Method for deformation control and error calculation of mutually contacted assembly surfaces based on Gaussian function characterization

Abstract

The invention discloses a deformation control and error calculation method for mutually contacted assembly surfaces based on Gaussian function representation, and belongs to the field of assembly error control and calculation. The method comprises the following steps: acquiring point cloud data of a contact surface, and calculating height parameters and space parameters of the surface; the height parameters are corrected to convert the non-Gaussian surface into a Gaussian surface convenient to analyze and calculate, and an assembly model containing manufacturing errors is established; carrying out finite element simulation analysis calculation on the model, solving the stress of the joint surface, comparing the stress measured by the pressure sensing diaphragm, correcting spatial parameters, and establishing an assembly model of a corrected Gaussian surface; parameterized simulation is carried out to optimize contact deformation of the surface; establishing an assembly body model based on differential optimal parameters, performing finite element simulation analysis calculation, solving assembly deformation of the joint surface, and calculating assembly deformation error spinor according to data; and calculating the transmission error of the two deformed surfaces of the improved assembly surface by using the Jacobian-spinor theory to obtain the size variation range of the closed ring.

Description

Technical Field

[0001] The invention relates to the field of controlling assembly deformation of mutually contacting assembly surfaces, and in particular to a deformation control and error calculation method of mutually contacting assembly surfaces based on Gaussian function characterization. Background Art

[0002] There are a large number of assembly surfaces in the assembly and connection process of parts, especially in high-end equipment such as aerospace and precision machine tools; the contact deformation of these assembly surfaces has an important impact on the performance of the whole machine, and the contact of the assembly surface is actually a rough surface contact containing multi-scale morphological features, which has an important impact on the deformation of the assembly surface, stress distribution, connection stiffness, etc. The study of assembly accuracy is closely related to the analysis of the morphological characteristics of the assembly surface. Due to the actual manufacturing process, it is inevitable that there will be geometric defects on the surface that deviate from the ideal design state, which directly lead to the generation of uneven gaps between assembly surfaces. This gap in turn causes the uneven pressure distribution of the assembly surface, as well as the non-uniform deformation of the assembly surface caused by the uneven pressure, which ultimately affects and forms the assembly error. The accuracy of the assembly error directly affects the processing accuracy of the processing equipment. Therefore, studying a deformation control and error calculation method for mutually contacting assembly surfaces based on Gaussian function characterization is of great significance to guide the improvement of assembly accuracy and ensure assembly quality. At present, the deformation control of the assembly based on measured data is mainly in terms of geometric dimensions, such as shape and deviation, and the calculation of assembly deformation error and the prediction of assembly error cannot meet the requirements.

[0003] Based on the above problems, the present invention characterizes the mutually contacting assembly surfaces based on Gaussian surfaces, obtains the deformation of the contact surface under the optimal tightening torque of the assembly based on the co-occurrence matrix, and predicts the assembly error. For high-end equipment such as aerospace and precision machine tools, it is of great significance to carry out the prediction and evaluation of assembly errors. Summary of the invention

[0004] In view of the fact that in the previous assembly error analysis, only the manufacturing error was considered without considering the deformation error of the joint surface after assembly, and no problem of improving the assembly deformation was proposed, the present invention provides a deformation control and error calculation method of mutually contacting assembly surfaces based on Gaussian function characterization, which can improve the accuracy of error transmission between assembly surfaces, improve assembly deformation, and improve the accuracy of assembly error prediction. Specifically including:

[0005] S1, obtaining point cloud data of two surfaces of the assembly that are in contact with each other, and calculating the height parameters and space parameters of the two surfaces respectively;

[0006] S2. The non-Gaussian surface obtained by fitting the point cloud data is converted into a Gaussian surface that is convenient for analysis and calculation by correcting the height parameter, and an assembly model containing two contact surfaces with manufacturing errors is established;

[0007] S3, performing finite element simulation analysis and calculation on the above assembly model to solve the bonding surface stress, and at the same time comparing the bonding surface stress obtained by measuring the actual assembly with the pressure-sensitive diaphragm, correcting the spatial parameters, and establishing an assembly model based on the modified Gaussian surface;

[0008] S4, performing a parametric simulation of the deformation of the joint surface to optimize the contact deformation of the two surfaces of the assembly in contact with each other;

[0009] S5. Establish an assembly model based on differentiated optimal parameters and perform finite element simulation analysis and calculation to solve the assembly deformation of the joint surface, fit the obtained deformation surface into a plane equation, and calculate the small displacement rotation of the assembly deformation error of the two surfaces;

[0010] S6. Use Jacobi-screw theory to calculate the transmission error between the two contacting surfaces of the assembly with improved assembly surface deformation, and obtain the dimensional variation range of the closed loop.

