Method for controlling time-varying disturbance and defect fluctuation in casting process of complex casting

Abstract

The invention provides a time-varying disturbance and defect fluctuation control method in a casting process of a complex casting, which comprises the following steps of: acquiring real-time temperatures of a mold casting mold and a casting interface and different depth positions in the casting mold in the whole casting process; building a high-precision casting process boundary condition model on the basis of casting process casting mold interface heat flow and a heat exchange coefficient between a casting mold and a casting which are inversely calculated according to the measured temperature, and setting time-varying disturbance parameters for the model for numerical simulation; analyzing a numerical simulation result to reveal the incidence relation between the time-varying disturbance behavior in the casting process and the defect evolution of the casting, and exploring the parameter fluctuation characteristics of the former and the influence rule on the latter; and according to the parameter fluctuation distribution characteristics and the sensitivity and influence mechanism to the looseness, a process parameter time-varying disturbance control strategy is obtained. According to the method, the time-varying disturbance in the casting process of the complex casting is controlled, and the problem of precision liquid forming quality fluctuation of the complex casting of an airspace engine is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of investment precision casting, and specifically, to a method for controlling time-varying disturbances and defect fluctuations during the casting process of complex castings. Background Art

[0002] The investment casting process is widely used in fields such as aerospace, automotive, and energy because it can produce castings with complex shapes and precise dimensions. The mold temperature is a very important parameter in the investment precision casting process, directly affecting the filling and solidification of the molten metal. In investment casting, the ceramic mold is usually heated to about 1000°C to minimize the temperature difference between the metal casting and the mold as much as possible. This high-temperature state ensures that the melt remains fluid during the filling process and avoids premature solidification. However, since the mold needs to be transferred from the roasting furnace to the mold chamber before pouring, the temperature of the mold shell will inevitably change during this process. These temperature changes will affect the cooling and solidification of the high-temperature melt during the filling process. The time-varying disturbance behaviors such as the boundary conditions and process parameters of the casting process increase the uncertainty and complexity of the entire process, forming knowledge laws that have not been mastered or are difficult to describe at present, resulting in the uncertainty of the mechanical properties of the castings and becoming a bottleneck problem for the quality control of complex casting.

[0003] Compared with traditional experimental methods, numerical simulation can quickly test and verify different process plans, provide detailed analysis data and visualization results, and provide accurate and reliable guidance for actual production. However, existing numerical simulation methods usually set the boundary condition coefficients that affect the numerical simulation results, such as the interfacial heat transfer between the casting and the mold and the heat transfer between the mold and the environment during the casting process, as fixed values, and fail to accurately reflect the dynamic change characteristics of the heat transfer coefficient in the actual casting process. This simplified treatment may lead to deviations between the simulation results and the actual situation, affecting the accurate prediction of the solidification process of the casting. Summary of the Invention

[0004] Aiming at the defects in the prior art, the purpose of the present invention is to provide a method for controlling time-varying disturbances and defect fluctuations during the casting process of complex castings.

[0005] The present invention provides a method for controlling time-varying disturbances and defect fluctuations during the casting process of complex castings, including:

[0006] Obtaining real-time temperature data at the interface between the mold and the casting and at different depths inside the mold during the entire casting process;

[0007] Calculating the heat flux coefficient at the mold interface and the heat transfer coefficient between the mold and the casting during the casting process based on the real-time temperature data;

[0008] Based on the heat flux coefficient at the mold interface and the heat transfer coefficient between the mold and the casting, building a boundary condition model for the casting process;

[0009] Add a time-varying perturbation parameter to the casting process boundary condition model for perturbation modeling and perform numerical simulation;

[0010] Based on the numerical simulation results, determine the correlation between the time-varying perturbation parameter in the casting process and the evolution of casting defects, so as to determine the fluctuation characteristics of the time-varying perturbation parameter and the influence law on casting defects;

[0011] According to the fluctuation characteristics of the time-varying perturbation parameter and the influence law on casting defects, determine the control strategy for time-varying perturbation and defect fluctuation, and optimize the casting process.

