Prediction method for surface microtopography of internal meshing honing gear of cylindrical gear based on convolution

Abstract

The invention discloses a cylindrical gear internal meshing honing tooth surface microstructure prediction method based on convolution, and the method comprises the steps: calculating a motion velocity vector of grinding particles on the surface of a honing wheel at a contact point of a tooth surface of a workpiece according to a velocity equation of the motion of the tooth surface of the honing wheel relative to the tooth surface of the workpiece; simulating the sliding cutting process of the abrasive particles on the tooth surface of the workpiece along the motion velocity vector, and calculating the cutting characteristics of the abrasive particles; according to the number of revolutions and the number of abrasive particles of the machined workpiece gear, the total abrasive particle cutting frequency is calculated; calculating the cutting times of the abrasive particles on each contact point of the tooth surface of the workpiece based on the total cutting times of the abrasive particles; convolution calculation is carried out based on the abrasive particle cutting features and the cutting times of all the contact points, and a convolution result is obtained; and according to the convolution result, the tooth surface microstructure of the workpiece of the internal meshing gear honing is predicted. The method can improve the prediction accuracy of the surface microstructure of the internal meshing gear honing, and has universality.

Description

Technical Field

[0001] The present application relates to the field of mechanical processing and manufacturing technology, and in particular to a convolution-based method for predicting the micro-morphology of the surface of cylindrical gear internal meshing honing. Background Art

[0002] Faced with the wave of electrification, the transmission systems of high-end equipment have put forward higher requirements on gears, which urgently requires the use of more advanced gear processing technologies to improve the processing quality and manufacturing accuracy of gears, so as to ensure the high-reliability service performance of high-end equipment in complex environments and complex working conditions.

[0003] Internal gear honing is a key process for precision machining of gears and is one of the key processes for precision machining of high-end components such as new energy vehicles, high-speed rail, and aerospace. However, due to the unique cross-axis meshing method of internal gear honing and the very complex movement of abrasive particles during machining. The current surface visualization model of internal gear honing can only represent the movement direction of each contact point on a macro scale, and the research on the abrasive honing mechanism and the creation of surface micromorphology is not in-depth enough. Therefore, the existing related technologies have low accuracy in predicting the surface micromorphology of internal gear honing and have poor universality. Summary of the invention

[0004] The present application aims to propose a convolution-based method for predicting the micro-morphology of the surface of cylindrical gear internal meshing honing, which can improve the accuracy of the prediction of the micro-morphology of the surface of internal meshing honing and has universal applicability.

[0005] In a first aspect, an embodiment of the present application provides a method for predicting the microscopic morphology of a cylindrical gear internal meshing honing surface based on convolution, the method comprising: According to the velocity equation of the honing wheel tooth surface moving relative to the workpiece tooth surface, the velocity vector of the abrasive grains on the honing wheel surface at the contact point of the workpiece tooth surface is calculated; Simulating the sliding cutting process of the abrasive particles on the tooth surface of the workpiece along the motion velocity vector, and calculating the abrasive particle cutting characteristics; According to the number of revolutions and the number of abrasive grains of the workpiece gear being processed, the total number of abrasive grain cutting times is calculated; Calculating the number of cutting times of the abrasive grains at each contact point on the tooth surface of the workpiece based on the total number of cutting times of the abrasive grains; Performing convolution calculation based on the abrasive cutting characteristics and the number of cutting times of each contact point to obtain a convolution result; According to the convolution result, the microstructure of the tooth surface of the workpiece of internal meshing honing is predicted.

[0006] Compared with the prior art, the first aspect of the present application has the following beneficial effects: This method calculates the velocity vector of the abrasive grains on the surface of the honing wheel at the contact point of the workpiece tooth surface according to the velocity equation of the movement of the honing wheel tooth surface relative to the workpiece tooth surface; simulates the sliding cutting process of the abrasive grains on the workpiece tooth surface along the velocity vector, and calculates the cutting characteristics of the abrasive grains; calculates the total cutting times of the abrasive grains according to the number of revolutions of the workpiece gear and the number of abrasive grains; calculates the cutting times of the abrasive grains at each contact point on the workpiece tooth surface based on the total cutting times of the abrasive grains; performs convolution calculation based on the cutting characteristics of the abrasive grains and the cutting times of each contact point to obtain the convolution result; and predicts the microscopic morphology of the workpiece tooth surface of the internal meshing honing according to the convolution result. In this way, the cutting range and intensity of the abrasive grains on the three-dimensional space surface can be considered through the convolution operation, and the morphology creation at any local position of the tooth surface can be accurately predicted. Moreover, the convolution operation reveals the creation mechanism of the microscopic morphology of the workpiece surface through mathematical equations, and can accurately map the changes in processing parameters to the microscopic morphology of the workpiece surface. Therefore, by performing convolution calculation on the abrasive cutting characteristics and the number of cutting times at each contact point, the accuracy of the prediction of the micromorphology of the internal meshing honing surface can be improved, which is universal.