[0011] A further technical solution of the present invention is: in step S1,

[0012] S11. Use a three-dimensional coordinate measuring machine to measure the assembly surface of unassembled parts. ik (x ik ,y ik ,z ik ) represents the point coordinates, and the initial point cloud data T is obtained i ={a i1 ,a i2 ,…,a ik ,…,a in}, where i represents the assembly surface of the i-th component, k represents the k-th point in the point cloud data, and n represents the number of coordinate points in the point cloud data;

[0013] S12. Calculate the three height parameters of the surface, namely, root mean square deviation, kurtosis and skewness, and the two spatial parameters, namely, autocorrelation length and texture length and width, according to the formula.

[0014] A further technical solution of the present invention is: in step S2,

[0015] S21, using MATLAB to generate a Gaussian surface that is convenient for analysis and calculation according to the height parameters and spatial parameters of the calculated surface;

[0016] S22, importing the Gaussian surface point cloud data obtained above into UG, and establishing an assembly model including manufacturing errors.

[0017] A further technical solution of the present invention is: in step S22,

[0018] Import the point cloud data into UG, use the surface fitting function in UG reverse engineering to fit the actual surface, create the remaining surfaces as smooth surfaces, use the stitching tool to stitch the surfaces into a solid, and finally use the collision detection function to complete the contact of the two Gaussian surfaces, and finally complete the creation of the assembly model containing manufacturing errors.

[0019] A further technical solution of the present invention is: in step S3,

[0020] S31, importing the assembly model into Ansys Workbench software, defining the material properties, boundary conditions, number of steps and step length of each component, dividing the grid, setting the output and evaluating the results, completing the finite element simulation analysis, and obtaining the joint surface stress;

[0021] S32. Use a pressure-sensitive diaphragm to measure the stress / deformation of the actual assembly interface when the bolt tightening torque is 50% of the rated value;

[0022] S33. Compare the simulated and measured joint surface stresses, and correct the spatial parameters to ensure that the obtained Gaussian surface is closer to the actual assembly surface, and regenerate the assembly model of the corrected Gaussian surface according to S2.

[0023] A further technical solution of the present invention is: in step S31, the simulation analysis is as follows:

[0024] The density, Young's modulus, and Poisson's ratio of each component are set according to the actual material properties. The bulk modulus and shear modulus will be automatically calculated based on the input Young's modulus and Poisson's ratio;

[0025] Boundary conditions and loads are set according to the actual contact conditions. For the application of bolt tightening torque: the bolt is divided into three sections: upper, middle and lower. The contact between the upper section, lower section and parts is fixed contact, and the tightening torque is applied to the middle section.

[0026] Set the number of steps to 2, the duration of each step to 1s, and the initial sub-step, minimum sub-step, and maximum sub-step to 5, 5, and 25 respectively; take 50% of the rated tightening torque for load application and locking;

[0027] Tetrahedral mesh was used for meshing, and mesh refinement and hexahedral mesh were used for key parts;

[0028] In the output settings, set Deformation-Directional according to the required component joint surface to solve the directional deformation of the joint surface;

[0029] A further technical solution of the present invention is: in step S32,

[0030] S321. Cut the pressure-sensitive diaphragm to the size corresponding to the assembly surface of the first component, and at the same time reserve a part of the pressure-sensitive diaphragm that does not participate in pressure measurement, which is convenient for clamping and can also avoid affecting the pressure measurement result of the pressure-sensitive diaphragm.

[0031] S322. To avoid affecting the pressure measurement result of the joint surface due to inclined placement, place the first component horizontally on the ground. Use tweezers to pick up the part of the cut pressure-sensitive diaphragm that does not participate in pressure measurement and place it on the assembly surface of the first component, so that the pressure-sensitive diaphragm is kept in close contact and parallel with the assembly surface of the first component. Then align the assembly surface of the second component with the assembly surface of the first component and place them relatively.

[0032] S323. Fix and connect the two components with bolts. Look up the national standard according to the bolt model to obtain the bolt tightening torque, and calculate the rated tightening torque value using the formula. Then take 50% of the tightening torque value and use a digital display torque wrench to tighten the bolts.

