Calculation method and electronic equipment for profile error of rotating parts

Abstract

The present invention provides a method and electronic device for calculating the profile error of a rotating part. The method comprises: performing coordinate transformation processing on each measuring point on the rotating surface of the rotating part to obtain the first coordinate of each measuring point; establishing an ideal rotating surface model and dividing the ideal rotating surface model into regions to obtain a standard region and an approximation region; when the measuring point is in the standard region, calculating the minimum distance from the measuring point to the ideal rotating surface within the standard region based on the geometric properties of the ideal rotating surface within the standard region; when the measuring point is in the approximation region, calculating the first distance from the measuring point to each subdivided surface based on the first coordinate of the measuring point, and determining the minimum value of the first distances as the minimum distance from the measuring point to the ideal rotating surface within the approximation region; and determining the profile error of the rotating surface of the rotating part based on the minimum distance. The present invention can accurately calculate the profile error of the rotating surface of a composite rotating surface in a rotating part.

Description

Technical Field

[0001] The present invention relates to the technical field of profile error evaluation, and in particular to a method for calculating the profile error of a rotating part and an electronic device. Background Art

[0002] A surface of revolution is a curved surface formed in space when a plane curve (single curvature, where the plane of the curve is not perpendicular to the axis of rotation) or a spatial curve (double curvature) rotates around a fixed straight line (axis). Surfaces of revolution are widely used in mechanical processing and manufacturing, such as bearings, hemispherical resonators, and continuously variable transmissions. The surfaces of revolution in rotating parts often affect the parts' rotational errors, such as axial play, radial runout, and angular motion. The surface machining accuracy directly determines the mechanical performance and service life of the parts. Therefore, strict requirements are placed on the inspection of the geometric dimensions of these rotating parts, making the assessment of the profile errors of these rotating parts extremely important.

[0003] Common surface topography for rotating parts includes spheres, cylinders, cones, tori, and their composites. These surfaces are all surfaces of revolution, and the assessment of their profile error is considered surface profile error assessment. Surface profile error refers to the variation between the actual measured surface shape and the ideal profile.

[0004] Existing methods for evaluating the profile error of rotating surfaces all calculate the shortest distance from the measuring point to the ideal surface based on the geometric properties of a single rotating surface. However, for a composite rotating surface formed by fitting two or more rotating surfaces such as a sphere, cylinder, cone, or torus, when the distances from a measuring point to two adjacent rotating surfaces are close, it is impossible to accurately determine which geometric property of the rotating surface should be used to calculate the distance from the measuring point to the rotating surface. As a result, it is impossible to accurately calculate the surface profile error of the composite rotating surface, resulting in low accuracy of the surface profile error, which in turn leads to high error rates and production costs for industrial parts. Summary of the Invention

[0005] Embodiments of the present invention provide a method for calculating the profile error of a rotating part, an electronic device, and a storage medium to solve the problem that the profile error of a composite rotating surface cannot be accurately calculated.

[0006] In a first aspect, an embodiment of the present invention provides a method for calculating a profile error of a rotating part, comprising:

[0007] Performing coordinate transformation processing on each measuring point on a rotational surface of a rotational part to obtain a first coordinate of each measuring point; the rotational part includes at least two rotational surfaces;

[0008] An ideal surface of revolution model is established according to the design dimensions of the ideal surface of revolution of the rotating part, and the ideal surface of revolution model is divided into regions to obtain a standard region and an approximate region; wherein the standard region contains a single ideal surface of revolution, and the approximate region contains at least two ideal surfaces of revolution;

[0009] For each measuring point, when the measuring point is in a certain standard area, the minimum distance from the measuring point to the ideal rotation surface in the standard area is calculated according to the geometric properties of the ideal rotation surface in the standard area;

[0010] When the measuring point is within an approximation region, first distances from the measuring point to each subdivision surface are calculated based on the first coordinate of the measuring point, and a minimum value among the first distances is determined as the minimum distance from the measuring point to the ideal surface of revolution within the approximation region; wherein each subdivision surface is obtained by dividing the ideal surface of revolution within the approximation region;

[0011] Based on the minimum distance, a profile error of the rotational surface of the rotational part is determined.

[0012] In a possible implementation, dividing the ideal surface of revolution model into regions includes:

[0013] Taking the connection point of each two ideal rotation surfaces as the midpoint, extending the preset offset amount to both ends of the ideal rotation surfaces to obtain an approximate area containing the two ideal rotation surfaces;

[0014] The other areas in the ideal rotation surface model except the approximation area are determined as standard areas.

[0015] In a possible implementation, after dividing the ideal surface of revolution model into regions, the method further includes:

[0016] Calculate the approximation parameters based on the error between the measurement point and each ideal rotation surface and the preset offset;

[0017] When the approximation parameter is greater than or equal to zero, determining that the measurement point is in a standard area;

[0018] When the approximation parameter is less than zero, it is determined that the measurement point is in the approximation area.

[0019] In one possible implementation, calculating the approximation parameter based on the error from the measurement point to each ideal rotation surface and the preset offset includes:

[0020] According to A=|Δ j+1 -Δ j |-2P, calculate the approximation parameters;

[0021] Among them, A represents the approximation parameter, Δ j+1Indicates the error from the measurement point to the j+1th ideal rotation surface, Δ j It represents the error from the measuring point to the jth ideal rotation surface, and P represents the preset offset.

[0022] In a possible implementation, respectively calculating the first distance from the measurement point to each subdivision surface includes:

[0023] Get the coordinates of the center point of each subdivision surface;

[0024] According to the first coordinate of the measuring point and the coordinates of each center point, the distance from the measuring point to the center point of each subdivision surface is calculated respectively, and the distance is determined as the first distance.

[0025] In a possible implementation, determining the profile error of the rotational surface of the rotational part based on the minimum distance includes:

[0026] Constructing a mathematical model of the rotary surface profile error based on the minimum distance;

[0027] The mathematical model of the rotation surface profile error is optimized and solved to obtain the rotation surface profile error of the rotational part.