[0007] In some embodiments, the simulating the sliding cutting process of the abrasive particles on the tooth surface of the workpiece along the motion velocity vector and calculating the abrasive particle cutting characteristics includes: Simulating the sliding cutting process of the abrasive particles on the tooth surface of the workpiece along the motion velocity vector, and obtaining the cutting depth of the abrasive particles and the discrete points on the tooth surface contacted during the sliding cutting process; According to the cutting depth, calculating the radius of the abrasive grain embedded in the tooth surface of the workpiece; The portion of the abrasive grain embedded in the tooth surface of the workpiece is regarded as a spherical cap, the radius of the spherical cap is the radius of the abrasive grain embedded in the tooth surface of the workpiece, and the height of the spherical cap is equal to the cutting depth; The vertical distance from the discrete point on the tooth surface to the spherical cap curved surface is used as the abrasive cutting feature, and the discrete point on the tooth surface is a point within the radius of the spherical cap during the sliding cutting process.

[0008] In some embodiments, taking the vertical distance from the discrete point on the tooth surface to the spherical cap surface as the abrasive cutting feature comprises:

[0009] in, represents a single height removal function, represents the diameter of the abrasive grains, The radius corresponding to the point on the bottom of the spherical cap, represents the height of the spherical crown, Represents the radius of the spherical cap.

[0010] In some embodiments, the step of calculating the total number of abrasive cutting times according to the number of revolutions of the workpiece gear and the number of abrasive grains includes: Obtain the workpiece gear rotation number and tooth surface processing area required to complete honing; According to the abrasive grain size and the organization number of the honing wheel, the average spacing between the abrasive grains is calculated; Calculating the number of abrasive grains based on the average spacing between the abrasive grains and the area of ​​the tooth surface processing region; The number of workpiece gear revolutions required to complete the honing is multiplied by the number of abrasive grains to obtain the total number of abrasive grain cutting times.

[0011] In some embodiments, multiplying the number of workpiece gear revolutions required to complete the honing by the number of abrasive particles to obtain a total number of abrasive particle cutting times includes:

[0012] in, Indicates the total number of abrasive cutting times, Indicates the number of abrasive particles, Indicates the number of revolutions of the workpiece gear. Indicates the processing time, Indicates the number of workpiece gear revolutions required to complete honing. Indicates the area of ​​the tooth surface processing area, Indicates the abrasive particle size, Indicates the honing wheel organization number.

[0013] In some embodiments, performing convolution calculation based on the abrasive cutting feature and the number of cutting times of each contact point to obtain a convolution result includes:

[0014] in, represents the convolution result, represents the number of cuts in the matrix Line The number of cutting times of the contact point, represents a single height removal matrix, represents the convolution calculation, Represents the point in the mth row and nth column of the bottom surface of the spherical cap.

[0015] In some embodiments, predicting the microscopic morphology of the tooth surface of the workpiece of internal meshing honing according to the convolution result includes:

[0016] in, represents the predicted internal meshing honing surface micro-topography height matrix, represents the initial tooth surface height matrix, represents the convolution result, Represents the tooth surface normal vector The mold length.