[0033] S324. After keeping the pressure-sensitive diaphragm under pressure for one minute, first remove the bolts, then translate the first component upward, take out the pressure-sensitive diaphragm with tweezers, scan the tested pressure-sensitive diaphragm with a supporting scanner and compare the corresponding relationship between the RGB value and the pressure, and correct it according to the temperature and humidity when using the pressure-sensitive diaphragm to obtain the pressure distribution numerical map of the joint surface.

[0034] A further technical solution of the present invention is: in the step S4,

[0035] S41. Through parametric simulation in Ansys Workbench, set the bolt tightening torque as a variable parameter, repeat the steps the same as S31, and analyze the stress conditions of the two mutually contacting surfaces of the assembly under different bolt tightening torques.

[0036] S42. Analyze the uniformity of the stress distribution on the two mutually contacting surfaces of the assembly under different bolt tightening torques through the co-occurrence matrix:

[0037] Z = a·ASM - b·CON - c·ENT + d·HOM

[0038] Among them, a, b, c, and d are the coefficients or weight factors corresponding to ASM, CON, ENT, and HOM respectively, and 0 < a, b, c, d < 1, a + b + c + d = 1. The larger the obtained index Z, the more uniform the surface stress distribution. Obtain the optimal tightening torque parameter value for assembly through the analysis result to realize the optimization of the bolt tightening torque.

[0039] A further technical solution of the present invention is: in the step S5,

[0040] S51, setting the tightening torque value to the optimal parameter value obtained above, repeating step S31, and obtaining the assembly deformation of the joint surface including the manufacturing error;

[0041] S52, extract the point cloud data after the deformation of the joint surface, and obtain the deformed point cloud data as T i ″={a i1 ″,a i2 ″,…,a ik ″,…,a io ″}, where o represents the number of coordinate points in the point cloud data after calculating the assembly deformation;

[0042] S53. Fit the least squares plane equation based on the point cloud data, calculate the equation and normal vector of the fitted plane, introduce the small displacement spin theory to represent the posture of the fitted plane, and obtain the small displacement spin of the manufacturing error of the two contacting surfaces of the assembly.

[0043] A further technical solution of the present invention is: in step S6,

[0044] S61. According to the relative position relationship between the structural dimensions and the coordinate system, the Jacobian matrix between each feature surface can be calculated as:

[0045]

[0046] Among them, [X i ] 3×1 , [Y i ] 3×1 , [Z i ] 3×1 They represent the unit direction vectors of the local coordinate system axes relative to the three axes of the global coordinate system. [W i n ] represents the position change of the nth coordinate system relative to the ith coordinate system, and its expression is:

[0047]

[0048] in, Indicates the changing position relationship between the origins of the coordinate systems of various points.

[0049] Ignoring the quadratic term, the variation error spin D of a single surface feature can be expressed as:

[0050]

[0051] Among them, FE i ′=[u i ′v i ′w i ′α i ′βi ′γ i ′] T , is the small displacement rotation of the two surfaces of the assembly that are in contact with each other, including manufacturing and assembly deformation;

[0052] S62, using Jacobi-spinor theory FR = [J 1 ,J 2 ,…,J n ]·[D 1 ,D 2 ,…,D n ], the cumulative deformation error of the assembly can be obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A flowchart of a method for deformation control and error calculation of mutually contacting assembly surfaces based on Gaussian function characterization according to the present invention;

[0054] Figure 2 It is a schematic diagram of the present invention when it is not fully assembled;

[0055] Figure 3 It is a schematic diagram of the joint surface after assembly of the present invention;

[0056] Figure 4 The assembly model based on the modified Gaussian surface in step S3 of the present invention;

[0057] Figure 5 is the assembly deformation of the part 1 obtained by simulation analysis in step S5 of the present invention;

[0058] Figure 6 is the assembly deformation of the part 2 obtained by simulation analysis in step S51 of the present invention;

[0059] Figure 7 This is the assembly error plane fitting of the two surfaces in contact with each other in step S53 of the present invention, where a is the fitting plane of part 1 and b is the fitting plane of part 2. DETAILED DESCRIPTION

[0060] The following will clearly and completely describe the technical solution in the embodiment of the present invention by combining the drawings in the embodiment of the present invention and one side of the guide rail base plate bolt connection as an example. Obviously, the embodiment described with reference to the drawings is exemplary and is intended to be used to explain the present invention, and cannot be understood as a limitation to the present invention.

