performed by processor 303.

[0113] The processor 303 controls and manages the operation of the device 300, and is used to execute the processing procedures performed by the device 300 in the above embodiments of this disclosure. For example, the processor 303 is also used to execute various steps of the transmitting or receiving device in the above method embodiments, and / or other steps of the technical solutions described in the embodiments of this disclosure.

[0114] Furthermore, the device 300 may also include a memory 304 for storing program code and data for the device 300.

[0115] Understandable, Figure 4Only a simplified design of device 300 is shown. In practical applications, device 300 may include any number of transmitters, receivers, processors, modem processors, memory, etc., and all devices that can implement the embodiments of this disclosure are within the protection scope of the embodiments of this disclosure.

[0116] The present invention also provides a precision casting device based on simultaneous pouring and vibration, the precision casting device based on simultaneous pouring and vibration includes a memory and a processor, the memory stores computer-readable instructions, when the computer-readable instructions are executed by the processor, the processor performs the steps of the precision casting method based on simultaneous pouring and vibration in the above embodiments.

[0117] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when the instructions are executed on a computer, cause the computer to perform the steps of the precision casting method based on simultaneous pouring and vibration.

[0118] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0119] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0120] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A precision casting method based on simultaneous pouring and vibration, characterized in that, include: A process database containing multiple historical casting cases was constructed, with each historical casting case recording the corresponding combination of operating parameters and vibration parameters; Obtain the operating parameters of the current casting task, and match similar historical cases from the process database based on the operating parameters to form a similar case set; The vibration parameters recorded in the set of similar cases are processed to obtain the reference vibration parameters for the current task; Based on the operating parameters of the current casting task, and after calibrating the reference vibration parameters, vibration parameters are obtained; During the casting process, the vibrating equipment is driven to operate at the vibration parameters to complete the casting.

2. The precision casting method based on simultaneous pouring and vibration according to claim 1, characterized in that, Constructing the process database includes: Based on the energy threshold theory, a set of key parameters for describing the casting conditions and vibration effects are determined, forming a key parameter set. Collect process data from multiple completed historical casting cases, and extract corresponding parameter values ​​from the process data of each historical case based on the key parameter set to form a historical casting dataset; The parameter values ​​extracted from each case in the historical casting dataset are associated with and stored with the corresponding casting quality evaluation results.

3. The precision casting method based on simultaneous pouring and vibration according to claim 1, characterized in that, include: The vibration parameters recorded in each historical case are read from the set of similar cases to form the original set of vibration parameters; The original set of vibration parameters is analyzed to identify parameters that meet the vibration validity criteria, thus forming a set of valid vibration parameters. The reference vibration parameters are obtained by comprehensively calculating the parameter values ​​in the set of effective vibration parameters.

4. The precision casting method based on simultaneous pouring and vibration according to claim 3, characterized in that, Calculate the vibration energy factor corresponding to each vibration parameter in the set of effective vibration parameters; Based on the numerical distribution of the vibration energy factor, vibration parameters located within a preset preferred factor range are selected from the set of effective vibration parameters to form a core parameter subset; For multiple vibration parameters in the core parameter subset, their frequency and amplitude components are synthesized to obtain the reference vibration parameters.

5. The precision casting method based on simultaneous pouring and vibration according to claim 1, characterized in that, include: The working condition parameters of the current casting task and the reference vibration parameters are obtained to form a comprehensive input parameter set; Based on the comprehensive input parameter set, determine the required adjustment direction for the reference vibration parameters; The reference vibration parameters are numerically calibrated according to the adjustment direction to obtain the vibration parameters.

6. The precision casting method based on simultaneous pouring and vibration according to claim 5, characterized in that, A comprehensive parameter vector characterizing the current casting state is obtained based on the comprehensive input parameter set. The comprehensive parameter vector is matched with multiple pre-stored empirical parameter vectors, and each empirical parameter vector is associated with a historically successful parameter adjustment direction; Based on the matching results, a parameter adjustment direction suitable for the current casting state is selected from the historically successful parameter adjustment directions associated with the empirical parameter vector.

7. The precision casting method based on simultaneous pouring and vibration according to claim 6, characterized in that, When the selected parameter adjustment direction is the frequency increase and amplitude preservation direction, the corresponding equipment control value is calculated according to the preset critical vibration penetration power requirement formula, which is: ； in: The critical vibration power; Where W is the liquid vibration attenuation constant; and W is the current gross weight of a single casting. This refers to the actual pouring temperature; This refers to the actual shell temperature. This is the inherent liquidus temperature of the alloy.

8. The precision casting method based on simultaneous pouring and vibration according to claim 1, characterized in that, include: Equipment control commands are obtained based on the vibration parameters; During the casting process, the equipment control commands are executed to drive the vibration equipment to operate, and real-time operating data of the casting process are collected simultaneously. After the casting is formed, the casting is evaluated for quality, and the quality evaluation results are obtained. The vibration parameters, the real-time operating data, and the quality evaluation results are linked and integrated into a casting process record. The casting process record is stored as a new historical case in the process database.

9. The precision casting method based on simultaneous pouring and vibration according to claim 1, characterized in that, Also includes: Based on the working parameters of the current casting task, the physical property parameters of the casting material are obtained to form a set of material property parameters; The vibration parameters and the set of material property parameters are input into the vibration effect evaluation model, and the vibration effect evaluation value is output. Based on the comparison between the vibration effect evaluation value and the preset empirical threshold range, it is determined whether a parameter correction instruction is obtained; If the parameter correction instruction is received, the vibration parameters are compensated and corrected once to obtain the corrected vibration parameters, which are then used as the vibration parameters for driving the vibration equipment.

10. The precision casting method based on simultaneous pouring and vibration according to claim 9, characterized in that, The vibration effect evaluation value is compared with the boundary value of the preset empirical threshold range, and the deviation of the evaluation value is calculated. Based on the set of material property parameters and the deviation of the evaluation value, a preset correction rule table is searched to determine the corresponding parameter correction factor; The frequency and amplitude components in the vibration parameters are adjusted using the parameter correction factor to obtain the corrected vibration parameters.

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