[0012] Further, the back-calculation of the heat flux coefficient at the mold interface and the heat transfer coefficient between the mold and the casting during the casting process based on the real-time temperature data includes:

[0013] Use the real-time temperature data at the interface between the mold and the casting and at different depths inside the mold shell to establish a one-dimensional heat conduction back-calculation model;

[0014] Based on the one-dimensional heat conduction back-calculation model, back-calculate the heat flux coefficient at the mold interface and the heat transfer coefficient at the mold-casting interface during the casting process.

[0015] Further, the establishment of the casting process boundary condition model, where: the setting of the boundary conditions is based on the temperature distribution on the mold surface, the temperature at different wall thicknesses inside the mold, and the heat transfer coefficient at the interface between the casting and the mold.

[0016] Further, adding a time-varying perturbation parameter to the casting process boundary condition model for perturbation modeling, where: according to the casting process boundary condition model, take the transfer time during the transfer of the mold from the roasting furnace to the pouring furnace as the time-varying perturbation parameter for perturbation modeling and simulation.

[0017] Further, take the time for the mold to be transferred from the roasting furnace to the pouring furnace as the time-varying parameter, where: by dynamically adjusting the boundary conditions of the model, incorporate the initial temperature of the mold, the temperature change of the mold during the transfer process, and the change of the transfer time into the numerical simulation model.

[0018] Further, the determination of the fluctuation characteristics of the time-varying perturbation parameter and the influence law on casting defects includes:

[0019] Based on the numerical simulation results, determine the influence mechanism of time-varying perturbation on defects and the correlation between time-varying perturbation and defects.

[0020] Further, the influence mechanism of the time-varying perturbation on defects includes: the action mechanism of the temperature gradient and the change of solidification rate on the formation of shrinkage porosity defects in the casting.

[0021] Further, the correlation between the time-varying perturbation and the defect includes: quantitatively constructing a mathematical correlation model between the mold transfer time and the volume and quantity of shrinkage porosity defects in the casting.

[0022] Further, the determination of the time-varying perturbation and the defect fluctuation control strategy includes: controlling the temperature of the mold during the transfer process, and / or enhancing the feeding capacity of the casting riser.

[0023] Further, after the optimized casting process, it includes: applying the optimized casting process to numerical simulation to verify its effectiveness.

[0024] Further, the method further includes: conducting production verification on the optimized casting process.

[0025] Compared with the prior art, the present invention has at least one of the following beneficial effects:

[0026] The method provided by the present invention can obtain the real-time temperature at the interface between the mold and the casting and at different depths inside the mold during the entire casting process in real time, and build a high-precision boundary condition model for the casting process based on the heat flux at the mold interface and the heat transfer coefficient between the mold and the casting calculated from the measured temperature. Numerical simulation is carried out by setting time-varying perturbation parameters for the model. By setting the temperature field and time-varying parameters of the actual casting process, the reliability of the model is improved, and the numerical simulation results are analyzed later to study the influence mechanism of the time-varying perturbation on the casting defects and the correlation between the two, and corresponding time-varying perturbation control strategies are proposed to optimize the casting process, so as to realize the control of the time-varying perturbation and the defect fluctuation during the casting process of complex castings, thus solving the problem of precision liquid forming quality control of complex castings for aerospace engines. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] By reading the detailed description of the non-restrictive embodiments with reference to the following drawings, other features, objectives and advantages of the present invention will become more obvious:

[0028] Figure 1 It is the process flow chart of the method for controlling the time-varying perturbation and the defect fluctuation during the casting process of complex castings in an embodiment of the present invention;

[0029] Figure 2 It is the schematic diagram of the quantity and volume of shrinkage porosity defects in the casting under different mold transfer times in an embodiment of the present invention;

[0030] Figure 3 It is the schematic diagram of the comparison of the fluorescence detection images of the key component outlet pipe of the liquid oxygen-kerosene engine oxygen pre-pressurizing pump prepared before and after implementing the control strategy in an embodiment of the present invention: where (a) is without using the control strategy, and (b) is after using the control strategy. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] The present invention will be described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made. These all belong to the protection scope of the present invention.