[0028] In a possible implementation, optimizing and solving the mathematical model of the rotary surface profile error includes:

[0029] The minimum distance corresponding to each measurement point is used as a different population individual, and the entire population is initialized to obtain the original population;

[0030] Perform mutation processing on each individual in the original population to obtain a mutant population;

[0031] Crossing the variant population with the original population to obtain a crossover population;

[0032] Calculate the fitness of each population individual in the cross population and the fitness of the corresponding population individual in the original population respectively, and determine the population individual with better fitness as the population individual in the next generation population;

[0033] According to the boundary conditions, the population individuals of the next generation population are checked and processed to obtain the final population individuals of the next generation population;

[0034] The final next generation population is determined as the original population, and the process jumps to the step of "mutating each individual in the original population to obtain a mutant population" to obtain a new mutant population, and subsequent steps are executed until the iterative generation reaches the set value, completing the iterative optimization and obtaining the final rotation surface contour error.

[0035] In a possible implementation, performing mutation processing on each individual in the original population includes:

[0036] according to Perform mutation processing on each individual in the original population;

[0037] Or, according to Perform mutation processing on each individual in the original population;

[0038] Among them, v i represents the i-th individual in the mutant population, w r1 、w r2 and w r3 Represent any three individuals in the original population, and r1≠r2≠r3≠i, F represents the coefficient of variation, λ represents the adaptive operator, G m Indicates the maximum number of iterations, G indicates the current number of iterations, F0 indicates a random number in the range [0,2], V i V represents the individual update speed of the i-th individual in the mutant population; i-1 represents the individual update speed of the i-1th population individual in the mutant population, c1 and c2 represent the first learning factor and the second learning factor respectively, q1 and q2 represent random numbers in the range [0,1] respectively, and x best Indicates the optimal individual extreme value of the i-th population individual in all current populations, y best Represents the global optimal extreme value among all current populations, w i-1 Represents the i-1th population individual in the original population.

[0039] In a possible implementation, performing cross processing on the variant population and the original population includes:

[0040] according to Perform cross processing on the individuals in the mutant population and the corresponding individuals in the original population;

[0041] Among them, u i,j represents the sub-individual of the jth dimension in the i-th population individual in the cross population, v i,j represents the sub-individual of the jth dimension in the i-th population individual in the mutant population, w i,j represents the j-th dimension sub-individual in the i-th population individual in the original population, rand is a random number in the interval [0, 1], randi represents any randomly selected dimension number, randi∈{1, 2, ..., D}, D represents the population dimension, CR represents the crossover operator, CR0 represents a real number in the range [0, 1], and λ represents an adaptive operator.

[0042] In a second aspect, an embodiment of the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method described in the first aspect or any possible implementation of the first aspect are implemented.

[0043] An embodiment of the present invention provides a method and electronic device for calculating the profile error of a rotating part. The method comprises performing coordinate transformation processing on each measuring point on a rotating surface of the rotating part to obtain a first coordinate of each measuring point. An ideal rotating surface model is established based on the design dimensions of the ideal rotating surface of the rotating part, and the ideal rotating surface model is divided into regions to obtain a standard region and an approximation region. For each measuring point, when the measuring point is in a certain standard region, the minimum distance from the measuring point to the ideal rotating surface within the standard region is calculated based on the geometric properties of the ideal rotating surface within the standard region. When the measuring point is in a certain approximation region, the first distance from the measuring point to each subdivided surface is calculated based on the first coordinate of the measuring point, and the minimum value of the first distances is determined as the minimum distance from the measuring point to the ideal rotating surface within the approximation region. Based on the minimum distance, the profile error of the rotating surface of the rotating part is determined, and the profile error of the rotating surface of the composite rotating surface in the rotating part can be accurately calculated. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 1 is a flowchart of a method for calculating the profile error of a rotating part provided by an embodiment of the present invention;

[0046] Figure 2 is a transformation diagram of the coordinate transformation process provided by an embodiment of the present invention;

[0047] Figure 3 Schematic diagram of the division of regions using the ideal rotation surface mathematical model provided by an embodiment of the present invention;

[0048] Figure 4 This is a flowchart for calculating the minimum distance from a measurement point to an ideal rotation surface provided by an embodiment of the present invention;

[0049] Figure 5 is a schematic diagram of dividing the ideal rotation surface in the approximation area provided by an embodiment of the present invention;

[0050] Figure 6 This is a flow chart for optimizing and solving a mathematical model for a profile error of a rotary surface provided by an embodiment of the present invention;

[0051] Figure 7 1 is a schematic structural diagram of a device for calculating a profile error of a rotating part provided by an embodiment of the present invention;

[0052] Figure 8 is a schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In the following description, specific details such as particular system structures and techniques are provided for purposes of illustration, not limitation, to facilitate a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0054] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below with reference to the accompanying drawings.

[0055] Figure 1 The implementation flow chart of the method for calculating the profile error of a rotating part provided by the embodiment of the present invention is detailed as follows:

[0056] Step 101 : performing coordinate transformation processing on each measuring point on a rotational surface of a rotational part to obtain a first coordinate of each measuring point; the rotational part includes at least two rotational surfaces.

[0057] When coordinate transformation is performed on the measurement point, the Q i '=T'·Q i Perform coordinate transformation on each measuring point to obtain the first coordinate of each measuring point.