[0061] like Figure 1 FIG. 4 is a flowchart of a method for deformation control and error calculation of mutually contacting assembly surfaces based on Gaussian function characterization provided by the present invention; Figure 2 Shown is a schematic diagram of an embodiment of the present invention when it is not fully assembled; Figure 3This is a schematic diagram of the assembly of part 1 and part 2 according to an embodiment of the present invention, and the steps are as follows:

[0062] S1. Obtain the point cloud data of the two surfaces of the assembly that are in contact with each other, and calculate the height parameters and space parameters of the two surfaces respectively.

[0063] S11. Use Tango 564 universal three-dimensional coordinate measuring machine of Sirui Company to collect points on the assembly surface of unassembled parts, and obtain point cloud data of the two surfaces of the assembly body that contact each other, which are T 1 and T 2 ;

[0064] S12, according to the formula

[0065]

[0066] The root mean square deviation, kurtosis and skewness of the two surfaces in contact with each other can be calculated to be 0.103, 2.301, 0.127 and 0.097, 2.235, 0.113 respectively; according to the formula

[0067]

[0068] It can be calculated that the autocorrelation length and texture length and width of the two contacting surfaces are 0.112, 0.536 and 0.101, 0.478 respectively.

[0069] S2. The non-Gaussian surface obtained by fitting the point cloud data is converted into a Gaussian surface that is convenient for analysis and calculation by correcting the height parameter. The Gaussian surface is a representation of the surface manufacturing error, and an assembly model containing two contact surfaces with manufacturing errors is established;

[0070] S21, adoption Fit the point cloud into a surface by

[0071]

[0072] Find the coefficient a k,l , where β x =β y / Str,β y =Sal; Determine the input sequence η according to the surface height distribution, when S sk =0, S ku =3, the generated surface is a Gaussian surface; according to the coefficients and the modified input sequence, MATLAB is used to generate a Gaussian surface that is easy to analyze and calculate;

[0073] S22. Import the Gaussian surface point cloud data obtained above into UG, use the surface fitting function in UG reverse engineering to fit the actual surface, create the remaining surfaces as smooth surfaces, use the stitching tool to stitch the surfaces into a solid, and finally use the collision detection function to complete the contact of the two Gaussian surfaces, and finally complete the creation of the assembly model containing manufacturing errors.

[0074] S3. Perform finite element simulation analysis and calculation on the above assembly model to solve the bonding surface stress. At the same time, compare the bonding surface stress obtained by measuring the actual assembly with the pressure-sensitive diaphragm, correct the spatial parameters, and establish an assembly model based on the modified Gaussian surface, such as Figure 4 As shown;

[0075] S31, saving the assembly model as a .x_t format file and importing it into the static analysis module in Ansys Workbench; defining the material properties, boundary conditions, number of steps and step length of each component, dividing the grid, setting the output and evaluating the results, completing the finite element simulation analysis, and obtaining the joint surface stress;

[0076] The specific operations are as follows:

[0077] The density, Young's modulus, and Poisson's ratio of each component are set according to the actual material properties. The bulk modulus and shear modulus will be automatically calculated based on the input Young's modulus and Poisson's ratio. The specific parameters are shown in Table 1;

[0078] Table 1 Material properties of components

[0079]

[0080] Boundary conditions and loads are set according to the actual contact situation. In this example, the lower bottom surface 202 of the assembly is set to fixed. For the application of bolt tightening torque: all bolts are divided into three sections: upper, middle and lower, and named groups are generated respectively. The contact between the upper section, lower section and parts adopts fixed contact. A local coordinate system is established in the middle section of the bolt and the tightening torque is applied to the middle section.

[0081] Set the number of steps to 2, the duration of each step to 1s, and the initial sub-step, minimum sub-step, and maximum sub-step to 5, 5, and 25 respectively; take 50% of the rated value of the tightening torque to apply the load in step 1, and lock the load in step 2 to simulate the actual tightening process and the end of the tightening of the bolt;

[0082] The assembly model is meshed using tetrahedral meshes, the overall unit size is set to 10 mm, the meshes of the two surfaces of the assembly that are in contact with each other are refined to 3 mm, and the bolts are meshed using hexahedral meshes;

[0083] After the settings are completed, Deformation-Directional is set for the two contacting surfaces of the assembly in the solution to solve the normal deformation of the two surfaces and obtain the stress of the bonding surface.

