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

Abstract

The invention relates to the technical field of machining, in particular to an integral impeller machining method, device and equipment based on a five-axis machining center, and the method comprises the steps: obtaining cutter location data of a starting cutter location point and an ending cutter location point of an interpolation path section according to geometric features of an impeller model, the time interval between the starting cutter location point and the ending cutter location point is determined; randomly generating a plurality of interpolation matrixes, and constructing a judgment matrix corresponding to each interpolation matrix; obtaining each effective interpolation matrix; the overall non-smoothness, the interpolation anomaly, the cutter location point optimization weight and the interpolation self-adaption degree of each column in each effective interpolation matrix are obtained; iteration is conducted on the interpolation matrix through an optimization algorithm, an optimal interpolation matrix is obtained, and the integral impeller is machined. According to the machining method, the change speed of the cutting tool in the machining process can be smooth, shaking of the cutting tool is effectively reduced, and the machining quality of the integral impeller is improved.

Description

Technical Field

[0001] The present application relates to the field of mechanical processing technology, and in particular to an integral impeller processing method, device and equipment based on a five-axis machining center. Background Art

[0002] The five-axis machining center is a CNC machine tool with five degrees of freedom that can process complex industrial parts. Integral impeller parts are complex and have high requirements for surface smoothness, so they are usually made using five-axis machining. When machining integral impellers with five axes, it is necessary to first obtain the geometric model of the target impeller, then plan the tool path based on the geometric model, and generate tool position information to control the five-axis CNC machine tool for cutting. When the five-axis CNC machine tool uses the tool position information for cutting, it is necessary to perform path interpolation based on the tool position information to make the tool path smooth and reduce the error between the finished impeller and the impeller model.

[0003] Traditional methods usually use a curve fitting algorithm to calculate the tool position point when performing path interpolation based on the tool position point information, insert a new tool position point on the fitting curve between two tool position points to complete the path interpolation and obtain the control path of the cutting tool. Among them, since the tool position point interpolation process does not take into account whether the movement speed of each degree of freedom is smooth, when the cutting tool moves along the obtained control path, some degrees of freedom may experience drastic speed changes, which in turn leads to increased jitter of the cutting tool during the cutting process, resulting in reduced surface smoothness of the impeller, affecting the processing quality of the integral impeller. Summary of the invention

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

[0005] The solution to the technical problem of this application is to provide an integral impeller machining method, device and equipment based on a five-axis machining center, including the following steps: In a first aspect, an embodiment of the present application provides an integral impeller machining method based on a five-axis machining center, the method comprising the following steps: According to the geometric features of the impeller model, tool position data of the starting tool position and the ending tool position of the interpolation path segment, as well as the time interval between the starting tool position and the ending tool position are obtained; A plurality of multidimensional matrices are randomly generated, each of which is recorded as an interpolation matrix, wherein each column vector in the interpolation matrix corresponds to an interpolation tool position; a judgment matrix corresponding to each interpolation matrix is ​​constructed using tool position data of a starting tool position and an ending tool position, and each interpolation matrix; based on the time interval, a change rate between adjacent elements in each row of the judgment matrix is ​​analyzed to obtain each valid interpolation matrix; Analyze the change rate of each column element in each row of the judgment matrix corresponding to each valid interpolation matrix, as well as the average level of the change rate of all row elements in each column of the judgment matrix, and obtain the overall non-smoothness of each column in each valid interpolation matrix; Analyze the distance between the interpolation tool position corresponding to each column in each valid interpolation matrix and the surface of the impeller model, as well as the movement time required for the interpolation tool positions corresponding to two adjacent columns, and determine the interpolation abnormality of each column in each valid interpolation matrix in combination with the overall non-smoothness; According to the difference between the normal vectors of all the tool positions in the local area of ​​different ranges at the tool position closest to the interpolation tool position corresponding to each column in each effective interpolation matrix on the impeller model surface, the tool position optimization weight of each column in each effective interpolation matrix is ​​determined; in combination with the interpolation abnormality, the interpolation adaptability of each effective interpolation matrix is ​​determined; Based on the interpolation adaptability, the interpolation matrix is ​​iterated using an optimization algorithm to obtain the best interpolation matrix, and the integral impeller is processed.

[0006] Preferably, the step of determining a judgment matrix corresponding to each interpolation matrix includes: The tool position data of the starting tool position point, the column vectors in each interpolation matrix, and the tool position data of the ending tool position point are arranged in order to form a judgment matrix corresponding to each interpolation matrix.