[0058] Among them, Q i =[x i ,y i ,z i ] T , Q i represents the initial coordinate matrix corresponding to the i-th measurement point before coordinate transformation, x i Indicates the initial horizontal coordinate of the i-th measurement point before coordinate transformation, y i Indicates the vertical coordinate of the i-th measurement point before coordinate transformation, z i represents the vertical coordinate of the i-th measurement point before coordinate transformation, T represents the transposition operator; Q i '=[x i ',yi ',z i '] T , Q i ' represents the first coordinate matrix corresponding to the i-th measurement point after coordinate transformation, x i ' represents the first horizontal coordinate of the i-th measurement point after coordinate transformation, y i ' represents the first ordinate of the i-th measurement point after coordinate transformation, z i ' represents the first vertical coordinate of the i-th measurement point after coordinate transformation, and T' represents the coordinate transformation matrix.

[0059] Preferably, in order to improve the efficiency of coordinate transformation, the coordinates of all measurement points can be formed into an initial coordinate matrix, and the initial coordinate matrix can be subjected to coordinate transformation processing according to Q'=T'·Q to obtain the first coordinate matrix corresponding to all measurement points, and the first coordinate matrix corresponding to all measurement points contains the first coordinates of all measurement points.

[0060] in, Q represents the initial coordinate matrix of all measurement points before coordinate transformation, x1, y1 and z1 represent the initial horizontal coordinate, initial vertical coordinate and initial vertical coordinate of the first measurement point before coordinate transformation, respectively. i 、y i and z i They represent the initial horizontal coordinate, initial vertical coordinate and initial vertical coordinate of the i-th measurement point before coordinate transformation, respectively. n 、y n and z n They represent the initial horizontal coordinate, initial vertical coordinate and initial vertical coordinate of the nth measurement point before coordinate transformation respectively; Q' represents the first coordinate matrix corresponding to all measurement points after coordinate transformation, x1', y1' and z1' respectively represent the first horizontal coordinate, first vertical coordinate and first vertical coordinate of the first measurement point after coordinate transformation, x i '、y i ' and z i 'represents the first horizontal coordinate, first vertical coordinate and first vertical coordinate of the i-th measurement point after coordinate transformation, x n '、y n ' and z n ' respectively represent the first horizontal coordinate, first vertical coordinate and first ordinate of the nth measurement point after coordinate transformation.

[0061] The above coordinate transformation matrix can be expressed as:

[0062]

[0063] Where x, y, and z represent the translation distances of the measurement point along the X-axis, Y-axis, and Z-axis, respectively; α, β, and γ represent the rotation angles of the measurement point around the X-axis, Y-axis, and Z-axis, respectively.

[0064] The coordinate transformation matrix T' translates and rotates the measurement point through six parameters x, y, z, α, β and γ to achieve coordinate transformation.

[0065] When solving the profile error of the rotating surface according to the minimum area criterion, the inner deviation surface and outer deviation surface of the ideal rotating surface are established according to the ideal rotating surface offset parameter l. By translating and rotating the measuring points, the distance between the inner and outer deviation surfaces of the ideal rotating surface that can accommodate all measuring points is minimized. The minimum distance is further solved to obtain the profile error of the measured rotating surface.

[0066] For example, see Figure 2 All measurement points form actual contour surface 1. Actual inner contour surface 2 and actual outer contour surface 3 are generated based on actual contour surface 1. Based on the ideal rotational surface design dimensions and the ideal rotational surface offset parameter l, ideal inner contour surface 4 and ideal outer contour surface 5 are generated. Coordinate transformation is performed on all measurement points so that ideal inner contour surface 4 and ideal inner contour surface 5 can encompass all measurement points.

[0067] Step 102: Based on the ideal surface of revolution design dimensions of the part, an ideal surface of revolution model is established, and the ideal surface of revolution model is divided into regions to obtain a standard region and an approximation region. The standard region contains a single ideal surface of revolution, and the approximation region contains at least two ideal surfaces of revolution.

[0068] In this embodiment of the present invention, when establishing an ideal surface of revolution model based on the ideal surface of revolution design dimensions of a rotating part, an ideal surface of revolution offset parameter l (which can be simply understood as the allowable error of the ideal surface of revolution) is introduced to obtain the ideal surface of revolution model. In other words, the ideal surface of revolution model here is not a fixed model, but rather a dynamic model that can change within the allowable range of the ideal surface of revolution offset parameter l.

[0069] The rotational body part includes at least two rotational surfaces, and accordingly, its corresponding ideal rotational surface model also includes at least two ideal rotational surfaces. For example, see Figure 3 The ideal surface of revolution model includes, from the inside out, a cylinder, a torus, and a sphere. When partitioning the rational surface of revolution model, the area near the junction of two ideal surfaces of revolution (e.g., between a cylinder and a torus) can be divided into an approximation region, and the remaining area can be divided into a standard region. The approximation region contains at least two ideal surfaces of revolution, while the standard region contains only one ideal surface of revolution.

[0070] Optionally, the ideal surface of revolution model is divided into regions, including:

[0071] Taking the connection point of each two ideal rotation surfaces as the midpoint, extending the preset offset amount to both ends of the ideal rotation surfaces to obtain an approximate area containing the two ideal rotation surfaces;

[0072] The other areas in the ideal rotation surface model except the approximation area are determined as standard areas.

[0073] It should be noted that the preset offset can be set by the user based on their own needs and is not specifically limited in the embodiments of the present invention. When the user has high requirements for the precision of the rotating part, the preset offset can be set slightly larger, for example, 10mm; when the user has low requirements for the precision of the rotating part, the preset offset can be set slightly smaller, for example, 5mm.

[0074] For example, see Figure 3 Using the junction of the cylindrical surface and the torus as the midpoint, the edges are extended upward along the cylindrical surface by a preset offset, and downward along the torus by a preset offset to obtain an approximation region. Using the junction of the torus and the sphere as the midpoint, the edges are extended upward along the torus by a preset offset, and downward along the sphere by a preset offset to obtain an approximation region. These two approximation regions for the ideal surface of revolution model are obtained. The remaining cylindrical, torus, and spherical regions are all standard regions.

