A Method for Optimizing the Gas Sealing Structure of a Bearing Box Based on Fluent

Abstract

The present invention discloses a method for optimizing the gas seal structure of a bearing box based on Fluent, which includes the following steps: establishing a geometric model of the bearing box and importing it into ANSYS, using SpaceClaim to establish a fluid domain and naming relevant components, using a mesh generation tool for mesh generation and inflation layer setting, importing the processed mesh file into Fluent, determining the calculation equation and particle properties, setting boundary conditions and solution parameters, initializing and iteratively calculating the model, performing post-processing statistics, modifying the geometric model parameters according to the post-processing results, repeating the above relevant calculation steps, and comparing the calculation results to obtain an optimal solution. The present invention uses Fluent software for simulation, and provides guidance for the optimal design of the gas seal structure of the bearing box by statistically analyzing the amount of impurity particles entering at the impurity inlet and the amount of impurities escaping at the bearing outlet, improving the optimization efficiency and reducing the cost.

Description

Technical Field

[0001] The present invention belongs to the technical field of bearing housing sealing structures, and particularly relates to a method for optimizing the gas sealing structure of a bearing housing based on Fluent. Background Art

[0002] With the continuous improvement of social demands, the current requirements for bearing housings are also getting higher and higher. They often need to maintain high speed, high precision, and long life in a harsh environment. Therefore, the sealing of bearing housings is particularly important, and gas sealing is a common method in bearing housing sealing.

[0003] However, in the actual production process, there are often situations where the gas source is insufficient or even cut off during the operation of the equipment. Therefore, when designing the gas sealing structure of the bearing housing, it is necessary to comprehensively consider the sealing performance of the structure itself in case of insufficient gas source and gas cut-off. Generally, experiments are used to optimize its sealing performance, but conventional experimental methods will cause high time costs and economic costs. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention provides a method for optimizing the gas sealing structure of a bearing housing based on Fluent, which is convenient to operate, can improve the optimization efficiency of the gas sealing structure of the bearing housing, and reduce costs.

[0005] The present invention is realized through the following technical solutions:

[0006] A method for optimizing the gas sealing structure of a bearing housing based on Fluent, comprising the following steps:

[0007] S1: Determine the gas sealing structure parameters of the bearing housing,

[0008] S2: Use 3D modeling software to model the bearing housing structure and import it into ANSYS;

[0009] S3: Use SpaceClaim to establish a fluid domain and name the relevant components;

[0010] S4: Use a mesh generation tool to generate meshes for the 3D model of the bearing housing and set the inflation layer;

[0011] S5: Import the mesh file obtained in S4 into Fluent and enable the turbulent energy model;

[0012] S6: Select the gas phase and discrete phase parameters;

[0013] S7: Set the boundary conditions and select the solver and relaxation factor. The boundary conditions include the gas source inlet, impurity inlet, and outlet;

[0014] S8: Initialize the model and set the transient iterative calculation;

[0015] S9: Determine whether the calculation converges. If the calculation residual is lower than the set value or the indicators in the report definition tend to be stable, it means the calculation converges; otherwise, it means it does not converge. At this time, it is necessary to improve the mesh quality or adjust the relaxation factor, and return to step S7;

[0016] S10: Use the Fluent post-processing sampling tool to count the number of particles entering at the inlet, the number of particles escaping at the outlet, and the distribution of particles in each region of the structure;

[0017] S11: Modify the gas seal structure parameters of the bearing box multiple times. After each modification of the gas seal structure parameters of the bearing box, repeat the above steps S1 - S10, and record the data of each structure modification, the particle distribution, and the ratio;

[0018] S12: Compare the particle distribution and ratio of multiple simulation analyses to obtain the optimal parameter conditions of the gas seal structure.

[0019] Further, in step S1, the gas seal structure parameters of the bearing box include the impurity channel height, the impurity channel shape, and the cavity size.

[0020] Further, in step S5, the turbulence energy model selects the k - epsilon, Realizable model, and Discrete Phase Model.

[0021] Further, in step S6, the discrete phase particle injection source type is set to surface, and the gas phase material is simplified to an ideal gas; the particle inlet flow rate is set according to the area - scaled flow rate, and the injection direction is the surface normal direction.

[0022] Further, in step S6, the operating pressure is set to atmospheric pressure, the gravitational acceleration is set according to the actual local gravity situation, and the operating density is given.

[0023] Further, in step S7, for the boundary conditions, the gas source inlet is given according to the actual situation of gas interruption or less gas, the outlet boundary is set as a pressure outlet, and a negative pressure is given. The formula for determining the negative pressure value is:

[0024]

[0025] In the formula: p is the negative pressure value, Pa; ρ is the air density, kg / m 3 ; Δv represents the velocity of the object relative to the surrounding air, m / s.

