Integral impeller machining method, device and equipment based on five-axis machining center

Abstract

This application relates to the field of machining technology, specifically to an integral impeller machining method, device and equipment based on a five-axis machining center. The method includes: obtaining the tool position data of the starting tool position point and the ending tool position point of the interpolation path segment according to the geometric characteristics of the impeller model, as well as the time interval between the starting tool position point and the ending tool position point; randomly generating a plurality of interpolation matrices, and constructing a judgment matrix corresponding to each interpolation matrix; obtaining each effective interpolation matrix; obtaining the overall non-smoothness, interpolation abnormality degree, tool position point optimization weight, and interpolation adaptability degree of each column in each effective interpolation matrix; iterating the interpolation matrix using an optimization algorithm to obtain the optimal interpolation matrix, and machining the integral impeller. This application can make the change speed of the cutting tool relatively smooth during the machining process, effectively reduce the cutting tool jitter, and improve the machining quality of the integral impeller.

Description

Technical Field

[0001] The present application relates to the technical field of machining, and particularly relates to a method, device and equipment for machining an integral impeller based on a five-axis machining center. Background Art

[0002] A five-axis machining center is a numerically controlled machining tool with five degrees of freedom, capable of machining complex industrial parts. The integral impeller part is complex and has high requirements for surface smoothness, and is usually manufactured by a five-axis machining method. When machining an integral impeller by five-axis machining, it is necessary to first obtain the geometric model of the target impeller, and then plan the tool path according to the geometric model to generate the cutter location point information to control the five-axis numerical control machine tool for cutting. When the five-axis numerical control machine tool performs cutting based on the cutter location point information, it is necessary to perform path interpolation according to the cutter location point information to make the tool path smooth and reduce the error between the finished impeller and the impeller model.

[0003] When performing path interpolation according to the cutter location point information by the traditional method, a curve fitting algorithm is usually used to calculate the cutter location points. New cutter location points are inserted on the fitting curve between two cutter location points to complete the path interpolation and obtain the control path of the cutting tool. Among them, since the movement speed of each degree of freedom is not considered smooth during the cutter location point interpolation process, when the cutting tool moves along the obtained control path, the speed of some degrees of freedom may change violently, resulting in an increase in the vibration of the cutting tool during the cutting process, reducing the surface smoothness of the impeller and affecting the machining quality of the integral impeller. Summary of the Invention

[0004] In order to solve the above technical problems, a method, device and equipment for machining an integral impeller based on a five-axis machining center are provided to solve the existing problems.

[0005] The solution of the present application to solve the technical problems is to provide a method, device and equipment for machining an integral impeller based on a five-axis machining center, including the following steps:

[0006] In the first aspect, an embodiment of the present application provides a method for machining an integral impeller based on a five-axis machining center, and the method includes the following steps:

[0007] Obtain the cutter location data of the starting cutter location point and the ending cutter location point of the interpolation path segment, and the time interval between the starting cutter location point and the ending cutter location point according to the geometric characteristics of the impeller model;

[0008] Randomly generate a plurality of multi-dimensional matrices, denoted as each interpolation matrix, where each column vector in the interpolation matrix corresponds to an interpolation cutter location point; use the cutter location data of the starting cutter location point and the ending cutter location point, and each interpolation matrix to construct a judgment matrix corresponding to each interpolation matrix; based on the time interval, analyze the change rate between adjacent elements in each row of the judgment matrix to obtain each effective interpolation matrix;

[0009] Analyze the change rate of each column element within each row in the judgment matrix corresponding to each valid interpolation matrix, as well as the average level of the change rate of all row elements within each column in the judgment matrix, to obtain the overall non-smoothness of each column in each valid interpolation matrix;

[0010] Analyze the distance from the interpolation tool position points corresponding to each column in each valid interpolation matrix to the surface of the impeller model, as well as the movement duration required for the interpolation tool position points corresponding to two adjacent columns, and combine the overall non-smoothness to determine the interpolation abnormality of each column in each valid interpolation matrix;

[0011] According to the difference situation between the normal vectors of all tool position points within different ranges of local areas at the tool position point on the impeller model surface that is closest to the interpolation tool position point corresponding to each column in each valid interpolation matrix, determine the tool position point optimization weight of each column in each valid interpolation matrix; combine the interpolation abnormality to determine the interpolation adaptability of each valid interpolation matrix;

[0012] Based on the interpolation adaptability, iterate the interpolation matrix using an optimization algorithm to obtain the optimal interpolation matrix and machine the integral impeller.

[0013] Preferably, the determination of the judgment matrix corresponding to each interpolation matrix includes:

[0014] Arrange in the order of the tool position data of the starting tool position point, each column vector in each interpolation matrix, and the tool position data of the ending tool position point to form the judgment matrix corresponding to each interpolation matrix.

[0015] Preferably, the obtaining of each valid interpolation matrix includes:

[0016] Based on the time interval between the starting tool position point and the ending tool position point, as well as the number of columns of the judgment matrix, calculate the interpolation time of each column in the judgment matrix;

[0017] Obtain the preset maximum limit speed of each degree of freedom through the numerical control system of the five-axis machining tool, where each row in the judgment matrix represents a degree of freedom;

[0018] Based on the interval duration between the interpolation times of two adjacent columns in the judgment matrix, calculate the change rate between each column element in any row in the judgment matrix and its previous column element and next column element respectively, and record it as the forward speed and backward speed of each column element in the any row;

[0019] If the forward speed and backward speed of all column elements in all rows in the judgment matrix are less than or equal to the preset maximum limit speed of the degree of freedom corresponding to the row where the element is located, record the interpolation matrix corresponding to the judgment matrix as a valid interpolation matrix.

[0020] Preferably, in the judgment matrix, the Interpolation time of the column The calculation formula is: , where is the column in the judgment matrix, is the time interval between the starting tool point and the ending tool point, is the number of all columns in the judgment matrix.