[0075] Optionally, after the ideal surface of revolution model is divided into regions, the following steps are further included:

[0076] Calculate the approximation parameters based on the error between the measurement point and each ideal rotation surface and the preset offset;

[0077] When the approximation parameter is greater than or equal to zero, it is determined that the measurement point is in the standard area;

[0078] When the approximation parameter is less than zero, it is determined that the measurement point is in the approximation region.

[0079] Optionally, approximation parameters are calculated based on the error between the measurement point and each ideal rotation surface and the preset offset, including:

[0080] According to A=|Δ j+1 -Δ j |-2P, calculate the approximation parameters;

[0081] Among them, A represents the approximation parameter, Δ j+1 Indicates the error from the measurement point to the j+1th ideal rotation surface, Δ j It represents the error from the measuring point to the jth ideal rotation surface, and P represents the preset offset.

[0082] When calculating the error between the measuring point and the ideal surface of revolution, the basic error formula can be determined based on the geometric properties of the ideal surface of revolution.

[0083] For example, when the ideal rotation surface is a sphere, assuming that the first coordinate of the measurement point is (x r ',y r ', z r '), the coordinates of the sphere center are (a1, b1, c1), and the radius of the sphere is R1. Calculate the error from the measured point to the sphere.

[0084] When the ideal rotation surface is a cylindrical surface, assuming that the first coordinate of the measurement point is (x r ',y r ', z r '), the intersection coordinates of the cylindrical axis and the X'OY' plane are (a2, b2, 0), and the radius of the cylindrical surface is R2, which can be calculated based on Calculate the error from the measuring point to the cylindrical surface. α2 represents the angle of rotation of the axis around the X' axis, and β2 represents the angle of rotation of the axis around the Y' axis.

[0085] When the ideal rotation surface is a conical surface, assuming that the first coordinate of the measuring point is (x r ',y r ', z r '), the intersection coordinates of the cone axis and the X'OY' plane are (a3, b3, 0), the large cross-section radius of the cone is R3, and the cone angle is 2λ3.

[0086] Calculate the error from the measuring point to the conical surface. α3 represents the angle of rotation of the axis around the X' axis, and β3 represents the angle of rotation of the axis around the Y' axis.

[0087] When the ideal rotation surface is a torus, assuming that the first coordinate of the measurement point is (x r ',y r ', z r '), the center coordinates of the annular axis are (a4, b4, c4), the arc center offset is R4, and the annular arc radius is r.

[0088] Calculate the error from the measurement point to the annular surface. α4 represents the angle of rotation of the axis around the X' axis, and β4 represents the angle of rotation of the axis around the Y' axis.

[0089] Step 103 : for each measurement point, when the measurement point is in a certain standard area, the minimum distance from the measurement point to the ideal rotation surface in the standard area is calculated according to the geometric properties of the ideal rotation surface in the standard area.

[0090] See Figure 4 When the measuring point is in a certain standard area, since there is only one ideal rotation surface in the standard area, the minimum distance from the measuring point to the ideal rotation surface can be calculated according to the geometric properties of the ideal rotation surface.

[0091] Referring to the above basic formula for the error between the measuring point and different ideal rotation surfaces, the error between the measuring point and different ideal rotation surfaces can be calculated according to the above basic formula, and the error is determined as the minimum distance d between the measuring point and the ideal rotation surface, that is, d=Δ.

[0092] When the measuring point is in a certain approximation area, the first distances from the measuring point to each subdivision surface are calculated respectively according to the first coordinate of the measuring point, and the minimum value of the first distances is determined as the minimum distance from the measuring point to the ideal rotation surface in the approximation area; wherein each subdivision surface is obtained by dividing the ideal rotation surface in the approximation area.

[0093] The approximation region contains at least two ideal surfaces of revolution, making it impossible to accurately determine which ideal surface of revolution's geometric properties should be used to calculate the distance from the measurement point to that ideal surface of revolution. Therefore, the minimum distance from the measurement point to the ideal surface of revolution within the approximation region cannot be calculated using the above basic error formula.

[0094] Optionally, calculating the first distance from the measurement point to each subdivision surface separately includes:

[0095] Get the coordinates of the center point of each subdivision surface;

[0096] According to the first coordinate of the measuring point and the coordinates of each center point, the distance from the measuring point to the center point of each subdivision surface is calculated respectively, and the distance is determined as the first distance.

[0097] When the measurement point is within an approximation region that contains two ideal surfaces of revolution, these two ideal surfaces of revolution need to be divided into a number of subdivisions, for example, 200. The coordinates of the center points of each of the 200 subdivisions are obtained, and the distances from the measurement point to each of these 200 center points are calculated. Because the area of ​​the subdivisions is sufficiently small, the distance from the measurement point to the center point of each subdivision can be directly determined as the first distance from the measurement point to each subdivision. Finally, the minimum value of all calculated first distances is determined as the minimum distance from the measurement point to the ideal surface of revolution within the approximation region.

[0098] For example, see Figure 5 When the measurement point is located in the approximate area between the sphere and the torus, the ideal rotation surface in the approximate area needs to be divided into multiple subdivision surfaces. Since the subdivision surface is small enough, Figure 5Only the center points of each subdivision surface are shown in the figure. The first distances from the measurement point Pi to each center point are calculated respectively, and the minimum value of all the first distances is determined as the minimum distance.

[0099] Step 104 : determining the profile error of the rotational surface of the rotational part based on the minimum distance.

[0100] Optionally, based on the minimum distance, the profile error of the rotational surface of the rotational part is determined, including:

[0101] According to the minimum distance, a mathematical model of the rotary surface profile error is constructed.

[0102] Optionally, the i (x,y,z,α,β,γ,l)}) to construct a mathematical model of the rotary surface profile error.