[0032] Referring to Figure 1 , a method for controlling time-varying disturbances and defect fluctuations during the casting process of complex castings provided by an embodiment of the present invention includes the following steps:

[0033] S1. During the entire casting process, obtain the real-time temperature data at the interface between the mold and the casting and at different depths inside the mold, and obtain the time when the mold is transferred from the roasting furnace to the pouring furnace;

[0034] Specifically, the real-time temperature data is the interface temperature between the shell and the casting during the pouring process, and the temperatures at different depths inside the shell (the shell is 10 mm, and different depths refer to 2 mm, 5 mm, and 7 mm of the shell) and other temperatures at different thicknesses;

[0035] S2. Inversely calculate the heat flux coefficient at the interface of the mold during the casting process and the heat transfer coefficient between the mold and the casting according to the real-time temperature data;

[0036] S3. Based on the heat flux coefficient at the interface of the mold and the heat transfer coefficient between the mold and the casting, build a boundary condition model for the casting process (i.e., a heat transfer coefficient boundary condition model at the casting-mold interface);

[0037] After obtaining the real-time temperatures at the interface between the shell and the casting and at different depths inside the shell during the casting process in step S1, the interface heat transfer coefficient between the shell and the casting, the convective heat transfer coefficient and the thermal radiation coefficient between the shell and the surrounding environment, etc. can be inversely calculated according to these temperature data. Input these inversely calculated data into the model, and then obtain the heat transfer coefficient boundary condition model at the casting-mold interface;

[0038] S4. Add time-varying disturbance parameters (i.e., time-varying parameters) to the boundary condition model of the casting process for disturbance modeling and numerical simulation;

[0039] Specifically, according to the heat transfer coefficient boundary condition model at the casting-mold interface, take the transfer time during the transfer of the mold from the roasting furnace to the pouring furnace as the time-varying disturbance parameter for disturbance modeling and simulation; the numerical simulation model is the model obtained by disturbance modeling. Compared with the general model, disturbance modeling adds time-varying parameters such as the shell transfer time (the numerical change of this parameter will disturb the casting quality, so it is also called a time-varying disturbance parameter);

[0040] S5. Determine the correlation between the time-varying disturbance parameters and the evolution of casting defects during the casting process based on the numerical simulation results, so as to determine the fluctuation characteristics of the time-varying disturbance parameters and the influence law on casting defects;

[0041] Specifically, based on the numerical simulation results, for the casting process under different mold transfer times, determine the change laws of the distribution, volume and quantity of shrinkage porosity defects;

[0042] S6. Determine the time-varying disturbance and defect fluctuation control strategies according to the fluctuation characteristics of the time-varying disturbance parameters and the influence law on casting defects, and optimize the casting process.

[0043] In the embodiment of the present invention, the temperature field setting refers to the interfacial heat transfer coefficient between the mold shell and the casting, as well as the convective heat transfer and radiation heat transfer coefficients between the mold shell and the surrounding environment. After obtaining the temperature data in step S1, the interfacial heat transfer coefficient between the mold shell and the casting and the convective heat transfer and radiation heat transfer coefficients between the mold shell and the surrounding environment during the pouring process are inversely calculated; the time-varying parameter refers to the "mold shell transfer time". In the embodiment of the present invention, the variable setting "mold shell transfer time" is added during the numerical simulation process to make the simulation results more in line with the actual situation.