[0017] In a second aspect, the present application also provides a convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction system, the system comprising: A first calculation unit is used to calculate the motion velocity vector of the abrasive grains on the surface of the honing wheel at the contact point of the tooth surface of the workpiece according to the velocity equation of the motion of the tooth surface of the honing wheel relative to the tooth surface of the workpiece; A second calculation unit is used to simulate the sliding cutting process of the abrasive particles on the tooth surface of the workpiece along the motion velocity vector, and calculate the abrasive particle cutting characteristics; A third calculation unit is used to calculate the total number of cutting times of the abrasive grains according to the number of revolutions of the workpiece gear and the number of abrasive grains; A fourth calculation unit, configured to calculate the number of cutting times of the abrasive grains at each contact point on the tooth surface of the workpiece based on the total number of cutting times of the abrasive grains; A convolution calculation unit, configured to perform convolution calculation based on the abrasive cutting characteristics and the number of cutting times of each contact point to obtain a convolution result; The micro-morphology prediction unit is used to predict the micro-morphology of the tooth surface of the workpiece of the internal meshing honing according to the convolution result.

[0018] In the third aspect, an embodiment of the present application also provides an electronic device, comprising at least one control processor and a memory for communicating with the at least one control processor; the memory stores instructions executable by the at least one control processor, and the instructions are executed by the at least one control processor so that the at least one control processor can execute the above-mentioned convolution-based method for predicting the micromorphology of the internal meshing honing surface of cylindrical gears.

[0019] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the above-mentioned convolution-based method for predicting the micromorphology of the internal meshing honing surface of cylindrical gears.

[0020] It can be understood that the beneficial effects of the second to fourth aspects compared with the related art are the same as the beneficial effects of the first aspect compared with the related art. Please refer to the relevant description in the first aspect, and no further details will be given here. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which: Figure 1 It is a flow chart of an embodiment of a method for predicting micro-morphology of cylindrical gear internal meshing honing surface based on convolution provided by the present application; Figure 2It is a schematic diagram of the overall process of the best embodiment of the convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction method provided by the present application; Figure 3 It is a schematic diagram of geometric motion of the internal meshing honing process in the best embodiment of the convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction method provided by the present application; Figure 4 It is a schematic diagram of the movement velocity vector of the abrasive grains on the surface of the honing wheel at the contact point of the workpiece tooth surface in the best embodiment of the convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction method provided by the present application; Figure 5 It is a simulation schematic diagram of sliding cutting of abrasive particles on the tooth surface of a workpiece along the motion velocity vector of the abrasive particles in the best embodiment of the convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction method provided by the present application; Figure 6 It is a schematic diagram of the number of cuts at each contact point on the tooth surface in the best embodiment of the convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction method provided by the present application; Figure 7 It is a schematic diagram of obtaining a rough surface profile by convolutionally removing materials in the best embodiment of the convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction method provided by the present application; Figure 8 It is a schematic diagram of generating surface micro-morphology data in the best embodiment of the convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction method provided by the present application; Fig. 9 is a schematic diagram of actual abrasive cutting traces in the best embodiment of the convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction method provided by the present application; Fig.10 It is a schematic diagram of simulated abrasive cutting traces in the best embodiment of the convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction method provided by the present application; Fig.11 It is a schematic diagram of the comparison of two-dimensional profiles of experimental and simulated micro-morphologies in the best embodiment of the convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction method provided by the present application; Fig.12 It is a structural schematic diagram of an embodiment of a convolution-based cylindrical gear internal meshing honing surface micromorphology prediction system provided in the present application. DETAILED DESCRIPTION

[0022] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as limiting the present application.

[0023] In the description of this application, if there is a description of first, second, etc., it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0024] In the description of the present application, it should be understood that the descriptions involving orientation, such as the orientation or positional relationship indicated as up, down, etc., are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0025] In the description of this application, it should be noted that, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meaning of the above terms in this application based on the specific content of the technical solution.

[0026] Faced with the wave of electrification, the transmission systems of high-end equipment have put forward higher requirements on gears, which urgently requires the use of more advanced gear processing technologies to improve the processing quality and manufacturing accuracy of gears, so as to ensure the high-reliability service performance of high-end equipment in complex environments and complex working conditions.

[0027] Internal gear honing is a key process for precision machining of gears and is one of the key processes for precision machining of high-end components such as new energy vehicles, high-speed rail, and aerospace. However, due to the unique cross-axis meshing method of internal gear honing and the very complex movement of abrasive particles during machining. The current surface visualization model of internal gear honing can only represent the movement direction of each contact point on a macroscopic scale, and the research on the abrasive honing mechanism and the creation of surface micromorphology is not in-depth enough. Therefore, the existing related technologies have low accuracy in predicting the surface micromorphology of internal gear honing and have poor universality.