[0103] Among them, f represents the profile error of the rotating surface of the rotating part, d i represents the minimum distance from the i-th measurement point to the ideal rotation surface. x, y, and z represent the distances of translation of the measurement point along the X-axis, Y-axis, and Z-axis, respectively, when the coordinate transformation is performed. α, β, and γ represent the angles of rotation of the measurement point around the X-axis, Y-axis, and Z-axis, respectively, when the coordinate transformation is performed. l represents the offset parameter of the ideal rotation surface. x, y, z, α, β, γ, and l all affect d i The final value of .

[0104] The mathematical model of the rotational surface profile error is further optimized and solved to obtain the rotational surface profile error of the rotating part.

[0105] To obtain the optimal rotary surface profile error, it is necessary to optimize the parameter variables x, y, z, α, β, γ, and l in the mathematical model of the rotary surface profile error. When optimizing and solving the mathematical model of the rotary surface profile error, a differential evolution algorithm can be used for optimization and solution.

[0106] Optional, see Figure 6 , optimize and solve the mathematical model of the rotary surface profile error, including:

[0107] Step 141 : Using the minimum distances corresponding to the measurement points as different population individuals, the entire population is initialized to obtain an original population.

[0108] The individuals in the population can be represented as w i =(d i,1 ,d i,2 ,…,d i,D), where i = 1, 2, ..., n, where n represents the population size, i.e., the number of measurement points, and D represents the population dimension. Since the mathematical model of the profile error of the rotating surface includes x, y, z, α, β, γ, and l, a total of 7 parameter variables, the population dimension D = 7. i,1 ,d i,2 ,…,d i,D These correspond to the minimum distances under different parameter variables of x, y, z, α, β, γ, and l.

[0109] The constraints of the parameter variables are set according to the preset error range, and the initial population is randomly generated within the given constraints.

[0110] Step 142: Perform mutation processing on each individual in the original population to obtain a mutant population.

[0111] Optionally, mutation processing is performed on each individual in the original population, including:

[0112] according to Perform mutation processing on each individual in the original population.

[0113] Among them, v i represents the i-th individual in the mutant population, w r1 、w r2 and w r3 Represent any three individuals in the original population, and r1≠r2≠r3≠i, F represents the coefficient of variation, λ represents the adaptive operator, G m Indicates the maximum number of iterations, G indicates the current number of iterations, and F0 indicates a random number in the range [0,2].

[0114] By introducing an adaptive operator to improve the coefficient of variation, the premature phenomenon of the differential evolution algorithm can be avoided and the convergence speed of the algorithm can be improved.

[0115] Or, according to Perform mutation processing on each individual in the original population.

[0116] Among them, v i represents the i-th individual in the mutant population, w r1 、w r2 and w r3 Represent any three individuals in the original population, and r1≠r2≠r3≠i, F represents the coefficient of variation, λ represents the adaptive operator, G m Indicates the maximum number of iterations, G indicates the current number of iterations, F0 indicates a random number in the range [0,2], V i V represents the individual update speed of the i-th individual in the mutant population; i-1represents the individual update speed of the i-1th population individual in the mutant population, c1 and c2 represent the first learning factor and the second learning factor respectively, q1 and q2 represent random numbers in the range [0,1] respectively, and x best Indicates the optimal individual extreme value of the i-th population individual in all current populations, y best Represents the global optimal extreme value among all current populations, w i-1 Represents the i-1th population individual in the original population.

[0117] By further improving the coefficient of variation by utilizing the individual update speed in the particle swarm optimization algorithm, the evolution process of the differential evolution algorithm can be further optimized, and the convergence speed of the algorithm population individuals and the contour error fitting accuracy can be improved.

[0118] Step 143: Cross the mutant population with the original population to obtain a crossover population.

[0119] Unlike genetic algorithms, the crossover in differential evolution operates on a certain dimension of the entire population, ensuring that at least one dimension of the sub-individual in the new individual comes from the mutant population. In essence, at least one parameter variable in the new individual comes from the mutant population.

[0120] Optionally, performing a crossover process on the variant population and the original population includes:

[0121] according to Perform cross processing on the individuals in the mutant population and the corresponding individuals in the original population;

[0122] Among them, u i,j represents the sub-individual of the jth dimension in the i-th population individual in the cross population, v i,j represents the sub-individual of the jth dimension in the i-th population individual in the mutant population, w i,j represents the j-th dimension sub-individual in the i-th population individual in the original population, rand is a random number in the interval [0, 1], randi represents any randomly selected dimension number, randi∈{1, 2, ..., D}, D represents the population dimension, CR represents the crossover operator, CR0 represents a real number in the range [0, 1], and λ represents an adaptive operator.

[0123] For high-precision rotary surface error evaluation, among the seven parameter variables in the mathematical model of rotary surface profile error, the ideal rotary surface bias parameter l has a higher precision requirement on the composite rotary surface profile fitting accuracy. Therefore, according to Improvement of the crossover operator can effectively improve the fitting accuracy of the composite rotational surface profile

[0124] Step 144 , respectively calculating the fitness of each population individual in the cross population and the fitness of the corresponding population individual in the original population, and determining the population individual with better fitness as the population individual in the next generation population.

[0125] Specifically, according to The population individuals with better fitness are determined as the population individuals in the next generation population.

[0126] Among them, w i ' represents the i-th individual in the next generation population, fit(u i ) represents the fitness of the i-th individual in the cross population, fit(w i ) represents the fitness of the i-th individual in the original population, and the fitness function represents the maximum value of the minimum distance from all measurement points to the ideal surface.

[0127] Step 145 , performing boundary checking and processing on the population individuals of the next generation population according to the boundary conditions, to obtain the final population individuals of the next generation population.