[0021] Preferably, obtaining the overall non-smoothness of each column in each effective interpolation matrix includes:

[0022] Normalize all column elements in each row of the judgment matrix corresponding to each effective interpolation matrix, and denote it as the normalized judgment matrix;

[0023] The velocity non-smoothness of the element corresponding to the th row and the th column in the normalized judgment matrix The calculation formula is: , is the overall velocity of the element corresponding to the th row and the th column in the normalized judgment matrix, is the overall velocity of the element corresponding to the th row and the th column in the normalized judgment matrix, is the interpolation time of the th column in the normalized judgment matrix, is the interpolation time of the th column in the normalized judgment matrix, is the number of all columns in the normalized judgment matrix; is the element value corresponding to the th row and the th column in the normalized judgment matrix, is the element value corresponding to the th row and the th column in the normalized judgment matrix;

[0024] Take the mean value of the velocity non-smoothness of the elements corresponding to all rows in the same column of the normalized judgment matrix as the overall non-smoothness of each column in the normalized judgment matrix. Among them, the 2nd column to the (R - 1)th column in the normalized judgment matrix are effective interpolation matrices, and the overall non-smoothness of each column in each effective interpolation matrix is obtained.

[0025] Preferably, determining the interpolation abnormality of each column in each effective interpolation matrix includes:

[0026] Input the column vectors in each valid interpolation matrix into the numerical control system of the five-axis machining tool, obtain the mapping points of the interpolation tool path points corresponding to each column in each valid interpolation matrix in the three-dimensional space where the impeller model is located, and calculate the shortest distance from the mapping points to the surface of the impeller model, denoted as the relative distance;

[0027] Obtain the preset maximum feed rate through the numerical control system of the five-axis machining tool, calculate the ratio of the relative distance to the interval duration, denoted as the relative speed, and take the ratio of the relative speed to the preset maximum feed rate as the model fitting degree of each column in each valid interpolation matrix;

[0028] The interpolation abnormality degree is the product of the model fitting degree and the overall non-smoothness degree.

[0029] Preferably, determining the tool path point optimization weights of each column in each valid interpolation matrix includes:

[0030] Denote the coordinates of the point on the surface of the impeller model that is closest to the interpolation tool path point corresponding to each column in each valid interpolation matrix as the corresponding point cloud of each model;

[0031] Obtain the point cloud data of each point on the surface of the impeller model, and use the normal vector estimation algorithm based on local plane fitting to calculate the normal vectors of the point cloud data;

[0032] Denote the preset first number of point cloud data and the preset second number of point cloud data that are closest to the corresponding point cloud of the model on the surface of the impeller model as the small-range point cloud set and the large-range point cloud set corresponding to each interpolation tool path point respectively;

[0033] Calculate the sum vector of the normal vectors of all point cloud data in the small-range point cloud set, and form a small-range vector by taking the ratio of each element in the sum vector to the number of all point cloud data in the small-range point cloud set; correspondingly, obtain a large-range vector for all point cloud data in the large-range point cloud set;

[0034] Take the modulus of the difference vector between the small-range vector and the large-range vector as the local complexity of the interpolation tool path point corresponding to each column in each valid interpolation matrix; perform normalization processing on the local complexity of the interpolation tool path points corresponding to all columns in each valid interpolation matrix as the tool path point optimization weight of each column in each valid interpolation matrix.

[0035] Preferably, the interpolation adaptability degree is the sum value of the products of the tool path point optimization weights of all columns in each valid interpolation matrix and the interpolation abnormality degree.

[0036] In a second aspect, an embodiment of the present application further provides an integral impeller machining device based on a five-axis machining center. A computer program is stored in the device, and when the computer program is executed by a processor, the steps of the above-mentioned integral impeller machining method based on a five-axis machining center are implemented.

[0037] In a third aspect, an embodiment of the present application further provides an integral impeller machining equipment based on a five-axis machining center, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the above-mentioned integral impeller machining method based on a five-axis machining center are implemented.

[0038] The present application has at least the following beneficial effects:

[0039] In this application, an interpolation matrix is constructed in the interpolation path between the starting tool point and the ending tool point, and a tool path planning is formed based on the starting tool point, the interpolation matrix, and the ending tool point. A judgment matrix is constructed to analyze whether the change rate between adjacent column elements in the same row of the judgment matrix meets the preset constraint conditions, so as to screen the interpolation matrix, obtain each effective interpolation matrix, and form a cutting tool control scheme executable by a five-axis machine tool. Secondly, calculate the overall non-smoothness of each column in each effective interpolation matrix. The beneficial effect is that it considers the smoothness of the cutting speed of the interpolation tool points corresponding to different columns in the effective interpolation matrix, so as to reflect the impact of the cutting speed of the interpolation tool points on the cutting speed of the entire cutting process, which is convenient for subsequent screening of effective interpolation matrices with gentle cutting tool speed changes. Calculate the model fitting degree of each column in each effective interpolation matrix, and calculate the interpolation abnormality of each column in each effective interpolation matrix. The beneficial effect is that it considers the fitting degree between the interpolation tool points corresponding to different columns in the effective interpolation matrix and the impeller model, which is convenient for subsequent screening of effective interpolation matrices that fit closely with the impeller model, and can evaluate the interpolation effect of the interpolation tool points in each column of the effective interpolation matrix, which is beneficial to subsequent screening of effective interpolation matrices that can not only ensure smooth changes in the cutting tool speed but also ensure that the corresponding interpolation tool points fit the impeller model. Calculate the tool point optimization weight of each column in each effective interpolation matrix. The beneficial effect is that it considers the complex situation at the position of the interpolation tool points in each column of the effective interpolation matrix in the impeller model, and assigns higher weights to the interpolation tool points at complex local positions, which helps to improve the control effect of the effective interpolation matrix at the complex parts of the impeller model and improve the overall effect of the interpolation result. Determine the interpolation adaptability of each effective interpolation matrix, iterate the interpolation matrix using an optimization algorithm, obtain the optimal interpolation matrix, and machine the integral impeller. The beneficial effect is that through continuous iteration, an effective interpolation matrix is obtained, and according to the interpolation adaptability, the optimal interpolation matrix is selected, so that the speed change of the cutting tool is relatively gentle and fits the impeller model better, making the interpolation result of the cutting tool reach the best. Compared with the traditional method, it can make the cutting tool change speed more smoothly during the machining process, effectively reduce the cutting tool jitter, improve the smoothness of the impeller surface, and improve the machining quality of the integral impeller. Description of the Drawings

[0040] The following further elaborates in detail the integral impeller machining method based on a five-axis machining center of this application with reference to the drawings.