[0007] Preferably, the obtaining of each valid 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, the interpolation time of each column in the judgment matrix is ​​calculated; Obtaining a preset maximum limit speed for each degree of freedom through a five-axis machining center numerical control system, wherein each row in the judgment matrix represents one degree of freedom; Based on the interval between the interpolation moments of two adjacent columns in the judgment matrix, respectively calculate the change rate between each column element in any row of the judgment matrix and its previous column element and next column element, and record them as the forward speed and backward speed of each column element in any row; If the forward speed and backward speed of all column elements of all rows in the judgment matrix are less than or equal to the preset maximum speed limit of the degree of freedom corresponding to the row corresponding to the element, the interpolation matrix corresponding to the judgment matrix is ​​recorded as a valid interpolation matrix.

[0008] Preferably, the first Interpolation moment of the column The calculation formula is: ,in, is the first List, is the time interval between the starting knife point and the ending knife point, is the number of all columns in the judgment matrix.

[0009] Preferably, obtaining the overall non-smoothness of each column in each valid interpolation matrix includes: Normalize all column elements of each row in the judgment matrix corresponding to each valid interpolation matrix, and record it as the normalized judgment matrix; The normalized judgment matrix Line The velocity non-smoothness of the corresponding element of the column The calculation formula is: , ,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 moment 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; 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 to R-1th columns in the normalized judgment matrix are valid interpolation matrices, and the overall non-smoothness of each column in each valid interpolation matrix is ​​obtained.

[0010] Preferably, determining the interpolation abnormality of each column in each valid interpolation matrix includes: Input each column vector in each effective interpolation matrix into the CNC system of the five-axis machining center, obtain the mapping point of the interpolation tool position corresponding to each column in each effective interpolation matrix in the three-dimensional space where the impeller model is located, calculate the shortest distance from the mapping point to the surface of the impeller model, and record it as the relative distance; Obtaining a preset maximum feed amount through a five-axis machining center numerical control system, calculating a ratio of the relative distance to the interval time, recording it as a relative speed, and using the ratio of the relative speed to the preset maximum feed amount as a model fit of each column in each effective interpolation matrix; The interpolation abnormality is the product of the model fit and the overall non-smoothness.

[0011] Preferably, the step of determining the optimized weight of the tool position points of each column in each effective interpolation matrix comprises: The coordinates of the points on the impeller model surface that are closest to the interpolation tool positions corresponding to each column in each valid interpolation matrix are recorded as the corresponding point clouds of each model; Obtain each point cloud data on the surface of the impeller model, and use a normal estimation algorithm based on local plane fitting to calculate the normal vector of each point cloud data; Recording a preset first number of point cloud data and a preset second number of point cloud data on the surface of the impeller model that are closest to the corresponding point cloud of the model as a small-range point cloud set and a large-range point cloud set corresponding to each interpolation tool position point, respectively; 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 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; accordingly, obtain a large range vector for all the point cloud data in the large range point cloud set; The modulus of the difference vector between the small-range vector and the large-range vector is used as the local complexity of the interpolation tool position points corresponding to each column in each valid interpolation matrix; the local complexity of the interpolation tool position points corresponding to all columns in each valid interpolation matrix is ​​normalized as the tool position point optimization weight of each column in each valid interpolation matrix.

[0012] Preferably, the interpolation adaptability is the sum of the products of the tool position optimization weights of all columns in each effective interpolation matrix and the interpolation abnormality.

[0013] In a second aspect, an embodiment of the present application further provides an integrated impeller processing device based on a five-axis machining center, wherein 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 integrated impeller processing methods based on a five-axis machining center are implemented.

[0014] In the third aspect, an embodiment of the present application also provides an integrated impeller processing device 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, and when the processor executes the computer program, it implements any one of the steps of the above-mentioned integrated impeller processing method based on a five-axis machining center.