[0128] In the process of performing crossover and mutation operations on individuals in the population, the range of individuals in the population may exceed the given range. It is necessary to check and process the boundary conditions of the population obtained after the above operations. Assume that the constraint boundary of the parameter variable is [w min ,w max ], w' is the population individual in the next generation population obtained after mutation or crossover processing, w" is the population individual in the next generation population after boundary checking and processing. The boundary checking and processing rules for the population individuals in the next generation population are:

[0129]

[0130] The final next generation population is determined as the original population, and the process jumps to the step of "mutating each individual in the original population to obtain a mutant population" to obtain a new mutant population. Subsequent steps are performed until the iterative generation reaches the set value, completing the iterative optimization and obtaining the final rotational surface contour error.

[0131] The embodiment of the present invention performs coordinate transformation processing on all measurement points on the rotational surface of a rotational part to obtain the first coordinates of all measurement points; establishes an ideal rotational surface model based on the design dimensions of the ideal rotational surface of the rotational part, and divides the ideal rotational surface model into regions to obtain a standard region and an approximation region; for each measurement point, when the measurement point is in a certain standard region, calculates the minimum distance from the measurement point to the ideal rotational surface within the standard region based on the geometric properties of the ideal rotational surface within the standard region; when the measurement point is in a certain approximation region, calculates the first distance from the measurement point to each subdivided surface based on the first coordinate of the measurement point, and determines the minimum value of the first distances as the minimum distance from the measurement point to the ideal rotational surface within the approximation region; based on the minimum distance, determines the rotational surface profile error of the rotational part, and can accurately calculate the rotational surface profile error of the composite rotational surface in the rotational part.

[0132] Among them, by dividing the composite rotation surface into areas according to the preset offset, the approximation area where the existing basic error formula becomes invalid can be distinguished, and by calculating the first distance from the measurement point to each subdivided surface, the minimum distance from the measurement point to the ideal rotation surface in the approximation area is determined, which effectively solves the problem of not being able to accurately determine which ideal rotation surface's geometric properties to use to calculate the minimum distance in the approximation area.

[0133] In addition, the present invention further proposes using an adaptive operator and finer particle speed to improve the coefficient of variation in the differential evolution algorithm, which can prevent premature convergence and improve the algorithm's convergence speed. Furthermore, using an adaptive operator to improve the crossover operator can meet the higher precision requirements of the ideal rotational surface bias parameters, achieving high-precision and efficient fitting of composite rotational surface profile errors.

[0134] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0135] The following are device embodiments of the present invention. For details not fully described therein, reference may be made to the corresponding method embodiments described above.

[0136] Figure 7 The following is a schematic diagram showing the structure of a device for calculating the profile error of a rotating part provided by an embodiment of the present invention. For ease of explanation, only the parts related to the embodiment of the present invention are shown, which are described in detail as follows:

[0137] like Figure 7 As shown, the rotational part contour error calculation device 7 includes: a conversion module 71, a division module 72, a calculation module 73 and an optimization module 74.

[0138] The conversion module 71 is used to perform coordinate transformation processing on each measurement point on the rotation surface of the rotation part to obtain the first coordinate of each measurement point; the rotation part includes at least two rotation surfaces.

[0139] The division module 72 is used to establish an ideal rotation surface model based on the ideal rotation surface design dimensions of the rotating part, and divide the ideal rotation surface model into regions to obtain a standard region and an approximate region; wherein the standard region contains a single ideal rotation surface; and the approximate region contains at least two ideal rotation surfaces.

[0140] For each measurement point, the calculation module 73 is configured to calculate the minimum distance from the measurement point to the ideal rotation surface within a certain standard area according to the geometric properties of the ideal rotation surface within the standard area when the measurement point is within the standard area.

[0141] The calculation module 73 is further configured to calculate, when the measurement point is in an approximation region, a first distance from the measurement point to each subdivision surface based on the first coordinate of the measurement point, and determine the minimum value of the first distances as the minimum distance from the measurement point to the ideal surface of revolution within the approximation region; wherein each subdivision surface is obtained by dividing the ideal surface of revolution within the approximation region.

[0142] The optimization module 74 is used to determine the profile error of the rotating surface of the rotating part based on the minimum distance.

[0143] In a possible implementation, the dividing module 72 is configured to use the connection point of each two ideal revolution surfaces as a midpoint and extend a preset offset to both ends of the ideal revolution surfaces to obtain an approximate region including the two ideal revolution surfaces.

[0144] The division module 72 is further configured to determine other regions in the ideal surface of revolution model, except the approximation region, as standard regions.

[0145] In a possible implementation, the calculation module 73 is configured to calculate the approximation parameters according to the error from the measurement point to each ideal rotation surface and a preset offset.

[0146] The calculation module 73 is further configured to determine that the measurement point is in the standard area when the approximation parameter is greater than or equal to zero.

[0147] The calculation module 73 is further configured to determine that the measurement point is in the approximation area when the approximation parameter is less than zero.

[0148] In a possible implementation, the calculation module 73 is configured to calculate the value of the Δ j+1 -Δ j |-2P, calculate the approximation parameters;

[0149] Among them, A represents the approximation parameter, Δ j+1 Indicates the error from the measurement point to the j+1th ideal rotation surface, Δ j It represents the error from the measuring point to the jth ideal rotation surface, and P represents the preset offset.

[0150] In a possible implementation, the calculation module 73 is configured to obtain the coordinates of the center point of each subdivision surface.

[0151] The calculation module 73 is further configured to calculate the distance from the measurement point to the center point of each subdivision surface according to the first coordinate of the measurement point and the coordinates of each center point, and determine the distance as the first distance.

[0152] In a possible implementation, the optimization module 74 is configured to construct a mathematical model of the rotary surface profile error based on the minimum distance.

[0153] The optimization module 74 is also used to optimize and solve the mathematical model of the rotational surface profile error to obtain the rotational surface profile error of the rotational part.