[0041] Figure 1 It is the flowchart of the steps of the integral impeller machining method based on a five-axis machining center provided by an embodiment of this application;

[0042] Figure 2 It is the flowchart of the steps of the method for obtaining the tool point optimization weight of each column in each effective interpolation matrix provided by an embodiment of this application. Detailed implementation manners

[0043] In order to make the objectives, technical solutions and advantages of the present application more clear and understandable, the following further elaborates in detail on the integral impeller machining method, device and equipment based on a five-axis machining center proposed in the present application in combination with the accompanying drawings and implementation examples. It should be understood that the specific implementation examples described herein are only used to explain the present application and are not used to limit the present application.

[0044] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs.

[0045] Please refer to Figure 1 , which shows a flowchart of the steps of the integral impeller machining method based on a five-axis machining center provided in an embodiment of the present application. The method includes the following steps:

[0046] Step 1, obtain the tool position data of the starting tool position point and the ending tool position point of the interpolation path segment, and the time interval between the starting tool position point and the ending tool position point according to the geometric features of the impeller model.

[0047] Compared with three-axis CNC machine tools, five-axis CNC machine tools have two additional rotating axes, which enable the tool to obtain more machining freedoms, increase the flexibility of the cutting position and angle of the tool when machining complex curved surface parts, reduce the number of tool changes and the number of times the parts are re-clamped, and further improve the machining accuracy of complex curved surface parts.

[0048] When a five-axis machining machine processes an impeller, it will convert the geometric information of the impeller into tool position point information. Therefore, according to the three-dimensional geometric model of the impeller, determine the motion trajectory of the tool position, obtain the tool position data of all tool position points, select any two adjacent tool position points, and respectively use them as the starting tool position point and the ending tool position point of the interpolation path segment, and interpolate multiple tool position points between the starting tool position point and the ending tool position point.

[0049] It should be noted that the form of the tool position data of the th tool position point is , where the first three elements represent the position coordinates of the th tool position point, and the last two elements represent the angles of the two rotating axes corresponding to the th tool position point. The tool position data reflects the position of the cutting tool and the attitude of the impeller at the th tool position point.

[0050] At the same time, obtain the time interval T between the starting tool position point and the ending tool position point through the numerical control system of the five-axis machining machine, which represents the time taken by the numerical control machine tool to control the cutting tool from the starting tool position point to the ending tool position point.

[0051] So far, the tool position data of the starting tool position point and the ending tool position point of the interpolation path segment, as well as the time interval between the starting tool position point and the ending tool position point, are obtained.

[0052] Step 2: Randomly generate multiple multi-dimensional matrices, denoted as each interpolation matrix. Among them, each column vector in the interpolation matrix corresponds to an interpolation tool position point; use the tool position data of the starting tool position point and the ending tool position point, as well as each interpolation matrix, to construct a judgment matrix corresponding to each interpolation matrix; based on the time interval, analyze the change rate between adjacent elements in each row of the judgment matrix, and obtain each effective interpolation matrix.

[0053] The cutting tool movement path between the starting tool position point and the ending tool position point is optimized through a genetic algorithm to obtain a cutting tool movement path that fits the impeller model and has a smooth speed change of each parameter in the tool position data. Therefore, by constructing an interpolation matrix and setting constraint conditions for the interpolation matrix, the interpolation matrix becomes a machining plan that can be executed by a five-axis machining tool.

[0054] Randomly generate multiple multi-dimensional matrices, denoted as each interpolation matrix. Among them, the m-th column vector in the interpolation matrix is denoted as the tool position data of the m-th interpolation tool position point;

[0055] It should be noted that since the tool position data is a 5-dimensional vector, the interpolation matrix is a matrix with 5 rows and M columns. In this embodiment, M takes the value of 10. As other implementation methods, the implementer can set it according to the actual situation; the interpolation matrix contains a total of M columns, indicating that M tool position points are interpolated between the starting tool position point and the ending tool position point. Then, the column vector represents the tool position data of the th interpolated tool position point.

[0056] Construct a judgment matrix corresponding to each interpolation matrix. Among them, the tool position data of the starting tool position point is used as the first column of the judgment matrix; the tool position data of all interpolation tool position points in each interpolation matrix is used as the second column to the (M + 1)-th column of the judgment matrix; the tool position data of the ending tool position point is used as the (M + 2)-th column of the judgment matrix;

[0057] Thus, based on the time interval between the starting tool position point and the ending tool position point, the interpolation time of the th column in the judgment matrix is calculated by the formula: , where is the th column in the judgment matrix, is the time interval between the starting tool position point and the ending tool position point, is the number of all columns in the judgment matrix;

[0058] Then the time interval between the interpolation times of two adjacent columns in the judgment matrix is .

[0059] Calculate the time interval between two adjacent columns in the judgment matrix, and calculate the time interval between any two columns in the judgment matrix;

[0060] In this embodiment, the time when the cutting tool is at the starting tool position is recorded as the 0 time, and the time when the cutting tool is at the ending tool position is recorded as the T time. Then, the interpolation tool position corresponding to the m-th column in the judgment matrix represents the position of the cutting tool at the time and the posture of the impeller. When the five-axis machining machine executes the cutting scheme of the interpolation matrix, it is sufficient to control the posture of the cutting tool and the impeller to make the m-th interpolation tool position at the time.