[0015] This application has at least the following beneficial effects: The present application constructs an interpolation matrix in the interpolation path between the starting tool position point and the ending tool position point, forms a tool trajectory plan according to the starting tool position point, the interpolation matrix, and the ending tool position point, constructs a judgment matrix, analyzes whether the change rate between adjacent column elements in the same row in the judgment matrix meets the preset constraint conditions, screens the interpolation matrix, obtains each valid interpolation matrix, and forms a cutting tool control scheme executable by the five-axis machine tool; secondly, calculates the overall non-smoothness of each column in each valid interpolation matrix, and its beneficial effect is that it takes into account the corresponding non-smoothness of different columns in the valid interpolation matrix. The smoothness of the cutting speed of the interpolation tool position is used to reflect the influence of the cutting speed of the interpolation tool position on the cutting speed of the whole cutting process, so as to facilitate the subsequent screening of the effective interpolation matrix with smooth cutting tool speed change; the model fitting degree of each column in each effective interpolation matrix is ​​calculated, and the interpolation abnormality of each column in each effective interpolation matrix is ​​calculated. The beneficial effect is that the interpolation tool position corresponding to different columns in the effective interpolation matrix is ​​taken into account. The degree of fit with the impeller model is considered, which is convenient for the subsequent screening of the effective interpolation matrix that fits closely with the impeller model, and can evaluate the model fitting degree of each column in the effective interpolation matrix. The interpolation effect of the interpolation tool position is conducive to the subsequent screening of an effective interpolation matrix that can ensure smooth changes in the cutting tool speed and that the corresponding interpolation tool position fits the impeller model; the optimization weights of the tool position positions in each column of each effective interpolation matrix are calculated. The beneficial effect is that the complex situation of the position of the impeller model where the interpolation tool positions in each column of the effective interpolation matrix are located is taken into account, and a higher weight is given to the interpolation tool position positions in the complex local position, which helps to improve the control effect of the effective interpolation matrix in the complex part of the impeller model and improve the overall effect of the interpolation result; determine each The interpolation adaptability of the effective interpolation matrix is ​​used to iterate the interpolation matrix using an optimization algorithm to obtain the optimal interpolation matrix and process the integral impeller. The beneficial effect is that an effective interpolation matrix is ​​obtained through continuous iteration, and the optimal interpolation matrix is ​​selected according to the interpolation adaptability, so that the speed of the cutting tool changes more slowly and fits the impeller model more closely, so that the interpolation result of the cutting tool is optimal. Compared with the traditional method, the speed of the cutting tool can change more smoothly during the processing, effectively reducing the jitter of the cutting tool, improving the smoothness of the impeller surface, and improving the processing quality of the integral impeller. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The integrated impeller machining method based on a five-axis machining center of the present application is further described in detail below in conjunction with the accompanying drawings.

[0017] Figure 1 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; Figure 2 A flowchart of the steps of a method for obtaining the optimized weights of the tool position points of each column in each valid interpolation matrix provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the following is a further detailed description of the integrated impeller processing method, device and equipment based on a five-axis machining center proposed in the present application in conjunction with the accompanying drawings and implementation examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0019] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0020] See also Figure 1 , which shows a flowchart of a method for machining an integral impeller based on a five-axis machining center provided by an embodiment of the present application, the method comprising the following steps: Step 1: acquiring tool position data of a starting tool position point and an ending tool position point of an interpolation path segment and a time interval between the starting tool position point and the ending tool position point according to the geometric features of the impeller model.

[0021] Compared with three-axis CNC machine tools, five-axis CNC machine tools have two more rotating axes, which can give the tool more processing freedom, increase the flexibility of the tool cutting position and angle when processing complex curved parts, reduce the number of tool changes and part re-clamping times, and further improve the processing accuracy of complex curved parts.

[0022] When the five-axis machining center processes the impeller, the geometric information of the impeller will be converted into tool position information. Therefore, according to the three-dimensional geometric model of the impeller, the motion trajectory of the tool position is determined, and the tool position data of all tool positions are obtained. Any two adjacent tool positions are selected as the starting tool position and the ending tool position of the interpolation path segment, and multiple tool positions are interpolated between the starting tool position and the ending tool position.

[0023] It should be noted that The tool position data of a tool position is in the form of , where the first three elements Indicates The position coordinates of the tool position points, the last two elements Indicates The two rotation axis angles corresponding to the tool position data reflect the When the tool position is measured, the position of the cutting tool and the posture of the impeller.

[0024] At the same time, the time interval T between the starting tool position and the ending tool position is obtained through the CNC system of the five-axis machining machine tool, which represents the time taken by the CNC machine tool to control the cutting tool from the starting tool position to the ending tool position.

[0025] At this point, 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.

[0026] Step 2, randomly generate multiple multidimensional matrices, recorded as each interpolation matrix, wherein each column vector in the interpolation matrix corresponds to an interpolation tool position; use the tool position data of the starting tool position and the ending tool position, 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 valid interpolation matrix.

[0027] The cutting tool motion path between the starting tool position and the ending tool position is optimized by genetic algorithm to obtain a cutting tool motion path that fits the impeller model and has smooth speed changes of various parameters in the tool position data. Therefore, by constructing an interpolation matrix and setting constraints on the interpolation matrix, the interpolation matrix becomes a processing plan that can be executed by a five-axis machining machine.

[0028] Randomly generate a plurality of multi-dimensional matrices, which are recorded as each interpolation matrix, wherein the mth column vector in the interpolation matrix is ​​recorded as the tool position data of the mth interpolation tool position point; It should be noted that, since the tool position data is a 5-dimensional vector, the interpolation matrix is ​​a matrix of 5 rows and M columns. In this embodiment, the value of M is 10. As for other implementations, the implementer can set it according to the actual situation. The interpolation matrix contains M columns in total, indicating that M tool positions are interpolated between the starting tool position point and the ending tool position point. The column vector represents the interpolated Tool location data for each tool location.