[0084] S32. Use a pressure-sensitive diaphragm to measure the stress of the actual assembly joint surface when the bolt tightening torque is 50% of the rated value;

[0085] S321, cutting the pressure-sensitive diaphragm to a size corresponding to the surface 101, and reserving a portion of the pressure-sensitive diaphragm that does not participate in the pressure measurement, so as to facilitate clamping and avoid affecting the pressure measurement result of the pressure-sensitive diaphragm;

[0086] S322. To avoid the influence of tilted placement on the pressure measurement result of the joint surface, the part 2 is placed horizontally on the ground, and the cut pressure-sensitive diaphragm part that does not participate in the pressure measurement is clamped with tweezers and placed on the surface 201, so that the pressure-sensitive diaphragm and the first component assembly surface are kept in close contact and parallel, and then the surface 101 is aligned with the surface 201 and placed relatively;

[0087] S323, fixing the assembly with bolts, finding the national standard according to the bolt model to obtain the bolt tightening torque, and using the formula to calculate the rated tightening torque value, then taking 50% of the tightening torque value, and tightening the bolt with a digital torque wrench;

[0088] S324. After keeping the pressure-sensitive diaphragm under pressure for one minute, first remove the bolts, then translate the part 1 upward, take out the pressure-sensitive diaphragm with tweezers, scan the tested pressure-sensitive diaphragm with a matching scanner, and compare the correspondence between RGB value and pressure. Correct it according to the temperature and humidity when using the pressure-sensitive diaphragm, and obtain a numerical diagram of the pressure distribution on the bonding surface.

[0089] S33. Compare the simulated and measured bonding surface stresses, correct the spatial parameters, and regenerate the assembly model of the modified Gaussian surface according to S2, and simulate according to S3 to make the simulated bonding surface stress consistent with the experimental one, so as to ensure that the obtained Gaussian surface is closer to the actual assembly surface.

[0090] S4. Introduce the symbiosis matrix evaluation method to perform parametric simulation of joint surface deformation to optimize the bolt tightening torque, so as to obtain the optimal assembly bolt tightening torque;

[0091] S41. Perform parametric simulation through Ansys Workbench to set the bolt tightening torque as a variable parameter, as shown in the table, and repeat the steps in S31 to analyze the stress of the two contacting surfaces of the assembly under different bolt tightening torques;

[0092] S42. Analyze the uniformity of the stress distribution on the two mutually contacting surfaces of the assembly under different bolt tightening torques through the co-occurrence matrix:

[0093] Z = a·ASM - b·CON - c·ENT + d·HOM

[0094] Among them, a, b, c, and d are the corresponding coefficients or weight factors of ASM, CON, ENT, and HOM respectively, and 0 < a, b, c, d < 1, a + b + c + d = 1. The larger the obtained index Z, the more uniform the surface stress distribution. Obtain the optimal tightening torque parameter values of the assembly through the analysis results to achieve the optimization of the bolt tightening torque.

[0095] S5. Establish an assembly model based on the optimal bolt tightening torque and conduct finite element simulation analysis and calculation to solve the assembly deformation of the joint surface. After fitting the obtained deformed surface into a plane equation, calculate the small displacement screw of the assembly deformation error between the two surfaces;

[0096] S51. Set the tightening torque value to the optimal parameter value obtained above, repeat step S31, and solve the normal deformation of the two mutually contacting surfaces 101 and 201 at the solution scheme to obtain Figure 5 、 Figure 6 the deformed cloud diagram shown;

[0097] S52. Add a user-defined scheme to the solution scheme, and define the expressions LOC_DEFX, LOC_DEFY, and LOC_DEFZ to extract the deformations in three directions of the surfaces 101 and 201 and merge them to obtain the deformed point cloud data as T i ′, where o represents the number of coordinate points in the point cloud data after calculating the assembly deformation;

[0098] S53. The least-squares plane equation fitted according to the point cloud data is z = γ + αy + βx, and the plane is as Figure 7 shown. According to the least-squares method, the distance δ k from the discrete points of the point cloud to the fitted plane can be expressed as

[0099]

[0100] and the residual function according to the least-squares method is:

[0101]

[0102] Then there is a system of simultaneous equations:

[0103]

[0104] Substitute the above-obtained point cloud data, and the equation and normal vector of the fitted plane can be solved as:

[0105] z 1 =-0.0276+1.085e-07x 1 ′-5.388e-04y 1 ′, n=[-1.085e-07-5.388e-041];

[0106] z 2 =-0.0113+1.174e-06x 2 ′-4.213e-04y 2 ′, n=[-1.174e-064.213e-041].