[0061] It should be noted that the time interval between any two columns in the judgment matrix reflects the time required for the cutting tool of the five-axis machining machine to move from one interpolation tool position to the next interpolation tool position between the interpolation tool positions corresponding to two adjacent columns.

[0062] Obtain the preset maximum limit speed of each degree of freedom through the numerical control system of the five-axis machining machine, where each row in the judgment matrix represents a degree of freedom;

[0063] In this embodiment, the form of the tool position data is , then the corresponding 5 degrees of freedom are X, Y, Z, A, C respectively. The preset maximum limit speed corresponding to the X axis is 800 mm / min, the preset maximum limit speed corresponding to the Y axis is 800 mm / min, the preset maximum limit speed corresponding to the Z axis is 800 mm / min, the preset maximum limit speed corresponding to the A axis is 500° / min, and the preset maximum limit speed corresponding to the C axis is 500° / min. As other implementation manners, the implementer can set according to the actual situation.

[0064] It should be noted that the preset maximum limit speed reflects the highest movement speed that each axis of the five-axis machining machine can reach under normal operating conditions.

[0065] Further, construct constraint conditions for the elements in the 2nd to M+1 columns of the judgment matrix respectively, and screen the interpolation matrix to evaluate whether the interpolation scheme of the interpolation matrix can be executed by the five-axis machine tool. Specifically:

[0066] Based on the time interval between the interpolation times of two adjacent columns in the judgment matrix, calculate the change rate between each column element and its previous column element in any row of the judgment matrix, denoted as the forward velocity of each column element in any row; calculate the change rate between each column element and its subsequent column element in any row, denoted as the backward velocity of each column element in any row.

[0067] In this embodiment, for the forward velocity and backward velocity of the element corresponding to the th row and th column in the judgment matrix, the calculation formulas are as follows: , where is the forward velocity of the element corresponding to the th row and th column in the judgment matrix, is the element value corresponding to the th row and th column in the judgment matrix, is the element value corresponding to the th row and th column in the judgment matrix, is the time interval between the interpolation times of the th column and the th column in the judgment matrix; , where is the backward velocity of the element corresponding to the th row and th column in the judgment matrix, is the element value corresponding to the th row and th column in the judgment matrix, is the element value corresponding to the th row and th column in the judgment matrix, is the time interval between the interpolation times of the th column and the th column in the judgment matrix;

[0068] It should be noted that the forward velocity reflects the average velocity of the th degree of freedom corresponding to the th tool position point during the movement from the th tool position point to the th tool position point; the backward velocity reflects the average velocity of the th degree of freedom corresponding to the th row during the movement from the

[0069] For all elements from the second column to the (M + 1)-th column in the judgment matrix, if the forward speed and backward speed of all column elements in all rows of the judgment matrix are less than or equal to the preset maximum limit speed of the degrees of freedom corresponding to the rows of the elements, the interpolation matrix corresponding to the judgment matrix is denoted as a valid interpolation matrix;

[0070] It should be noted that a valid interpolation matrix represents an interpolation matrix that meets the constraint conditions and represents a machining plan that can be adopted by a five-axis machine tool.

[0071] Thus, all valid interpolation matrices are obtained.

[0072] Step 3: Analyze the change rate of each column element in each row of the judgment matrix corresponding to each valid interpolation matrix, and the average level of the change rate of all row elements in each column of the judgment matrix, so as to obtain the overall non-smoothness of each column in each valid interpolation matrix.

[0073] Multiple interpolation matrices are randomly generated, and the genetic algorithm is used to screen out the interpolation matrices with gentle speed changes and fitting the impeller surface as the machining plan for the five-axis machine tool. The row in the interpolation matrix represents the position change of the cutting tool control device of the -th degree of freedom. In order to avoid too fast speed change of the cutting tool in the -th degree of freedom, resulting in cutting tool vibration and reducing the machining quality of the impeller. Therefore, for the valid interpolation matrices that meet the constraint conditions, the speed non-smoothness is calculated to evaluate the rapid change degree of different degrees of freedom of the valid interpolation matrices that meet the constraint conditions, and then the valid interpolation matrices that can control the smooth movement of the cutting tool are screened out. Specifically:

[0074] Normalize all column elements in each row of the judgment matrix corresponding to each valid interpolation matrix, and denote it as the normalized judgment matrix;

[0075] In this embodiment, the normalization process is as follows: for the row vector of the -th row in the judgment matrix corresponding to each valid interpolation matrix, calculate the ratio of each column element in the -th row to the preset maximum limit speed of the degree of freedom corresponding to the -th row. The ratios of all columns in the -th row form the normalized vector of the -th row. The normalized vectors of all rows form the normalized judgment matrix, where the number of columns of the normalized judgment matrix is R = M + 2.

[0076] Calculate the speed non-smoothness of the element corresponding to the -th column in the -th row in the normalized judgment matrix. The calculation formula is:

[0077]

[0078]

[0079] in, is the normalized judgment matrix Line The overall speed of the corresponding elements in the column, is the normalized judgment matrix Line The overall speed of the corresponding elements in the column, is the normalized judgment matrix The interpolation time of the column, is the normalized judgment matrix The interpolation time of the column, is the number of all columns in the normalized judgment matrix; is the normalized judgment matrix Line The element value corresponding to the column, is the normalized judgment matrix Line The element value corresponding to the column.

[0080] It should be noted that reflects the average speed of the cutting tool between two interpolation moments, and the overall speed reflects the speed of the cutting tool in the i-th degree of freedom under the control of the s-th element; further, by , reflecting the absolute value of the acceleration of the cutting tool in the i-th degree of freedom under the control of the s-th element. The smaller the absolute value of the acceleration, the smoother the speed change of the cutting tool under the control of the s-th element, the smaller the speed non-smoothness, and the less drastic the speed change of the cutting tool controlled by the s-th element. The more it can reduce the jitter of the cutting tool caused by the drastic speed change, and improve the impeller processing quality.