[0029] Construct a judgment matrix corresponding to each interpolation matrix, wherein the tool position data of the starting tool position is used as the first column of the judgment matrix; the tool position data of all interpolation tool positions in each interpolation matrix are used as the second to the M+1 columns of the judgment matrix; and the tool position data of the ending tool position is used as the M+2 column of the judgment matrix; Therefore, based on the time interval between the starting knife position and the ending knife position, the first Interpolation moment of the column The calculation formula is: ,in, is the first List, is the time interval between the starting knife point and the ending knife point, is the number of all columns in the judgment matrix; Then the interval between the interpolation moments of two adjacent columns in the judgment matrix is .

[0030] Calculate the interval length between two adjacent columns in the judgment matrix, and calculate the interval length between any two columns in the judgment matrix; In this embodiment, the time when the cutting tool is at the starting tool position is recorded as time 0, and the time when the cutting tool is at the ending tool position is recorded as time T. Then the interpolation tool position corresponding to the mth column in the judgment matrix represents the time when the cutting tool is at the end tool position. When the five-axis machining center executes the cutting plan of the interpolation matrix, it controls the cutting tool and the impeller in the first Just make the gesture of the mth interpolation tool position at all times.

[0031] It should be noted that the interval between any two columns in the judgment matrix reflects the time required for the cutting tool of the five-axis machining center to move from one interpolation tool position to the next interpolation tool position between the interpolation tool positions corresponding to two adjacent columns.

[0032] Obtaining a preset maximum speed limit for each degree of freedom through a five-axis machining center numerical control system, wherein each row in the judgment matrix represents a degree of freedom; In this embodiment, the tool position data is in the form of , the corresponding 5 degrees of freedom are X, Y, Z, A, and C. The preset maximum limit speed corresponding to the X-axis is 800mm / min, the preset maximum limit speed corresponding to the Y-axis is 800mm / min, the preset maximum limit speed corresponding to the Z-axis is 800mm / 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 methods, the implementer can set them according to actual conditions.

[0033] It should be noted that the preset maximum speed limit reflects the maximum movement speed that each axis of the five-axis machining center can reach under normal operating conditions.

[0034] Furthermore, constraints are constructed for the elements in the 2nd to M+1th columns of the judgment matrix, and the interpolation matrix is ​​screened to evaluate whether the interpolation scheme of the interpolation matrix can be executed by the five-axis machine tool, specifically: Based on the interval between the interpolation moments of two adjacent columns in the judgment matrix, the change rate between the elements of each column in any row in the judgment matrix and the elements of the previous column is calculated, which is recorded as the forward speed of the elements of each column in any row; the change rate between the elements of each column in any row and the elements of the next column is calculated, which is recorded as the backward speed of the elements of each column in any row; In this embodiment, the first Line The forward and backward velocities of the corresponding elements in the column are calculated as follows: ,in, is the first Line The forward velocity of the corresponding element in the column, is the first Line The element value corresponding to the column, is the first Line The element value corresponding to the column, is the first Column and The length of the interval between the interpolation moments of the columns; ,in, is the first Line The backward velocity of the corresponding element in the column, is the first Line The element value corresponding to the column, is the first Line The element value corresponding to the column, is the first Column and The length of the interval between the interpolation moments of the columns; It should be noted that the forward speed reflects the The knife point to the During the movement of the knife point The backward velocity reflects the average velocity of the corresponding degree of freedom. The knife point to the During the movement of the knife point The average velocity of the corresponding degree of freedom.

[0035] For all elements from the 2nd column to the M+1th column in the judgment matrix, if the forward speed and the backward speed of all column elements of all rows in the judgment matrix are less than or equal to the preset maximum speed limit of the degree of freedom corresponding to the row corresponding to the element, the interpolation matrix corresponding to the judgment matrix is ​​recorded as a valid interpolation matrix; It should be noted that the effective interpolation matrix refers to the interpolation matrix that meets the constraint conditions and represents a processing solution that can be adopted by the five-axis machine tool.

[0036] So far, all valid interpolation matrices are obtained.

[0037] Step 3: Analyze the change rate of each column element in each row of the judgment matrix corresponding to each valid interpolation matrix, as well as 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 valid interpolation matrix.