[0107] The small displacement screw theory is introduced to represent the posture of the fitting plane, and the small displacement screw of the two surfaces of the assembly in contact with each other is obtained as follows:

[0108] D 1 =[6.014e-8-1.009e-43.818e-9-5.045e-5-3.007e-87.585e-13];

[0109] D 2 =[9.946e-89.702e-53.53e-94.851e-5 -4.973e-8-1.206e-12].

[0110] S6. Use Jacobi-screw theory to calculate the transmission error between the two contacting surfaces of the assembly and obtain the error variation range of the closed loop.

[0111] S61. According to the relative position relationship between the structural dimensions and the coordinate system, the Jacobian matrices of the surface 201 relative to the lower surface 202 and the surface 101 relative to the surface 201 can be calculated as follows:

[0112]

[0113] S62, using Jacobi-spinor theory, the closed loop error can be obtained

[0114] FR=[J 1 / 0 J 2 / 1 ][D 1 D 2 ] T

[0115] =[-1.3e-031.807e-043.5e-034.103e-051.525e-058.527e-10] T

[0116] The bolt tightening torque can be adjusted differently before assembly to predict the size of the closed loop error. This method is also applicable to the case of multiple components in an assembly.

Claims

1. A deformation control and error calculation method for mutually contacting assembly surfaces based on Gaussian function characterization, characterized in that: The specific steps are as follows: S1, obtaining point cloud data of two surfaces of the assembly that are in contact with each other, and calculating the height parameters and space parameters of the two surfaces respectively; S2. The non-Gaussian surface obtained by fitting the point cloud data is converted into a Gaussian surface that is convenient for analysis and calculation by correcting the height parameter, and an assembly model containing two contact surfaces with manufacturing errors is established; S3, performing finite element simulation analysis and calculation on the above assembly model to solve the bonding surface stress, and at the same time comparing the bonding surface stress obtained by measuring the actual assembly with the pressure-sensitive diaphragm, correcting the spatial parameters, and establishing an assembly model based on the modified Gaussian surface; S4, performing a parametric simulation of the deformation of the joint surface to optimize the contact deformation of the two surfaces of the assembly in contact with each other; S5. Establish an assembly model based on differentiated optimal parameters and perform finite element simulation analysis and calculation to solve the assembly deformation of the joint surface, fit the obtained deformation surface into a plane equation, and calculate the small displacement rotation of the assembly deformation error of the two surfaces; S6. Use Jacobi-screw theory to calculate the transmission error between the two contacting surfaces of the assembly with improved assembly surface deformation, and obtain the dimensional variation range of the closed loop.

2. The method for deformation control and error calculation of mutually contacting assembly surfaces based on Gaussian function characterization according to claim 1, characterized in that: In the step S1, S11. Use a three-dimensional coordinate measuring machine to measure the assembly surface of unassembled parts. ik (x ik ,y ik ,z ik ) represents the point coordinates, and the initial point cloud data T is obtained i ={a i1 ,a i2 ,…,a ik ,…,a in }, where i represents the assembly surface of the i-th component, k represents the k-th point in the point cloud data, and n represents the number of coordinate points in the point cloud data; S12. Calculate the three height parameters of the surface, namely, root mean square deviation, kurtosis and skewness, and the two spatial parameters, namely, autocorrelation length and texture length and width, according to the formula.

3. The method for deformation control and error calculation of mutually contacting assembly surfaces based on Gaussian function characterization according to claim 1, characterized in that: In the step S2, it specifically includes: S21, using MATLAB to generate a Gaussian rough surface that is easy to analyze and calculate based on the height parameters and spatial parameters of the calculated surface; S22, importing the Gaussian rough surface point cloud data obtained above into UG, and establishing an assembly model including manufacturing errors.