[0154] In one possible implementation, the optimization module 74 is configured to use the minimum distance corresponding to each measurement point as a different population individual to initialize the entire population and obtain an original population;

[0155] The optimization module 74 is used to perform mutation processing on each individual in the original population to obtain a mutant population;

[0156] The optimization module 74 is used to perform cross processing on the mutant population and the original population to obtain a cross population;

[0157] The optimization module 74 is used to calculate the fitness of each population individual in the cross population and the fitness of the corresponding population individuals in the original population, and determine the population individuals with better fitness as the population individuals in the next generation population;

[0158] The optimization module 74 is used to perform boundary checking and processing on the population individuals of the next generation population according to the boundary conditions to obtain the final population individuals of the next generation population;

[0159] The optimization module 74 is used to determine the final next-generation population as the original population, and jump to the step of "mutating each population individual in the original population to obtain a mutant population" to obtain a new mutant population, and execute subsequent steps until the iterative generation reaches the set value, completing the iterative optimization and obtaining the final rotation surface contour error.

[0160] In a possible implementation, the optimization module 74 is configured to: Perform mutation processing on each individual in the original population;

[0161] or,

[0162] according to Perform mutation processing on each individual in the original population;

[0163] Among them, v i represents the i-th individual in the mutant population, w r1 、w r2 and w r3 Represent any three individuals in the original population, and r1≠r2≠r3≠i, F represents the coefficient of variation, λ represents the adaptive operator, G m Indicates the maximum number of iterations, G indicates the current number of iterations, F0 indicates a random number in the range [0,2], V i V represents the individual update speed of the i-th individual in the mutant population; i-1 represents the individual update speed of the i-1th population individual in the mutant population, c1 and c2 represent the first learning factor and the second learning factor respectively, q1 and q2 represent random numbers in the range [0,1] respectively, and x best Indicates the optimal individual extreme value of the i-th population individual in all current populations, y best Represents the global optimal extreme value among all current populations, w i-1 Represents the i-1th population individual in the original population.

[0164] In a possible implementation, the optimization module 74 is configured to: Perform cross processing on the individuals in the mutant population and the corresponding individuals in the original population;

[0165] Among them, u i,j represents the sub-individual of the jth dimension in the i-th population individual in the cross population, v i,j represents the sub-individual of the jth dimension in the i-th population individual in the mutant population, w i,j represents the j-th dimension sub-individual in the i-th population individual in the original population, rand is a random number in the interval [0, 1], randi represents any randomly selected dimension number, randi∈{1, 2, ..., D}, D represents the population dimension, CR represents the crossover operator, CR0 represents a real number in the range [0, 1], and λ represents an adaptive operator.

[0166] In the embodiment of the present invention, a transformation module 71 is used to perform coordinate transformation processing on all measurement points on the rotational surface of the rotational part to obtain the first coordinates of all measurement points; a division module 72 is used to establish an ideal rotational surface model based on the design dimensions of the ideal rotational surface of the rotational part, and to divide the ideal rotational surface model into regions to obtain a standard region and an approximation region; for each measurement point, a calculation module 73 is used to calculate the minimum distance from the measurement point to the ideal rotational surface within the standard region based on the geometric properties of the ideal rotational surface within the standard region when the measurement point is in a certain standard region; when the measurement point is in a certain approximation region, the first distance from the measurement point to each subdivided surface is calculated based on the first coordinate of the measurement point, and the minimum value of the first distances is determined as the minimum distance from the measurement point to the ideal rotational surface within the approximation region; an optimization module 74 is used to determine the rotational surface profile error of the rotational part based on the minimum distance, so as to accurately calculate the rotational surface profile error of the composite rotational surface in the rotational part.

[0167] Among them, the division module 72 can distinguish the approximation area that makes the existing error basic formula invalid by dividing the composite rotation surface into areas according to the preset offset, and the calculation module 73 determines the minimum distance from the measurement point to the ideal rotation surface in the approximation area by calculating the first distance from the measurement point to each subdivided surface, effectively solving the problem of being unable to accurately determine which ideal rotation surface's geometric properties to use to calculate the minimum distance in the approximation area.

[0168] Furthermore, the present invention utilizes an adaptive operator and finer particle speed in optimization module 74 to improve the coefficient of variation in the differential evolution algorithm, thereby preventing premature convergence and improving the algorithm's convergence rate. Furthermore, optimization module 74 utilizes an adaptive operator to improve the crossover operator, meeting the higher precision requirements for the ideal rotational surface offset parameters and achieving high-precision and efficient fitting of composite rotational surface profile errors.

[0169] Figure 8 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 8 As shown, the electronic device 8 of this embodiment includes: a processor 80, a memory 81, and a computer program 82 stored in the memory 81 and executable on the processor 80. When the processor 80 executes the computer program 82, the steps in the above-mentioned embodiments of the method for calculating the profile error of a rotating part are implemented, such as Figure 1 Alternatively, when the processor 80 executes the computer program 82, the functions of the modules / units in the above-mentioned device embodiments are realized, for example, Figure 7 Functions of modules 71 to 74 are shown.

[0170] Exemplarily, the computer program 82 may be divided into one or more modules / units, which are stored in the memory 81 and executed by the processor 80 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program 82 in the electronic device 8. For example, the computer program 82 may be divided into Figure 7 Modules 71 to 74 are shown.

[0171] The electronic device 8 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 8 may include, but is not limited to, a processor 80 and a memory 81. Those skilled in the art will understand that Figure 8 It is only an example of the electronic device 8 and does not constitute a limitation of the electronic device 8. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0172] The processor 80 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0173] The memory 81 may be an internal storage unit of the electronic device 8, such as a hard disk or memory of the electronic device 8. The memory 81 may also be an external storage device of the electronic device 8, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 8. Furthermore, the memory 81 may include both an internal storage unit of the electronic device 8 and an external storage device. The memory 81 is used to store the computer program and other programs and data required by the electronic device. The memory 81 may also be used to temporarily store data that has been output or is about to be output.