[0038] Multiple interpolation matrices are randomly generated, and a genetic algorithm is used to select the interpolation matrix with a smooth speed change and fit to the impeller surface as the processing solution for the five-axis machine tool. The row represents the The position of the cutting tool control device with a degree of freedom is changed. In order to avoid the cutting tool in the first The speed change on each degree of freedom is too fast, which causes the cutting tool to shake and reduces the impeller processing quality. Therefore, for the effective interpolation matrix that meets the constraints, the speed non-smoothness is calculated to evaluate the rapidity of the change of different degrees of freedom of the effective interpolation matrix that meets the constraints, and then screen out the effective interpolation matrix that can control the smooth movement of the cutting tool, specifically: Normalize all column elements of each row in the judgment matrix corresponding to each valid interpolation matrix, and record it as the normalized judgment matrix; In this embodiment, the normalization process is as follows: for each valid interpolation matrix corresponding to the judgment matrix The row vector of rows, calculate the The elements of each column of the row and The ratio of the preset maximum speed limit of the corresponding degree of freedom is All the ratios of the rows make up the The normalized vectors of the rows form a normalized judgment matrix with the normalized vectors of all rows, wherein the number of columns of the normalized judgment matrix is ​​R=M+2.

[0039] Calculate the normalized judgment matrix Line The velocity non-smoothness of the corresponding element of the column The calculation formula is: 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.

[0040] 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.

[0041] 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; 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 of the corresponding column is, the more it can reduce the cutting tool jitter caused by the speed mutation, and improve the impeller processing quality; secondly, the judgment matrix obtains a total of R=M+2 overall non-smoothnesses, among which the overall non-smoothnesses of the 2nd to S-1th columns are the overall non-smoothnesses of the interpolation tool positions corresponding to each column in the effective interpolation matrix, and the overall smoothnesses of the 1st and Sth columns are the overall non-smoothnesses of the starting tool position and the ending tool position.

[0042] So far, the overall non-smoothness of each column in each valid interpolation matrix is ​​obtained.

[0043] Step 4: Analyze the distance from the interpolation tool position corresponding to each column in each valid interpolation matrix to the impeller model surface, as well as the movement time required for the interpolation tool position corresponding to two adjacent columns, and determine the interpolation abnormality of each column in each valid interpolation matrix in combination with the overall non-smoothness.

[0044] Furthermore, the distance between the cutting position of the interpolation tool position corresponding to each column in the effective interpolation matrix and the surface of the impeller model is analyzed to evaluate the situation where the actual cutting effect caused by the cutting result of the interpolation tool position does not conform to the impeller model. By calculating the model fitting degree, the degree of fit between the interpolation tool position corresponding to each column of the effective interpolation matrix and the surface of the impeller model is judged. To judge the degree of fit between the interpolation tool position and the impeller model, the tool position data of the interpolation tool position needs to be mapped to the coordinate system of the impeller model for comparison, specifically: The mth column vector in each valid interpolation matrix is ​​input into the CNC system of the five-axis machining center, the mapping point of the interpolation tool position corresponding to the mth column in the three-dimensional space where the impeller model is located is obtained, and the shortest distance from the mapping point to the surface of the impeller model is calculated, which is recorded as the relative distance of the interpolation tool position corresponding to the mth column; In this embodiment, the closest Euclidean distance from the mapping point to the surface of the impeller model is calculated, wherein the calculation of the Euclidean distance is a well-known technique and will not be described in detail herein.

[0045] It should be noted that the smaller the relative distance is, the more the tool position data of the interpolation tool position corresponding to the mth column fits the impeller model more closely.

[0046] Obtaining a preset maximum feed amount through a five-axis machining center numerical control system, calculating a ratio of the relative distance to the interval time between the interpolation moments of two adjacent columns in the effective interpolation matrix, recording the ratio as a relative speed, and taking the ratio of the relative speed to the preset maximum feed amount as the model fitting degree of the mth column in each effective interpolation matrix; In this embodiment, the preset maximum feed rate is 23 mm / s. As for other implementations, the implementer can set it according to the actual situation.

[0047] It should be noted that the mth column in the effective interpolation matrix corresponds to the mth interpolation tool position point. The relative speed reflects the rate of change of the distance between the mapping point corresponding to the mth 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 amount, it means that the deviation of the mapping point has been close to the maximum allowable range during the machining process, and the obtained model has a greater degree of fit. 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 deviates from the impeller model, the smaller the model fit is, and 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.

[0048] Furthermore, for the interpolation tool positions corresponding to each column in the effective interpolation matrix, when controlling the cutter to interpolate, it is necessary to ensure that the speed of the cutter changes smoothly to prevent the cutter from shaking, and to ensure that the interpolated tool positions fit the impeller model. If the speed of the cutter does not change smoothly enough, the cutter will shake at a high speed, and even if the tool position fits the impeller model, it will not achieve the corresponding cutting effect; similarly, even if the speed of the cutter changes smoothly, but the tool position does not fit the impeller model well, the speed smoothness will not achieve a good cutting effect.