[0028] In order to solve the problem that the above-mentioned existing related technologies have low accuracy and poor universality in predicting the micro-morphology of the internal meshing honing surface, this application proposes a convolution-based method for predicting the micro-morphology of the internal meshing honing surface of cylindrical gears.

[0029] Reference Figure 1 The present application provides a method for predicting the micro-morphology of the surface of cylindrical gear internal meshing honing based on convolution, the method comprising the following steps: Step S100, calculating the motion velocity vector of the abrasive grains on the surface of the honing wheel at the contact point of the tooth surface of the workpiece according to the velocity equation of the motion of the tooth surface of the honing wheel relative to the tooth surface of the workpiece; Step S200, simulating the process of abrasive particles sliding and cutting on the tooth surface of the workpiece along the motion velocity vector, and calculating the abrasive particle cutting characteristics; Step S300, calculating the total number of cutting times of the abrasive particles according to the number of revolutions of the workpiece gear and the number of abrasive particles; Step S400, calculating the number of cutting times of the abrasive grains at each contact point on the tooth surface of the workpiece based on the total number of cutting times of the abrasive grains; Step S500, performing convolution calculation based on the abrasive cutting characteristics and the number of cutting times of each contact point to obtain a convolution result; Step S600: predicting the microscopic morphology of the tooth surface of the workpiece of the internal meshing honing according to the convolution result.

[0030] In this embodiment, the velocity vector of the abrasive grains on the surface of the honing wheel at the contact point of the workpiece tooth surface is calculated according to the velocity equation of the movement of the honing wheel tooth surface relative to the workpiece tooth surface; the process of the abrasive grains sliding and cutting on the workpiece tooth surface along the velocity vector is simulated to calculate the abrasive grain cutting characteristics; the total number of abrasive grain cutting times is calculated according to the number of revolutions and the number of abrasive grains of the processed workpiece gear; the number of abrasive grain cutting times at each contact point of the workpiece tooth surface is calculated based on the total number of abrasive grain cutting times; the convolution calculation is performed based on the abrasive grain cutting characteristics and the number of cutting times at each contact point to obtain the convolution result; and the microscopic morphology of the workpiece tooth surface of the internal meshing honing is predicted according to the convolution result. In this way, the cutting range and intensity of the abrasive grains on the three-dimensional space surface can be considered through the convolution operation, and the morphology creation at any local position of the tooth surface can be accurately predicted, and the convolution operation is to reveal the creation mechanism of the microscopic morphology of the workpiece surface through mathematical equations, and the changes in processing parameters can be accurately mapped to the microscopic morphology of the workpiece surface. Therefore, by performing convolution calculation on the abrasive cutting characteristics and the number of cutting times at each contact point, the accuracy of the prediction of the micromorphology of the internal meshing honing surface can be improved, which is universal.

[0031] The above-mentioned velocity equation for the movement of the honing wheel tooth surface relative to the workpiece tooth surface is used to calculate the velocity vector of the abrasive grains on the honing wheel surface at the contact point of the workpiece tooth surface. This can be achieved by analyzing the geometric motion of the internal meshing honing process and calculating the velocity vector of the abrasive grains on the honing wheel surface at the contact point of the workpiece tooth surface. Since the abrasive grains must be at the contact point of the workpiece tooth surface when they start cutting the tooth surface, the contact point position coordinates are substituted into the velocity equation for the movement of the honing wheel tooth surface relative to the workpiece tooth surface to obtain the velocity vector. This velocity equation for the movement of the honing wheel tooth surface relative to the workpiece tooth surface can be calculated using existing technology.

[0032] The above simulation of the abrasive particles sliding and cutting on the workpiece tooth surface along the motion velocity vector calculates the abrasive cutting characteristics. Since the abrasive particles are embedded in the workpiece tooth surface and slide and cut along the motion velocity vector, the part of the abrasive particles embedded in the workpiece tooth surface can be regarded as a radius of , the height is The discrete points on the tooth surface that the spherical crown contacts during the sliding cutting process are points within the radius of the spherical crown. The vertical distances from these discrete points on the tooth surface to the curved surface of the spherical crown can be used as abrasive cutting features.