[0026] Further, in step S8, the initialization method is hybrid initialization, and the analysis mode is transient.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] Based on the research of the gas seal structure of the bearing box in actual production, the present invention combines simulation to evaluate the quality of the gas seal performance. By using the k-epsilon, Realizable model and Discrete Phase Model in Fluent, the present invention simulates the process of impurities entering the bearing box, monitors the amount of impurities entering the channel and the amount of impurity escape and generates a table file, counts the specific number of particles with the help of Excel, and judges the quality of the gas seal structure by comparing the ratio of the amount of impurity escape to the amount of entry. At the same time, the distribution of particles in the gas seal structure over a period of time can also be viewed with the help of Fluent post-processing to optimize the local structure. The present invention can reduce the time and cost required for a large number of experiments and improve the optimization efficiency of the gas seal structure of the bearing box. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is the overall flow chart of the present invention.

[0030] Figure 2 is a cross-sectional view of the first gas seal structure scheme of the bearing box.

[0031] Figure 3 is a cross-sectional view of the second gas seal structure scheme of the bearing box.

[0032] Figure 4 is a cross-sectional view of the third gas seal structure scheme of the bearing box.

[0033] Figure 5 is a cross-sectional particle distribution diagram of the first gas seal structure scheme of the bearing box.

[0034] Figure 6 is a cross-sectional particle distribution diagram of the second gas seal structure scheme of the bearing box.

[0035] Figure 7 is a cross-sectional particle distribution diagram of the third gas seal structure scheme of the bearing box. DETAILED DESCRIPTION OF THE INVENTION

[0036] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0037] For the optimization of the gas seal structure box of a certain bearing as shown in Figure 2 shown, as shown in Figure 1 shown, in the figure: 1 is the gas source inlet, 2 is the outlet, 3 is the cavity, 4 is the impurity inlet, and 5 is the impurity channel.

[0038] The present invention includes the following steps:

[0039] S1: Determine the first gas seal structure scheme of the bearing box (as shown in Figure 2In the figure shown, the impurity channel height is 0.5 mm, the shape of the impurity channel 5 is a rotary type, and the cavity size is 2 mm in height and 14.5 mm in length and other parameters.

[0040] S2: Use 3D modeling software such as SolidWorks (or Creo) to model the bearing housing structure and import it into ANSYS.

[0041] S3: Use SpaceClaim to establish the fluid domain and name the relevant components. Set the gas source inlet 1 as pressure inlet1, the impurity inlet 4 as pressure inlet2, and the outlet 2 as pressure outlet, and avoid setting it as wall.

[0042] S4: Use the mesh (or Fluent Meshing) meshing tool to perform mesh generation and inflation layer settings, verify mesh independence, and the final number of meshes is 82396.

[0043] S5: Import the mesh file obtained in step S4 into Fluent, and turn on the k-epsilon, Realizable model and Discrete Phase Model.

[0044] S6: Select the gas phase material property as ideal air, select the silicon particle property for the discrete phase particles, the diameter of the discrete phase particles is 0.1 mm, the injection speed is 0, the total flow rate is 1×10 -10 kg / s, the particle agglomerate release method is standard, and the drag criterion is spherical.

[0045] S7: According to the gas cut-off state, set the gauge pressure of the gas source inlet 1 to 0, set the gauge pressure of the impurity inlet 4 according to the actual situation to 0, set the gauge pressure of the outlet 2 to -10000 Pa, select SIMPLE for the solution scheme, and keep the solution parameters such as the relaxation factor as the default. Set the gravitational acceleration to -9.81 m / s2, the operating density to 1.225 kg / m 3 , the ambient pressure is 101325 Pa, and the operating density is 1.225 kg / m 3 .

[0046] Set the boundary of the outlet 2 as a pressure outlet to give a negative pressure, and the negative pressure value can be determined by the following formula:

[0047]

[0048] In the formula: p is the negative pressure value, Pa; ρ is the air density, kg / m 3 ; Δv represents the velocity of the object relative to the surrounding air, m / s.

[0049] S8: Initialize the model with a hybrid initialization method to ensure that the order of magnitude of the initialization calculation results is 10 -7 orders of magnitude. Set the time step to 0.01 s, the number of iteration steps to 25, and the total calculation time to 5 s. The analysis mode of the model is transient.

[0050] S9: Determine whether the calculation converges. If the calculation residual is lower than the set value or the indicators in the report definition tend to be stable, it means the calculation converges; otherwise, it means it does not converge. At this time, the mesh quality needs to be improved or the relaxation factor needs to be adjusted, and return to step S7.

[0051] S10: Use the Fluent post-processing sampling tool to count the number of particles entering at the statistical inlet and the number of escaping particles at the outlet and generate a file. At the same time, view the particle distribution in each region of the structure in the post-processing. The simulation results of Scheme 1 are shown in Figure 5 , the amount of structural particles entering is 9887, the amount going out at the outlet is 293, and the final proportion entering the bearing box is 2.9635%. And a large number of particles are distributed near the outlet end, indicating that the particle interception ability of the impurity inlet part of Scheme 1 is weak, and the structure of the impurity inlet part can be appropriately modified.