[0049] Therefore, based on the model fitting degree and the overall non-smoothness, the interpolation abnormality is determined to reflect the interpolation effect of the interpolation tool position, specifically: The product of the model fit and the overall non-smoothness is used as the interpolation abnormality of each column in each valid interpolation matrix; It should be noted that the smaller the interpolation abnormality is, the smoother the change in cutting tool speed can be ensured when machining according to the interpolation tool positions corresponding to each column in the effective interpolation matrix, and the corresponding interpolation tool positions can be ensured to fit the impeller model, thereby obtaining a better impeller machining effect.

[0050] At this point, the interpolation abnormality of each column in each valid interpolation matrix is ​​obtained.

[0051] Step 5, according to the difference between the normal vectors of all tool positions in local areas of different ranges at the tool position closest to the interpolation tool position corresponding to each column in each valid interpolation matrix on the impeller model surface, determine the optimization weight of the tool position of each column in each valid interpolation matrix; combined with the interpolation abnormality, determine the interpolation adaptability of each valid interpolation matrix.

[0052] For each of the M columns of a valid interpolation matrix, there are M interpolation tool positions corresponding to different model positions of the impeller. The impeller model positions have smooth and simple local shapes and complex and changeable local shapes. When cutting, we should focus on the complex and changeable local shapes because these shapes are prone to cause the cutting results to be different from the impeller design model due to unreasonable control of the cutting tool. Therefore, by calculating the tool position optimization weights for the interpolation tool positions corresponding to each column in each valid interpolation matrix, we can screen out the tool positions in the complex local part of the model, and focus on these tool positions when interpolating to obtain better interpolation results and improve the impeller processing effect. The step flow chart of the method for obtaining the tool position optimization weights for each column in each valid interpolation matrix provided in the embodiment of the present application is shown in the following figure. Figure 2 As shown, specifically: The coordinates of the point on the impeller model surface that is closest to the mapping point corresponding to the m-th interpolation tool position are recorded as the model corresponding point cloud of the m-th interpolation tool position; It should be noted that when calculating the shortest distance from the mapping point corresponding to the m-th interpolation tool position to the impeller model surface, there is a point on the impeller model surface that is shortest to the mapping point. The coordinates of the corresponding point on the impeller model surface are recorded as the model corresponding point cloud of the m-th interpolation tool position. The more complex the model corresponding point cloud is in the local area of ​​the impeller model, the greater the optimization weight of the m-th interpolation tool position should be.

[0053] Obtain each point cloud data on the surface of the impeller model, and use a normal estimation algorithm based on local plane fitting to calculate the normal vector of each point cloud data; It should be noted that the coordinates of each tool position point on the surface of the impeller model of the three-dimensional structure in the space coordinate system are used as each point cloud data on the surface of the impeller model.

[0054] It should be noted that the normal estimation algorithm based on local plane fitting is a well-known technology and will not be described in detail here. The normal vector reflects the direction information of the position of each point cloud data on the impeller model.

[0055] Recording a preset first number of point cloud data and a preset second number of point cloud data on the surface of the impeller model that are closest to the corresponding point cloud of the model as a small-range point cloud set and a large-range point cloud set corresponding to each interpolation tool position point, respectively; In this embodiment, the 10 point cloud data and 50 point cloud data on the surface of the impeller model that are closest to the corresponding point cloud of the model are recorded as the small-range point cloud set and the large-range point cloud set corresponding to each interpolation tool position, respectively. As other implementation methods, the implementer can set them according to the actual situation.

[0056] 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; Calculating the sum vector of the normal vectors of all the 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 the point cloud data in the large-scale point cloud set; 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; 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.

[0057] 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; 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.

[0058] 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.

[0059] 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: The sum of the products of the tool position optimization weights of all columns in each effective interpolation matrix and the interpolation abnormality degree is used as the interpolation adaptability of each effective interpolation matrix; It should be noted that the smaller the interpolation abnormality, the better the interpolation effect of the corresponding interpolation tool position, the smaller the interpolation adaptability of the entire effective interpolation matrix, and the better the interpolation effect of each effective interpolation matrix; the larger the tool position optimization weight, the more the interpolation tool position of the corresponding column is located in the local complex position of the impeller model, the more the corresponding interpolation tool position is the tool position that needs special attention, the greater the interpolation adaptability, the greater the influence of each effective interpolation matrix on the final adaptability, and the worse the interpolation effect.

[0060] At this point, the interpolation adaptability of each valid interpolation matrix is ​​obtained.

[0061] Step 6: Based on the interpolation adaptability, the interpolation matrix is ​​iterated using an optimization algorithm to obtain the best interpolation matrix and process the integral impeller.