[0081] The average of the speed non-smoothness of the corresponding elements of all rows in the same column of the normalized judgment matrix is ​​used as the overall non-smoothness of each column in the normalized judgment matrix, wherein the 2nd column to the R-1th column in the normalized judgment matrix are valid interpolation matrices, and the overall non-smoothness of each column in each valid interpolation matrix is ​​obtained;

[0082] It should be noted that the smaller the overall non-smoothness is, the smoother the cutting tool speed under the control of the tool position data in the corresponding column is, and the more the cutting tool jitter caused by speed mutation can be reduced, improving the machining quality of the impeller. Secondly, a total of R = M + 2 overall non-smoothness values are obtained for the judgment matrix. Among them, the overall non-smoothness values of the columns from the 2nd column to the (S - 1)th column are the overall non-smoothness values of the interpolated tool positions corresponding to each column in the effective interpolation matrix, and the overall smoothness values of the 1st column and the Sth column are the overall non-smoothness values of the starting tool position and the ending tool position.

[0083] Thus, the overall non-smoothness of each column in each effective interpolation matrix is obtained.

[0084] Step 4: Analyze the distance from the interpolated tool position corresponding to each column in each effective interpolation matrix to the surface of the impeller model, and the movement duration required for the interpolated tool positions corresponding to two adjacent columns. Combining the overall non-smoothness, determine the interpolation abnormality of each column in each effective interpolation matrix.

[0085] Furthermore, analyze the distance between the cutting position where the interpolated tool position corresponding to each column in the effective interpolation matrix is located and the surface of the impeller model, and evaluate the situation where the actual cutting effect caused by the cutting result of the interpolated tool position does not conform to the impeller model. By calculating the model fitting degree, judge the fitting degree between the interpolated tool position corresponding to each column in the effective interpolation matrix and the surface of the impeller model. To judge the fitting degree between the interpolated tool position and the impeller model, it is necessary to map the tool position data of the interpolated tool position into the coordinate system where the impeller model is located for comparison. Specifically:

[0086] Input the mth column vector in each effective interpolation matrix into the numerical control system of the five-axis machining tool, obtain the mapping point of the interpolated tool position corresponding to the mth column in the three-dimensional space where the impeller model is located, and calculate the shortest distance from the mapping point to the surface of the impeller model, which is denoted as the relative distance of the interpolated tool position corresponding to the mth column.

[0087] In this embodiment, calculate the Euclidean distance from the mapping point to the surface of the impeller model. Among them, the calculation of the Euclidean distance is a well-known technology and will not be elaborated here.

[0088] It should be noted that the smaller the relative distance is, the more the tool position data of the interpolated tool position corresponding to the mth column fits the impeller model.

[0089] Obtain the preset maximum feed rate through the numerical control system of the five-axis machining tool, calculate the ratio of the relative distance to the interval duration between the interpolation times of two adjacent columns in the effective interpolation matrix, which is denoted as the relative speed, and use the ratio of the relative speed to the preset maximum feed rate as the model fitting degree of the mth column in each effective interpolation matrix.

[0090] In this embodiment, the preset maximum feed rate is taken as 23 mm / s. As other implementation manners, the implementer can set it according to the actual situation.

[0091] It should be noted that the m-th column in the effective interpolation matrix corresponds to the m-th interpolation tool position point. The relative speed reflects the rate of change of the distance between the mapping point corresponding to the m-th interpolation tool position point and the surface of the impeller model per unit time, and reflects the influence of the moving speed of the tool position point on the machining accuracy. If the relative speed is closer to the preset maximum feed rate, it indicates that the deviation of the mapping point has approached the maximum allowable range during the machining process, and the greater the model fitting degree. When machining with the tool position data of the interpolation tool position point in the interpolation matrix corresponding to the mapping point, the more deviated from the impeller model, the smaller the model fitting degree. When machining with the tool position data of the interpolation tool position point in the interpolation matrix corresponding to the mapping point, the more it fits the impeller model, and the better the machining effect.

[0092] Furthermore, for the interpolation tool position points corresponding to each column in the effective interpolation matrix, when controlling the cutting tool for interpolation, it is necessary to ensure both the smooth change of the cutting tool speed to prevent the cutting tool from jittering and the interpolation tool position points fitting the impeller model. If the change in the cutting tool speed is not smooth enough, the jitter speed of the cutting tool is relatively large, and even if the tool position point fits the impeller model, it cannot achieve the corresponding cutting effect. Similarly, even if the cutting tool speed changes smoothly, but the tool position point does not fit the impeller model well, the smooth speed cannot obtain a good cutting effect either.

[0093] Therefore, based on the model fitting degree and the overall non-smoothness, the interpolation abnormality degree is determined to reflect the interpolation effect of the interpolation tool position points, specifically:

[0094] The product of the model fitting degree and the overall non-smoothness is used as the interpolation abnormality degree for each column in each effective interpolation matrix;

[0095] It should be noted that the smaller the interpolation abnormality degree, the smoother the cutting tool speed change can be ensured when machining according to the interpolation tool position points corresponding to each column in the effective interpolation matrix, and the interpolation tool position points can also be ensured to fit the impeller model, resulting in a better impeller machining effect.

[0096] Thus, the interpolation abnormality degree for each column in each effective interpolation matrix is obtained.

[0097] Step 5: Determine the tool position point optimization weight for each column in each effective interpolation matrix according to the difference situation among the normal vectors of all tool position points in different ranges of local areas at the tool position point on the impeller model surface that is closest to the interpolation tool position point corresponding to each column in each effective interpolation matrix; combine the interpolation abnormality degree to determine the interpolation adaptability degree of each effective interpolation matrix.