[0044] In some embodiments, in step S1, a black box furnace temperature tracker is used to obtain the temperature. In step S3, the boundary conditions are set based on the measured data during the casting process, including the temperature distribution on the surface of the mold, the temperature gradient inside the mold (i.e., the temperature at different wall thicknesses inside the mold), and the interfacial heat transfer coefficient between the casting and the mold.

[0045] Furthermore, the setting of the boundary conditions combines the convective heat transfer and thermal radiation characteristics between the mold and the atmospheric environment. The addition of these two data of convective heat transfer and thermal radiation characteristics makes the numerical simulation model more in line with the actual casting process and further improves the accuracy of the numerical simulation results.

[0046] In some embodiments, in step S2, a one-dimensional heat conduction inverse calculation model is established using the real-time temperature data at the interface between the mold and the casting and at different depths inside the mold; based on the one-dimensional heat conduction inverse calculation model, the heat flux coefficient at the mold interface and the interfacial heat transfer coefficient between the mold and the casting during the casting process are inversely calculated according to the measured temperature.

[0047] In some embodiments, in step S4, the time for transferring the mold from the roasting furnace to the pouring furnace is used as the time-varying parameter, where: by dynamically adjusting the boundary conditions of the model, the initial temperature of the mold, the temperature change of the mold during the transfer process, and the change of the transfer time are incorporated into the numerical simulation model to reflect the heat loss of the mold during the transfer process and its influence on the casting process.

[0048] Exemplarily, the mold transfer time during the casting process is added as a time-varying parameter to the numerical simulation model for perturbation modeling, and five groups of different mold transfer times: 0s, 60s, 120s, 180s, and 240s are set for numerical simulation respectively.

[0049] In some embodiments, in step S5, based on the numerical simulation results, the influence mechanism of time-varying perturbation on defects and the correlation relationship between time-varying perturbation and defects are determined, so as to realize the quantitative analysis of the distribution, volume, and quantity change laws of shrinkage porosity defects for the casting process under different mold transfer times.

[0050] In a further embodiment, the influence mechanism of time-varying perturbation on defects includes: the action mechanism of the temperature gradient and the change of solidification rate on the formation of shrinkage porosity defects in the casting.

[0051] In a further embodiment, the correlation relationship between time-varying perturbation and defects includes: quantitatively constructing a mathematical correlation model between the mold transfer time and the volume and quantity of shrinkage porosity defects in the casting.

[0052] Exemplarily, the mold surface temperature, the mold temperature at the casting defect, the temperatures at different wall thicknesses of the mold, the riser temperature, the solidification time at the defect, the total volume of shrinkage porosity defects, and the total number of shrinkage porosity defects in the five groups of simulation results are extracted and analyzed and compared. By extracting the defect distribution data inside the casting, the correlation relationship between shrinkage porosity defects and the casting transfer time is constructed, as Figure 2 shown, Figure 2 which represents the simulation results of the total number and total volume of shrinkage porosity defects in the castings poured under different mold transfer times of 0, 60, 120, 180, and 240s. Figure 2 The results show that as the mold transfer time prolongs, the total number and total volume of shrinkage porosity defects in the casting also increase. Thus, the influence of time-varying perturbation on the formation mechanism of shrinkage porosity defects can be revealed. The action mechanism of the temperature gradient and the change of solidification rate on shrinkage porosity defects can also be analyzed emphatically.

[0053] In the above embodiments of the present invention, through the analysis of the numerical simulation results, a mathematical correlation model between the mold transfer time and the volume and quantity of shrinkage porosity defects in the casting is quantitatively constructed. This model reveals the action mechanism of the transfer time on the formation of shrinkage porosity defects in the casting based on the dynamic changes of the temperature gradient and the solidification rate.

[0054] In a further embodiment, determining the time-varying perturbation and defect fluctuation control strategy includes: controlling the temperature of the mold during the transfer process, and / or enhancing the feeding capacity of the casting riser.