[0062] Furthermore, based on the interpolation adaptability, a genetic algorithm is used to perform optimization iterations to screen all effective interpolation matrices to select interpolation matrices with good control effects. The specific iterative steps are: (1) Randomly generate A interpolation matrices, screen the A interpolation matrices, and obtain all valid interpolation matrices; if the number of all valid interpolation matrices is less than A, continue to randomly generate interpolation matrices, and the obtained A valid interpolation matrices form the initial matrix set; In this embodiment, A=50 interpolation matrices are randomly generated. As other implementation methods, the implementer can set them according to the actual situation. (2) Calculate the interpolation adaptability of the A valid interpolation matrices in the initial matrix set, arrange them in ascending order, and select the valid interpolation matrices corresponding to the top B interpolation adaptability to form an elite matrix set; In this embodiment, the effective interpolation matrices corresponding to the top B=5 interpolation adaptability are selected to form an elite matrix set. As other implementation methods, the implementer can set them according to the actual situation. (3) Connect the row vectors of all rows in each valid interpolation matrix in the elite matrix set head to tail in row order to form each elite vector; It should be noted that, for ease of understanding, the effective interpolation matrix is ​​scaled from 5 rows and 10 columns to 2 rows and 3 columns. Assume that the scaled effective interpolation matrix is , then the corresponding elite vector is .

[0063] (4) Perform crossover and mutation on the elite vectors of B valid interpolation matrices in the elite matrix set to obtain A new vectors, divide all 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 valid interpolation matrices; if the number of all new valid interpolation matrices is less than A, continue to perform crossover and mutation on the B elite vectors to generate new vectors, construct a new interpolation matrix, and form a new matrix set with the obtained A new valid interpolation matrices; In this embodiment, crossover and mutation are well-known techniques in genetic algorithms and will not be described in detail here. When performing crossover and mutation, the crossover rate is set to 0.1 and the mutation rate is set to 0.05. As other implementation methods, the implementer can set them according to actual conditions.

[0064] (5) Repeat steps (2) to (4) and stop iterating after N iterations. The effective interpolation matrix with the minimum interpolation adaptability in the matrix set is finally obtained as the optimal interpolation matrix output by the genetic algorithm.

[0065] In this embodiment, iteration stops after 50 iterations. As other implementation modes, implementers can set them according to actual conditions.

[0066] It should be noted that the optimal interpolation matrix contains M columns, indicating that M tool positions are inserted between the starting tool position point and the ending tool position point. Therefore, the optimal interpolation matrix is ​​input into the CNC system of the five-axis machining center, so that the five-axis machine tool moves the cutting tool according to the tool position points described in the optimal interpolation matrix, thereby completing the interpolation of the five-axis machining center.

[0067] Among them, when obtaining the optimal interpolation matrix, the speed change of the interpolation matrix when controlling the cutting tool, the degree of fit with the impeller model, and the complexity of the model position of different interpolation tool positions 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 by the traditional method, it can effectively avoid the cutting tool jitter caused by the uneven change of the cutting tool control speed, avoid the rough impeller surface caused by the cutting tool jitter, and improve the processing quality of the integral impeller.

[0068] An embodiment of the present application also provides an integrated impeller processing device based on a five-axis machining center, in which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the above-mentioned integrated impeller processing methods based on a five-axis machining center are implemented.

[0069] Based on the same inventive concept as the above method, an embodiment of the present application also provides an integrated impeller processing device 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, and when the processor executes the computer program, the steps of any one of the above-mentioned integrated impeller processing methods based on a five-axis machining center are implemented.

[0070] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0071] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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, they should be considered to be within the scope of this specification.

[0072] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the present application. It should be pointed out that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application without departing from the content of the technical solution of the present application, shall fall within 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: According to the geometric features of the impeller model, tool position data of the starting tool position and the ending tool position of the interpolation path segment, as well as the time interval between the starting tool position and the ending tool position are obtained; A plurality of multidimensional matrices are randomly generated, each of which is recorded as an interpolation matrix, wherein each column vector in the interpolation matrix corresponds to an interpolation tool position; a judgment matrix corresponding to each interpolation matrix is ​​constructed using tool position data of a starting tool position and an ending tool position, and each interpolation matrix; based on the time interval, a change rate between adjacent elements in each row of the judgment matrix is ​​analyzed to obtain each valid interpolation matrix; Analyze the change rate of each column element in each row of the judgment matrix corresponding to each valid interpolation matrix, as well as the average level of the change rate of all row elements in each column of the judgment matrix, and obtain the overall non-smoothness of each column in each valid interpolation matrix; Analyze the distance between the interpolation tool position corresponding to each column in each valid interpolation matrix and the surface of the impeller model, as well as the movement time required for the interpolation tool positions corresponding to two adjacent columns, and determine the interpolation abnormality of each column in each valid interpolation matrix in combination with the overall non-smoothness; According to the difference between the normal vectors of all the tool positions in the local area of ​​different ranges at the tool position closest to the interpolation tool position corresponding to each column in each effective interpolation matrix on the impeller model surface, the tool position optimization weight of each column in each effective interpolation matrix is ​​determined; in combination with the interpolation abnormality, the interpolation adaptability of each effective interpolation matrix is ​​determined; Based on the interpolation adaptability, the interpolation matrix is ​​iterated using an optimization algorithm to obtain the best interpolation matrix, and the integral impeller is processed.