[0098] For each of the M columns of the valid interpolation matrix, there are M interpolated tool points. Different interpolated tool points correspond to different model positions of the impeller. The impeller model positions have smooth and simple local shapes and complex and variable local shapes. When performing cutting, the complex and variable local shapes should be focused on because the cutting results may differ from the impeller design model due to unreasonable control of the cutting tool. Therefore, by calculating the optimization weights of the tool points corresponding to each column in each valid interpolation matrix, screening out the tool points located in the complex local parts of the model, and focusing on these tool points during interpolation, a better interpolation result can be obtained and the impeller machining effect can be improved. The flowchart of the steps for obtaining the optimization weights of the tool points for each column in each valid interpolation matrix provided by the embodiments of the present application is as Figure 2 shown, specifically as follows:

[0099] Denote the coordinates of the point on the impeller model surface that is closest to the mapping point corresponding to the m-th interpolated tool point as the model corresponding point cloud of the m-th interpolated tool point;

[0100] It should be noted that when calculating the shortest distance from the mapping point corresponding to the m-th interpolated tool point to the impeller model surface, there is a point on the impeller model surface that is closest to the mapping point. Denote the coordinates of the corresponding point on the impeller model surface as the model corresponding point cloud of the m-th interpolated tool point; the more the model corresponding point cloud is located at the local complexity of the impeller model, the greater the optimization weight of the m-th interpolated tool point should be.

[0101] Obtain the point cloud data of each point on the impeller model surface, and use the normal vector estimation algorithm based on local plane fitting to calculate the normal vectors of the point cloud data;

[0102] It should be noted that take the coordinates of each tool point on the surface of the three-dimensional structure impeller model in the space coordinate system as the point cloud data of each point on the impeller model surface.

[0103] It should be noted that the normal vector estimation algorithm based on local plane fitting is a well-known technology and will not be elaborated here. Among them, the normal vector reflects the direction information of the position where each point cloud data is located on the impeller model.

[0104] Denote the preset first number of point cloud data and the preset second number of point cloud data on the impeller model surface that are closest to the model corresponding point cloud as the small-range point cloud set and the large-range point cloud set corresponding to each interpolated tool point, respectively;

[0105] In this embodiment, denote the 10 point cloud data and the 50 point cloud data on the impeller model surface that are closest to the model corresponding point cloud as the small-range point cloud set and the large-range point cloud set corresponding to each interpolated tool point, respectively. As other implementation manners, the implementer can set them according to the actual situation.

[0106] Calculate the sum vector of the normal vectors of all the point cloud data in the small range point cloud set, and form a small range vector by taking the ratio of each element in the sum vector to the number of all the point cloud data in the small range point cloud set;

[0107] Calculating the sum vector of the normal vectors of all point cloud data in the large-scale point cloud set, and forming a large-scale vector by taking the ratio of each element in the sum vector to the number of all point cloud data in the large-scale point cloud set;

[0108] The modulus length of the difference vector between the small range vector and the large range vector is used as the local complexity of the mth interpolation tool position;

[0109] It should be noted that the small-range vector reflects the directional information of the model corresponding point cloud of the m-th interpolation tool position within a smaller range, and the large-range vector reflects the directional information of the model corresponding point cloud of the m-th interpolation tool position within a larger range. The greater the local complexity, the greater the difference in directional information of the model corresponding point cloud of the same interpolation tool position in a smaller range and a larger range, indicating that the more drastic the change in the model surface direction at the model corresponding point cloud of the m-th interpolation tool position, the more likely the model corresponding point cloud of the m-th interpolation tool position is to be in the local complexity of the impeller model.

[0110] Normalizing the local complexity of the interpolation cutter position points corresponding to all columns in each valid interpolation matrix to serve as the cutter position point optimization weight of each column in each valid interpolation matrix;

[0111] In this embodiment, the process of normalizing the local complexity of the interpolation tool position points corresponding to all columns in each valid interpolation matrix is ​​as follows: calculating the cumulative sum of the local complexity of the interpolation tool position points corresponding to all columns in each valid interpolation matrix, and taking the ratio of the local complexity of the interpolation tool position points corresponding to each column in each valid interpolation matrix to the cumulative sum as the tool position point optimization weight of each column in each valid interpolation matrix.

[0112] It should be noted that the greater the tool position point optimization weight is, the more the interpolation tool position point of the corresponding column is located at a tool position point where the impeller model is locally complex. This position is more likely to reduce the cutting effect due to the change distance of the cutting tool speed or the mismatch between the cutting tool path and the impeller model. At this time, a better tool position point should be selected for interpolation to improve the overall processing level of the impeller model.

[0113] Furthermore, each effective interpolation matrix represents a processing scheme that can be executed by a five-axis machining machine. Based on the interpolation abnormality and the tool position point optimization weight, the interpolation adaptability is calculated, and the effective interpolation matrix that meets the constraint conditions is evaluated to screen the effective interpolation matrix so that it can control the cutting tool to perform better impeller processing, specifically:

[0114] The sum of the products of the tool point optimization weights of all columns in each valid interpolation matrix and the interpolation abnormality is used as the interpolation adaptability of each valid interpolation matrix;

[0115] It should be noted that the smaller the interpolation abnormality, the better the interpolation effect of the corresponding interpolation tool point. The smaller the interpolation adaptability of the entire valid interpolation matrix, the better the interpolation effect of each valid interpolation matrix; the larger the tool point optimization weight, it indicates that the interpolation tool point corresponding to the column is the tool point at the locally complex position of the impeller model, and the corresponding interpolation tool point is the tool point that needs to be focused on. The larger the interpolation adaptability, the greater the impact of each valid interpolation matrix on the final adaptability, and the worse the interpolation effect.

[0116] Thus, the interpolation adaptability of each valid interpolation matrix is obtained.