[0055] Specifically, combining the research results on the influence mechanism of the mold transfer time on the shrinkage porosity defect, a time-varying disturbance and defect fluctuation control strategy for the casting process is proposed: shorten the mold transfer time to reduce the temperature loss of the mold during the transfer process; wrap the riser of the mold with heat-insulating cotton and fill the mold with sand before preheating to further insulate the mold while enhancing the riser feeding capacity. By setting a reasonable mold transfer time and matching corresponding mold insulation measures, the casting process is optimized to reduce the influence of the temperature field fluctuation during the transfer process on the casting quality.

[0056] In some embodiments, after optimizing the casting process, it includes: applying the optimized casting process to numerical simulation to verify its effectiveness, and the results are as Figure 3 shown.

[0057] In a further embodiment, the method further includes: conducting production verification on the optimized casting process. Combining with actual production for experimental verification, comparing the casting quality before and after optimization, and evaluating the reduction degree of shrinkage porosity defects and the improvement effect of casting performance, so as to verify the practical application value and reliability of this control method.

[0058] Figure 3 The figure shows a comparison schematic diagram of the quality inspection images (fluorescent inspection images) of the key component outlet pipe castings of the liquid oxygen kerosene engine oxygen pre-pressurizing pump prepared before and after implementing the control strategy of the embodiment of the present invention. Among them, (a) is the casting produced without using the optimized process, and (b) is the casting produced using the optimized process. It can be seen that there are many more fluorescent parts in (a) than in (b), indicating that (a) contains more quality defects than (b), proving that the optimized casting process can effectively reduce casting defects and improve casting quality.

[0059] The embodiment of the present invention proposes a time-varying disturbance control strategy by adjusting the mold transfer time and adding a mold insulation method. Combining numerical simulation and actual production verification, the optimized control strategy significantly reduces the volume and quantity of shrinkage porosity defects and improves the casting quality.

[0060] In the above embodiments of the present invention, the real-time temperatures at the interface between the mold and the casting and at different depths inside the mold during the entire casting process are obtained, and a high-precision boundary condition model for the casting process is established based on the heat flux at the mold interface and the heat transfer coefficient between the mold and the casting calculated from the measured temperatures. Time-varying perturbation parameters are set for the model for numerical simulation. By analyzing the numerical simulation results, the correlation between the time-varying perturbation behavior during the casting process and the evolution of casting defects is revealed, and the parameter fluctuation characteristics of the former and its influence on the latter are explored. According to the parameter fluctuation distribution characteristics and the sensitivity and influence mechanism on porosity, a control strategy for time-varying perturbations of process parameters is obtained. By controlling the temperature of the mold during the transfer process and improving the feeding capacity of the riser, the casting process is optimized. After X-ray inspection, it is found that under the improved casting process, the shrinkage porosity defects are significantly reduced, achieving the purpose of controlling the time-varying perturbations and defect fluctuations during the casting process.

[0061] The method in the above embodiments of the present invention can accurately simulate the quality of castings produced under different process parameters by adjusting the mold transfer time and environmental parameter settings for different casting geometries and process conditions, optimize the casting process, and effectively control the shrinkage porosity defects of complex thin-walled structure castings. For the castings produced under this control method, the total number of shrinkage porosity defects of the castings is reduced by 80%, and the total volume of shrinkage porosity defects is reduced by 90%. The above method is applicable to the production of high-end key castings such as aero-engine gas turbines.

[0062] In the above embodiments of the present invention, the real-time temperatures at the interface between the mold and the casting and at different depths inside the mold during the entire casting process are obtained, and a high-precision boundary condition model for the casting process is established based on the heat flux at the mold interface and the heat transfer coefficient between the mold and the casting calculated from the measured temperatures. Time-varying perturbation parameters are set for the model for numerical simulation. By analyzing the numerical simulation results, the correlation between the time-varying perturbation behavior during the casting process and the evolution of casting defects is revealed, and the parameter fluctuation characteristics of the former and its influence on the latter are explored. According to the parameter fluctuation distribution characteristics and the sensitivity and influence mechanism on porosity, a control strategy for time-varying perturbations of process parameters is obtained. By obtaining the real-time temperature data during the casting process and setting the model boundary conditions based on this to improve the accuracy of the numerical simulation model, and establishing a correlation model between the time-varying parameters and casting defects to reveal its action mechanism, and then a control strategy for time-varying perturbations is proposed to achieve the control of time-varying perturbations and defect fluctuations during the casting process of complex castings, thus solving the problem of precision liquid forming quality control of complex castings for aerospace engines.