4. According to claim 1, a method for controlling and calculating assembly deformation errors based on error transfer between assembly surfaces of bolted parts, characterized in that: In the step S3, it specifically includes: S31, importing the assembly model into the simulation software, defining the material properties, boundary conditions, number of steps and step length of each component, dividing the grid, setting the output and evaluating the results, completing the finite element simulation analysis, and obtaining the joint surface stress; S32. In order not to affect the subsequent assembly accuracy, the pressure-sensitive diaphragm is used to measure the stress of the actual assembly joint surface when the bolt tightening torque is 50% of the rated value; S33. Compare the simulated and measured joint surface stresses, correct the height parameters and space parameters to ensure that the obtained Gaussian surface is closer to the actual assembly surface, and regenerate the assembly model of the corrected Gaussian surface according to S2.

5. According to claim 1, a method for controlling and calculating assembly deformation errors based on error transfer between assembly surfaces of bolted parts, characterized in that: In the step S32, it specifically includes: S321, cutting the pressure-sensitive diaphragm to a size corresponding to the assembly surface of the first component, and reserving a portion of the pressure-sensitive diaphragm that does not participate in pressure measurement, so as to facilitate clamping and avoid affecting the pressure measurement result of the pressure-sensitive diaphragm; S322. To avoid the influence of tilted placement on the pressure measurement result of the joint surface, the first component is placed horizontally on the ground, and the cut pressure-sensitive diaphragm part that does not participate in the pressure measurement is clamped with tweezers and placed on the assembly surface of the first component, so that the pressure-sensitive diaphragm and the assembly surface of the first component are kept in close contact and parallel, and then the assembly surface of the second component is aligned with the assembly surface of the first component and placed relatively; S323. Fix and connect the two components with bolts. Look up the national standard according to the bolt model to obtain the bolt tightening torque, calculate the rated tightening torque value using the formula, then take 50% of the tightening torque value, and use a digital display torque wrench to tighten the bolts. S324. After keeping the pressure-sensitive diaphragm under pressure for one minute, first remove the bolts, then translate the first component upward, take out the pressure-sensitive diaphragm with tweezers, scan the tested pressure-sensitive diaphragm with a supporting scanner and compare the corresponding relationship between the RGB value and the pressure, and correct it according to the temperature and humidity when using the pressure-sensitive diaphragm to obtain the numerical diagram of the joint surface pressure distribution.

6. The method for deformation control and error calculation of mutually contacting assembly surfaces based on Gaussian function characterization according to claim 1, characterized in that: In the step S4, it specifically includes: S41. Through parametric simulation in Ansys Workbench, set the bolt tightening torque as a variable parameter, repeat the steps in S31, and analyze the stress / deformation conditions of the two mutually contacting surfaces of the assembly under different bolt tightening torques. S42. Analyze the uniformity of the stress / deformation distribution of the two mutually contacting surfaces of the assembly under different bolt tightening torques through the co-occurrence matrix: Z = a·ASM - b·CON - c·ENT + d·HOM Among them, a, b, c, and d are the coefficients or weight factors corresponding to ASM, CON, ENT, and HOM respectively, and 0 < a, b, c, d < 1, a + b + c + d = 1. The larger the obtained index Z, the more uniform the surface stress / deformation distribution. Obtain the optimal tightening torque parameter value of the assembly through the analysis results to optimize the bolt tightening torque.

7. The method for deformation control and error calculation of mutually contacting assembly surfaces based on Gaussian function characterization according to claim 1, characterized in that: In the step S5, it specifically includes: S51. Set the tightening torque value as the optimal parameter value obtained above, repeat the step S31, and obtain the assembly deformation of the joint surface including manufacturing errors. S52, extract the point cloud data after the deformation of the joint surface, and obtain the deformed point cloud data as T i ″={a″ i1 ,a″ i2 ,…,a″ ik ,…,a″ io }, where o represents the number of coordinate points in the point cloud data after calculating the assembly deformation; S53. Fit the least squares plane equation according to the point cloud data, calculate the equation and normal vector of the fitted plane, introduce the small displacement screw theory to represent the pose of the fitted plane, and obtain the small displacement screw of the manufacturing errors of the two mutually contacting surfaces of the assembly.

8. The method for deformation control and error calculation of mutually contacting assembly surfaces based on Gaussian function characterization according to claim 1, characterized in that: In the step S6, it specifically includes: S61. Calculate the Jacobian matrix between each feature surface according to the relative position relationship between the structural dimensions and the coordinate system. S62. Use the Jacobian-screw theory to calculate the cumulative deformation transfer error of the two mutually contacting surfaces of the assembly with the improved assembly deformation.

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