[0117] Step 6: Based on the interpolation adaptability, use an optimization algorithm to iterate the interpolation matrix to obtain the optimal interpolation matrix and machine the integral impeller.

[0118] Furthermore, based on the interpolation adaptability, use a genetic algorithm for optimization iteration to screen all valid interpolation matrices to screen out the interpolation matrices with good control effects. The specific iteration steps are as follows:

[0119] (1) Randomly generate A interpolation matrices, screen the A interpolation matrices to obtain all valid interpolation matrices; if the number of all valid interpolation matrices is less than A, continue to randomly generate interpolation matrices, and form an initial matrix set with the obtained A valid interpolation matrices;

[0120] In this embodiment, randomly generate A = 50 interpolation matrices. As other implementation manners, the implementer can set it by himself according to the actual situation;

[0121] (2) Calculate the interpolation adaptability of the A valid interpolation matrices in the initial matrix set, arrange them in ascending order, and select the B valid interpolation matrices corresponding to the top B interpolation adaptabilities to form an elite matrix set;

[0122] In this embodiment, select the B = 5 valid interpolation matrices corresponding to the top B interpolation adaptabilities to form an elite matrix set. As other implementation manners, the implementer can set it by himself according to the actual situation;

[0123] (3) Connect the head and tail of the row vectors of all rows in each valid interpolation matrix in the elite matrix set in row order to form each elite vector;

[0124] It should be noted that for the convenience of understanding, the effective interpolation matrix is scaled from 5 rows and 10 columns to 2 rows and 3 columns. Assume the scaled effective interpolation matrix is , then the corresponding elite vector is .

[0125] (4) Cross and mutate the elite vectors of the B effective interpolation matrices in the elite matrix set to obtain A new vectors. Divide all the elements in each new vector into 5 row vectors of equal length, and form a new interpolation matrix with the 5 row vectors of equal length to obtain A new interpolation matrices; Screen the A new interpolation matrices to obtain all new effective interpolation matrices; If the number of all new effective interpolation matrices is less than A, continue to cross and mutate the B elite vectors to generate new vectors, construct new interpolation matrices, and form a new matrix set with the obtained A new effective interpolation matrices;

[0126] In this embodiment, cross and mutate are well-known techniques in genetic algorithms and will not be elaborated here; When performing cross and mutate, set the crossover rate to 0.1 and the mutation rate to 0.05. As other implementation manners, the implementer can set them according to the actual situation.

[0127] (5) Repeat steps (2) to (4). After iterating N times, stop the iteration. Take the effective interpolation matrix with the minimum interpolation adaptability in the finally obtained matrix set as the best interpolation matrix output by the genetic algorithm.

[0128] In this embodiment, stop the iteration after iterating 50 times. As other implementation manners, the implementer can set it according to the actual situation.

[0129] It should be noted that the best interpolation matrix contains M columns, indicating that M tool positions are inserted between the starting tool position and the ending tool position. Therefore, input the best interpolation matrix into the five-axis machining tool numerical control system, and make the five-axis machine tool move the cutting tool according to the tool positions described in the best interpolation matrix, completing the interpolation of the five-axis machining tool.

[0130] Among them, when obtaining the best interpolation matrix, the speed change situation of the interpolation matrix when controlling the cutting tool, the fitting degree with the impeller model, and the complexity of the model positions where different interpolation tool positions are located are analyzed, and the interpolation matrix that fits the model and controls the speed smoothly is selected as the control scheme. Compared with the control scheme obtained by curve fitting in the traditional method, it can effectively avoid the cutting tool jitter caused by the uneven change of the cutting tool control speed, avoid the roughness of the impeller surface caused by the cutting tool jitter, and improve the machining quality of the integral impeller.

[0131] The embodiment of the present application further provides an integral impeller processing device based on a five-axis machining center. A computer program is stored in the device, and when the computer program is executed by a processor, the steps of any one of the above-mentioned methods of the integral impeller processing method based on a five-axis machining center are implemented.

[0132] Based on the same inventive concept as the above method, the embodiment of the present application further provides an integral impeller processing equipment based on a five-axis machining center, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of any one of the above-mentioned methods of the integral impeller processing method based on a five-axis machining center are implemented.

[0133] It should be understood that although Figure 1 the steps in the flowchart of Figure 1 are shown in sequence according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover,

[0134] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0135] The above-described embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several deformations and improvements can still be made. Therefore, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present application without departing from the content of the technical solution of the present application all belong to the protection scope of the technical solution of the present application.

Claims

1. An integral impeller machining method based on a five-axis machining center, characterized in that, the method comprises the following steps: Obtain the tool position data of the starting tool position point and the ending tool position point of the interpolation path segment according to the geometric characteristics of the impeller model, as well as the time interval between the starting tool position point and the ending tool position point; Randomly generate a plurality of multi-dimensional matrices, denoted as each interpolation matrix, wherein each column vector in the interpolation matrix corresponds to an interpolation tool position point; use the tool position data of the starting tool position point and the ending tool position point, and each interpolation matrix to construct a judgment matrix corresponding to each interpolation matrix; based on the time interval, analyze the change rate between adjacent elements in each row of the judgment matrix, and obtain each effective interpolation matrix; Analyze the change rate of each column element in each row of the judgment matrix corresponding to each effective interpolation matrix, and the average level of the change rate of all row elements in each column of the judgment matrix, to obtain the overall non-smoothness of each column in each effective interpolation matrix; Analyze the distance from the interpolation tool position point corresponding to each column in each effective interpolation matrix to the surface of the impeller model, and the movement duration required for the interpolation tool position points corresponding to adjacent two columns, and combine the overall non-smoothness to determine the interpolation abnormality of each column in each effective interpolation matrix; According to the difference situation between the normal vectors of all tool position points in different local regions at the tool position point on the impeller model surface that is closest to the interpolation tool position point corresponding to each column in each effective interpolation matrix, determine the tool position point optimization weight of each column in each effective interpolation matrix; combine the interpolation abnormality to determine the interpolation adaptability of each effective interpolation matrix; Based on the interpolation adaptability, iterate the interpolation matrix using an optimization algorithm to obtain the best interpolation matrix, and machine the integral impeller.