[0063] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various deformations or modifications within the scope of the claims, which do not affect the essence of the present invention. The above preferred features can be combined arbitrarily without conflict.

Claims

1. A method for controlling time-varying disturbances and defect fluctuations in a complex casting process, characterized in that: include: Obtain real-time temperature data at the interface between the mold and the casting and at different depths inside the mold during the entire casting process; According to the real-time temperature data, the heat flow coefficient of the casting mold interface and the heat transfer coefficient between the casting mold and the casting are calculated; Based on the mold interface heat flow coefficient and the heat transfer coefficient between the mold and the casting, a casting process boundary condition model is constructed; Adding time-varying disturbance parameters to the casting process boundary condition model to perform disturbance modeling and numerical simulation; Based on the numerical simulation results, the correlation between the time-varying disturbance parameters of the casting process and the evolution of casting defects is determined, so as to determine the fluctuation characteristics of the time-varying disturbance parameters and their influence on casting defects; According to the fluctuation characteristics of the time-varying disturbance parameters and the influence rules on casting defects, the time-varying disturbance and defect fluctuation control strategy is determined to optimize the casting process.

2. The method according to claim 1, characterized in that The back-calculating of the heat flux coefficient of the mold interface and the heat transfer coefficient between the mold and the casting during the casting process according to the real-time temperature data includes: Using the real-time temperature data of the interface between the mold and the casting and different depth positions inside the mold, a one-dimensional heat conduction back-calculation model is established; Based on the one-dimensional heat conduction back-calculation model, the mold interface heat flow coefficient and the mold-casting interface heat transfer coefficient of the casting process are back-calculated.

3. The method according to claim 1, characterized in that The casting process boundary condition model is constructed, wherein: the boundary conditions are set based on the temperature distribution on the surface of the mold, the temperature at different wall thicknesses inside the mold, and the interface heat transfer coefficient between the casting and the mold.

4. The method according to claim 1, characterized in that: The time-varying disturbance parameters are added to the casting process boundary condition model for disturbance modeling, wherein: according to the casting process boundary condition model, the transfer time of the casting mold from the roasting furnace to the pouring furnace is used as the time-varying disturbance parameter to perform disturbance modeling and simulation.

5. The method according to claim 1, characterized in that The determination of the fluctuation characteristics of the time-varying disturbance parameters and the influence rules on casting defects includes: Based on the numerical simulation results, the influence mechanism of time-varying disturbance on defects and the correlation between time-varying disturbance and defects are determined.

6. The method according to claim 5, characterized in that The influence mechanism of the time-varying disturbance on defects includes: the mechanism of action of changes in temperature gradient and solidification rate on the formation of shrinkage defects in castings.

7. The method according to claim 5, characterized in that The correlation between the time-varying disturbance and the defect includes: quantitatively constructing a mathematical correlation model between the mold transfer time and the volume and number of shrinkage defects in the casting.

8. The method according to claim 1, characterized in that The strategy for determining the time-varying disturbance and defect fluctuation control includes: controlling the temperature of the casting mold during the transfer process, and / or improving the shrinkage compensation capacity of the riser.

9. The method according to claim 1, characterized in that: After the casting process is optimized, the method includes: applying the optimized casting process to numerical simulation to verify its effectiveness.

10. The method according to claim 9, characterized in that Also includes: The optimized casting process is then put into production for verification.

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