[0052] S11: Modify the structure. According to the instructions given in S10, increase the air cavity height by 1.5 mm and keep the others unchanged to obtain the structure of Scheme 2, as shown in Figure 3 . Repeat the above steps S1 - S10. The final simulation results of Scheme 2 are shown in Figure 6 , the amount of particles entering is 7557, the amount going out at the outlet is 175, and the final proportion entering the bearing box is 2.3157%. There are fewer particles distributed at the outlet end. Set the impurity outlet 6, and let the impurities spontaneously fall out of the sealing structure by gravity to obtain the structure of Scheme 3, as shown in Figure 4 . Repeat the above steps S1 - S10. The final simulation results of Scheme 3 are shown in Figure 7 , the amount of particles entering is 1247, the amount going out at Outlet 2 is 164, and the final proportion entering the bearing box is 13.1516%. The particles are mainly concentrated near the inlet and in the gas source channel. At the same time, the gauge pressure of the gas source inlet in step S7 can be modified, and multiple simulation analyses can be carried out, recording the data of each structure modification, the particle distribution, and the ratio.

[0053] S12: Modify the structure 2 times according to the method in S11. By comparing the particle distribution and ratio of the three times, finally select the best gas sealing structure. In this embodiment, it can be seen that the structure of Scheme 2 is significantly better than that of Scheme 1, and the particle interception ability of Scheme 3 is significantly weaker than that of Scheme 1 and Scheme 2. Therefore, in actual production, the structure of Scheme 2 can be preferentially selected, and through simulation, it can be prompted that the bearing box of the structure of Scheme 2 needs to be disassembled and cleaned regularly. At the same time, optimization can also be continued on the basis of Scheme 2.

[0054] For the gas seal structure, the traditional experimental method requires a large amount of time and economic costs, and the experimental results are difficult to specifically count and can only be roughly estimated. The method provided by the present invention can be fast, relatively accurate, and highly visual, and can provide great help for the optimal design of the gas seal structure.

Claims

1. A method for optimizing the gas seal structure of a bearing box based on Fluent, comprising the following steps: S1: Determine the gas seal structure parameters of the bearing box; S2: Use 3D modeling software to model the bearing box structure and import it into ANSYS; S3: Use SpaceClaim to establish the fluid domain and name the relevant components; S4: Use the mesh generation tool to perform mesh generation and set the inflation layer for the 3D model of the bearing box; S5: Import the mesh file obtained in S4 into Fluent and enable the turbulent energy model; S6: Select the gas phase and discrete phase parameters; S7: Set the boundary conditions, select the solver and relaxation factor. The boundary conditions include the gas source inlet, impurity inlet, and outlet; S8: Initialize the model and set the transient iterative calculation; S9: Determine whether the calculation converges. If the calculation residual is lower than the set value or the indicators in the report definition tend to be stable, it means the calculation converges. Otherwise, it means it does not converge. At this time, it is necessary to improve the mesh quality or adjust the relaxation factor, and return to step S7; S10: Use the Fluent post-processing sampling tool to count the number of particles entering at the inlet, the number of particles escaping at the outlet, and the distribution of particles in each region of the structure; S11: Modify the gas seal structure parameters of the bearing box multiple times. After each modification of the gas seal structure parameters of the bearing box, repeat the above steps S1 - S10, and record the data of each structure modification, the particle distribution, and the ratio; S12: Compare the particle distribution and ratio obtained from multiple simulation analyses to obtain the optimal parameter conditions of the gas seal structure.

2. The method for optimizing the gas seal structure of a bearing box based on Fluent according to claim 1, wherein the gas seal structure parameters in step S1 include the impurity channel height, impurity channel shape, and cavity size.

3. The method for optimizing the gas seal structure of a bearing box based on Fluent according to claim 1, wherein in step S5, the turbulent energy models selected are the k-epsilon, Realizable model, and Discrete Phase Model.

4. The method for optimizing the gas seal structure of a bearing box based on Fluent according to claim 1, wherein in step S6, the discrete phase particle injection source type is set to surface, and the gas phase material is simplified to an ideal gas; the particle inlet velocity is set according to the area-scaled velocity, and the injection direction is the surface normal direction.

5. The method for optimizing the gas seal structure of a bearing box based on Fluent according to claim 1, wherein in step S6, the operating pressure is set to atmospheric pressure, the gravitational acceleration is set according to the actual local gravity situation, and the operating density is given.

6. The method for optimizing the gas seal structure of a bearing box based on Fluent according to claim 1, wherein in step S7, when setting the boundary conditions, the gas source inlet is given according to the actual situation of gas interruption or less gas, the outlet boundary is set as a pressure outlet, and a negative pressure is given. The formula for determining the negative pressure value is: Where: p is the negative pressure value, in Pa; ρ is the air density, in kg / m 3 ; Δv represents the velocity of the object relative to the surrounding air, in m / s.

7. The method for optimizing the gas seal structure of a bearing box based on Fluent according to claim 1, wherein in step S8, the initialization method is hybrid initialization, and the analysis mode is transient.

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