2. The integral impeller machining method based on a five-axis machining center according to claim 1, characterized in that, the construction method of the judgment matrix corresponding to each interpolation matrix is: Arrange in the order of the tool position data of the starting tool position point, each column vector in each interpolation matrix, and the tool position data of the ending tool position point to form the judgment matrix corresponding to each interpolation matrix.

3. The integral impeller machining method based on a five-axis machining center according to claim 1, characterized in that, the obtaining of each effective interpolation matrix includes: Based on the time interval between the starting tool position point and the ending tool position point, and the number of columns of the judgment matrix, calculate the interpolation time of each column in the judgment matrix; Obtain the preset maximum limit speed of each degree of freedom through the numerical control system of the five-axis machining tool, wherein each row in the judgment matrix represents a degree of freedom; Based on the interval duration between the interpolation times of adjacent two columns in the judgment matrix, calculate the change rate between each column element in any row of the judgment matrix and its previous column element and its next column element respectively, and denote it as the forward speed and backward speed of each column element in the any row; If the forward speed and backward speed of all column elements in all rows of the judgment matrix are less than or equal to the preset maximum limit speed of the degree of freedom corresponding to the row where the element is located, the interpolation matrix corresponding to the judgment matrix is denoted as an effective interpolation matrix.

4. The integral impeller machining method based on a five-axis machining center according to claim 3, It is characterized in that The interpolation time of the th column in the judgment matrix is calculated as follows: , where is the th column in the judgment matrix, is the time interval between the starting tool position and the ending tool position, is the number of all columns in the judgment matrix.

5. The monolithic impeller machining method based on a five-axis machining center as described in claim 4, It is characterized in that The obtaining of the overall non-smoothness of each column in each effective interpolation matrix includes: Normalize all column elements in each row of the judgment matrix corresponding to each effective interpolation matrix, and denote it as the normalized judgment matrix; The velocity non-smoothness of the element corresponding to the th row and th column in the normalized judgment matrix is calculated as follows: , , where is the overall velocity of the element corresponding to the th row and th column in the normalized judgment matrix, is the overall velocity of the element corresponding to the th row and th column in the normalized judgment matrix, is the interpolation time of the th column in the normalized judgment matrix, is the interpolation time of the th column in the normalized judgment matrix, is the total number of columns in the normalized judgment matrix; is the element value corresponding to the th row and th column in the normalized judgment matrix, is the element value corresponding to the th row and th column in the normalized judgment matrix; Take the mean value of the velocity non-smoothness of the corresponding elements in all rows within the same column in the normalized judgment matrix as the overall non-smoothness of each column in the normalized judgment matrix. Among them, the 2nd column to the (R - 1)th column in the normalized judgment matrix are effective interpolation matrices, and the overall non-smoothness of each column in each effective interpolation matrix is obtained.

6. The monolithic impeller machining method based on a five-axis machining center as described in claim 3, It is characterized in that The determination of the interpolation abnormality of each column in each effective interpolation matrix includes: Input the column vectors in each effective interpolation matrix into the numerical control system of the five-axis machining machine tool, obtain the mapping points of the interpolation tool positions corresponding to each column in each effective interpolation matrix in the three-dimensional space where the impeller model is located, and calculate the shortest distance from the mapping point to the surface of the impeller model, denoted as the relative distance; Obtain the preset maximum feed rate through the numerical control system of the five-axis machining machine tool, calculate the ratio of the relative distance to the interval duration, denoted as the relative speed, and take the ratio of the relative speed to the preset maximum feed rate as the model fitting degree of each column in each effective interpolation matrix; The interpolation abnormality is the product of the model fitting degree and the overall non-smoothness.

7. The monolithic impeller machining method based on a five-axis machining center as described in claim 1, It is characterized in that The determination of the tool position optimization weight of each column in each effective interpolation matrix includes: Denote the coordinates of the point on the surface of the impeller model that is closest to the interpolation tool position corresponding to each column in each effective interpolation matrix as the corresponding point cloud of each model; Obtain the point cloud data on the surface of the impeller model, and use the normal vector estimation algorithm based on local plane fitting to calculate the normal vectors of the point cloud data; Denote the preset first number of point cloud data and the preset second number of point cloud data that are closest to the corresponding point cloud of the model on the surface of the impeller model as the small-range point cloud set and the large-range point cloud set corresponding to each interpolation tool position respectively; Calculate the sum vector of the normal vectors of all point cloud data in the small-range point cloud set, and form a small-range vector by taking the ratio of each element in the sum vector to the number of all point cloud data in the small-range point cloud set; correspondingly, obtain a large-range vector for all point cloud data in the large-range point cloud set; Take the modulus of the difference vector between the small-range vector and the large-range vector as the local complexity of the interpolation tool position corresponding to each column in each effective interpolation matrix; normalize the local complexity of the interpolation tool positions corresponding to all columns in each effective interpolation matrix as the tool position optimization weight of each column in each effective interpolation matrix.

8. The monolithic impeller machining method based on a five-axis machining center as described in claim 1, It is characterized in that The interpolation adaptability is the sum value of the products of the tool position optimization weights of all columns in each effective interpolation matrix and the interpolation abnormality.

9. An integral impeller machining device based on a five-axis machining center, characterized in that, a computer program is stored in the device, and characterized in that when the computer program is executed by a processor, the steps of the integral impeller machining method based on a five-axis machining center according to any one of claims 1-8 are implemented.

10. An integral impeller machining equipment based on a five-axis machining center, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, when the processor executes the computer program, the steps of the integral impeller machining method based on a five-axis machining center according to any one of claims 1-8 are implemented.

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