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: The tool position data of the starting tool position point, the column vectors in each interpolation matrix, and the tool position data of the ending tool position point are arranged in order to form a 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 valid interpolation matrix comprises: 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, the interpolation time of each column in the judgment matrix is ​​calculated; Obtaining a preset maximum limit speed for each degree of freedom through a five-axis machining center numerical control system, wherein each row in the judgment matrix represents one degree of freedom; Based on the interval between the interpolation moments of two adjacent columns in the judgment matrix, respectively calculate the change rate between each column element in any row of the judgment matrix and its previous column element and next column element, and record them as the forward speed and backward speed of each column element in any row; If the forward speed and backward speed of all column elements of all rows in the judgment matrix are less than or equal to the preset maximum speed limit of the degree of freedom corresponding to the row corresponding to the element, the interpolation matrix corresponding to the judgment matrix is ​​recorded as a valid interpolation matrix.

4. The integral impeller machining method based on a five-axis machining center as claimed in claim 3, characterized in that: The judgment matrix Interpolation moment of the column The calculation formula is: ,in, is the first List, is the time interval between the starting knife point and the ending knife point, is the number of all columns in the judgment matrix.

5. The integral impeller machining method based on a five-axis machining center according to claim 4, characterized in that: The step of obtaining the overall non-smoothness of each column in each valid interpolation matrix comprises: Normalize all column elements of each row in the judgment matrix corresponding to each valid interpolation matrix, and record it as the normalized judgment matrix; The normalized judgment matrix Line The velocity non-smoothness of the corresponding elements of the column The calculation formula is: , ,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 moment 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; 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 to R-1th columns in the normalized judgment matrix are valid interpolation matrices, and the overall non-smoothness of each column in each valid interpolation matrix is ​​obtained.

6. The integral impeller machining method based on a five-axis machining center according to claim 3, characterized in that: Determining the interpolation abnormality of each column in each valid interpolation matrix includes: Input each column vector in each effective interpolation matrix into the CNC system of the five-axis machining center, obtain the mapping point of the interpolation tool position corresponding to each column in each effective interpolation matrix in the three-dimensional space where the impeller model is located, calculate the shortest distance from the mapping point to the surface of the impeller model, and record it as the relative distance; Obtaining a preset maximum feed amount through a five-axis machining center numerical control system, calculating a ratio of the relative distance to the interval time, recording it as a relative speed, and using the ratio of the relative speed to the preset maximum feed amount as a model fit of each column in each effective interpolation matrix; The interpolation abnormality is the product of the model fit and the overall non-smoothness.

7. The integral impeller machining method based on a five-axis machining center according to claim 1, characterized in that: The step of determining the tool position optimization weight of each column in each effective interpolation matrix comprises: The coordinates of the points on the impeller model surface that are closest to the interpolation tool positions corresponding to each column in each valid interpolation matrix are recorded as the corresponding point clouds of each model; Obtain each point cloud data on the surface of the impeller model, and use a normal estimation algorithm based on local plane fitting to calculate the normal vector of each point cloud data; Recording a preset first number of point cloud data and a preset second number of point cloud data on the surface of the impeller model that are closest to the corresponding point cloud of the model as a small-range point cloud set and a large-range point cloud set corresponding to each interpolation tool position point, respectively; 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 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; accordingly, obtain a large range vector for all the point cloud data in the large range point cloud set; The modulus of the difference vector between the small-range vector and the large-range vector is used as the local complexity of the interpolation tool position points corresponding to each column in each valid interpolation matrix; the local complexity of the interpolation tool position points corresponding to all columns in each valid interpolation matrix is ​​normalized as the tool position point optimization weight of each column in each valid interpolation matrix.

8. The integral impeller machining method based on a five-axis machining center according to claim 1, characterized in that: The interpolation adaptability is the sum of the products of the tool location point optimization weights of all columns in each effective interpolation matrix and the interpolation abnormality.

9. An integrated impeller processing device based on a five-axis machining center, characterized in that: The device stores a computer program, which is 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 as described in any one of claims 1 to 8 are implemented.

10. An integrated impeller processing device 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 as described in any one of claims 1 to 8 are implemented.

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