[0174] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0175] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0176] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0177] In the embodiments provided by the present invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0178] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0179] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0180] If the integrated module / unit is implemented in the form of 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 present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned embodiments of the method for calculating the profile error of the rotating part. Wherein, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0181] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A method for calculating the profile error of a rotating part, characterized in that: include: Performing coordinate transformation processing on each measuring point on a rotational surface of a rotational part to obtain a first coordinate of each measuring point; the rotational part includes at least two rotational surfaces; An ideal surface of revolution model is established according to the design dimensions of the ideal surface of revolution of the rotating part, and the ideal surface of revolution model is divided into regions to obtain a standard region and an approximate region; wherein the standard region contains a single ideal surface of revolution, and the approximate region contains at least two ideal surfaces of revolution; For each measuring point, when the measuring point is in a certain standard area, the minimum distance from the measuring point to the ideal rotation surface in the standard area is calculated according to the geometric properties of the ideal rotation surface in the standard area; When the measuring point is within an approximation region, first distances from the measuring point to each subdivision surface are calculated based on the first coordinate of the measuring point, and a minimum value among the first distances is determined as the minimum distance from the measuring point to the ideal surface of revolution within the approximation region; wherein each subdivision surface is obtained by dividing the ideal surface of revolution within the approximation region; Based on the minimum distance, a profile error of the rotational surface of the rotational part is determined.

2. The method for calculating the profile error of a rotating part according to claim 1, wherein: The ideal surface of revolution model is divided into regions, including: Taking the connection point of each two ideal rotation surfaces as the midpoint, extending the preset offset amount to both ends of the ideal rotation surfaces to obtain an approximate area containing the two ideal rotation surfaces; The other areas in the ideal rotation surface model except the approximation area are determined as standard areas.

3. The method for calculating the profile error of a rotating part according to claim 2, wherein: After dividing the ideal surface of revolution model into regions, the method further includes: Calculate the approximation parameters based on the error between the measurement point and each ideal rotation surface and the preset offset; When the approximation parameter is greater than or equal to zero, determining that the measurement point is in a standard area; When the approximation parameter is less than zero, it is determined that the measurement point is in the approximation area.

4. The method for calculating the profile error of a rotating part according to claim 3, wherein: The method of calculating the approximation parameters based on the error between the measurement point and each ideal rotation surface and the preset offset includes: According to A=|Δ j+1 -Δ j |-2P, calculate the approximation parameters; Among them, A represents the approximation parameter, Δ j+1 Indicates the error from the measurement point to the j+1th ideal rotation surface, Δ j It represents the error from the measuring point to the jth ideal rotation surface, and P represents the preset offset.

5. The method for calculating the profile error of a rotating part according to claim 4, wherein: The step of respectively calculating the first distance from the measurement point to each subdivision surface includes: Get the coordinates of the center point of each subdivision surface; According to the first coordinate of the measuring point and the coordinates of each center point, the distance from the measuring point to the center point of each subdivision surface is calculated respectively, and the distance is determined as the first distance.

6. The method for calculating the profile error of a rotating part according to any one of claims 1 to 5, characterized in that: Determining the profile error of the rotational surface of the rotational part based on the minimum distance includes: Constructing a mathematical model of the rotary surface profile error based on the minimum distance; The mathematical model of the rotation surface profile error is optimized and solved to obtain the rotation surface profile error of the rotational part.

7. The method for calculating the profile error of a rotating part according to claim 6, wherein: The optimizing and solving the mathematical model of the rotary surface profile error includes: The minimum distance corresponding to each measurement point is used as a different population individual, and the entire population is initialized to obtain the original population; Perform mutation processing on each individual in the original population to obtain a mutant population; Crossing the variant population with the original population to obtain a crossover population; Calculate the fitness of each population individual in the cross population and the fitness of the corresponding population individual in the original population respectively, and determine the population individual with better fitness as the population individual in the next generation population; According to the boundary conditions, the population individuals of the next generation population are checked and processed to obtain the final population individuals of the next generation population; The final next-generation population is determined as the original population, and the process jumps to the step of "mutating each individual in the original population to obtain a mutant population" to obtain a new mutant population. Subsequent steps are performed until the iterative generation number reaches the set value, completing the iterative optimization and obtaining the final rotation surface profile error.

8. The method for calculating the profile error of a rotating part according to claim 7, wherein: The mutation process of each individual in the original population includes: according to Perform mutation processing on each individual in the original population; or, according to Perform mutation processing on each individual in the original population; Among them, v i represents the i-th individual in the mutant population, w r1 、w r2 and w r3 Represent any three individuals in the original population, and r1≠r2≠r3≠i, F represents the coefficient of variation, λ represents the adaptive operator, G m Indicates the maximum number of iterations, G indicates the current number of iterations, F0 indicates a random number in the range [0,2], V i V represents the individual update speed of the i-th individual in the mutant population; i-1 represents the individual update speed of the i-1th population individual in the mutant population, c1 and c2 represent the first learning factor and the second learning factor respectively, q1 and q2 represent random numbers in the range [0,1] respectively, and x best Indicates the optimal individual extreme value of the i-th population individual in all current populations, y best Represents the global optimal extreme value among all current populations, w i-1 Represents the i-1th population individual in the original population.

9. The method for calculating the profile error of a rotating part according to claim 7, wherein: The cross processing of the variant population and the original population includes: according to Perform cross processing on the individuals in the mutant population and the corresponding individuals in the original population; Among them, u i,j represents the sub-individual of the jth dimension in the i-th population individual in the cross population, v i,j represents the sub-individual of the jth dimension in the i-th population individual in the mutant population, w i,j represents the j-th dimension sub-individual in the i-th population individual in the original population, rand is a random number in the interval [0, 1], randi represents any randomly selected dimension number, randi∈{1, 2, ..., D}, D represents the population dimension, CR represents the crossover operator, CR0 represents a real number in the range [0, 1], and λ represents an adaptive operator.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for calculating the profile error of a rotating part as described in any one of claims 1 to 9 are implemented.

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