[0033] The number of revolutions of the gear of the above-mentioned workpiece can be obtained by counting the number of times the gear rotates per unit time.

[0034] The above calculation of the cutting times of each contact point between the abrasive and the workpiece tooth surface based on the total cutting times of the abrasive may be performed by mechanically and automatically counting the cutting times of each contact point between the abrasive and the workpiece tooth surface, but the sum of the cutting times of each contact point between the abrasive and the workpiece tooth surface is equal to the total cutting times of the abrasive.

[0035] The convolution calculation is performed based on the abrasive cutting characteristics and the number of cutting times of each contact point to obtain the convolution result. The number of cutting times of each contact point is used as the convolved matrix and the abrasive cutting characteristics are used as the convolution kernel to perform convolution operation to obtain the convolution result.

[0036] In some embodiments, simulating the sliding cutting process of abrasive particles on the tooth surface of a workpiece along the motion velocity vector and calculating the abrasive particle cutting characteristics includes: The process of abrasive particles sliding and cutting on the tooth surface of the workpiece along the motion velocity vector is simulated to obtain the cutting depth of the abrasive particles and the discrete points on the tooth surface contacted during the sliding cutting process; According to the cutting depth, calculate the radius of the abrasive embedded in the workpiece tooth surface; The part of the abrasive grain embedded in the workpiece tooth surface is regarded as a spherical cap, the radius of the spherical cap is the radius of the abrasive grain embedded in the workpiece tooth surface, and the height of the spherical cap is equal to the cutting depth; The vertical distance from the discrete point on the tooth surface to the spherical cap surface is taken as the abrasive cutting feature, and the discrete point on the tooth surface is the point within the spherical cap radius during the sliding cutting process.

[0037] In this embodiment, the abrasive particles are simulated to slide and cut on the tooth surface of the workpiece along the motion velocity vector, and the cutting depth of the abrasive particles and the discrete points on the tooth surface contacted during the sliding cutting process are obtained; the radius of the abrasive particles embedded in the tooth surface of the workpiece is calculated according to the cutting depth; the part of the abrasive particles embedded in the tooth surface of the workpiece is taken as a spherical cap, the radius of the spherical cap is the radius of the abrasive particles embedded in the tooth surface of the workpiece, and the height of the spherical cap is equal to the cutting depth; the vertical distance from the discrete points on the tooth surface to the spherical cap surface is taken as the abrasive particle cutting feature. In this way, the abrasive particle cutting feature is used as the convolution kernel to reflect the influence weight of the abrasive particles on a certain position on the tooth surface of the workpiece, and to lay a good data foundation for the later accurate prediction of the microscopic morphology of the internal meshing honing surface.

[0038] The cutting depth may be the vertical distance between the machined surface and the surface to be machined each time the workpiece is cut.

[0039] In some embodiments, taking the vertical distance from the discrete point on the tooth surface to the spherical cap surface as the abrasive cutting feature comprises:

[0040] in, represents a single height removal function, represents the diameter of the abrasive grains, The radius corresponding to the point on the bottom of the spherical cap, represents the height of the spherical crown, Represents the radius of the spherical cap.

[0041] In some embodiments, the total number of abrasive cutting times is calculated according to the number of revolutions of the workpiece gear and the number of abrasive grains, including: Obtain the workpiece gear rotation number and tooth surface processing area required to complete honing; According to the abrasive grain size and the organization number of the honing wheel, the average spacing between the abrasive grains is calculated; The number of abrasive grains is calculated based on the average spacing between the abrasive grains and the area of ​​the tooth surface processing area; The total number of cuts by the abrasive grains is obtained by multiplying the number of workpiece gear revolutions required to complete the honing by the number of abrasive grains.

[0042] In this embodiment, the distribution of cutting times is used as a convoluted function to reflect the contact form between the abrasive and the workpiece tooth surface. By calculating the total cutting times of the abrasive to constrain the cutting times of each contact point in the later stage, a good data foundation is laid for the later accurate prediction of the microscopic morphology of the internal meshing honing surface.

[0043] In some embodiments, the number of workpiece gear revolutions required to complete honing is multiplied by the number of abrasive particles to obtain the total number of abrasive particle cutting times, including:

[0044] in, Indicates the total number of abrasive cutting times, Indicates the number of abrasive particles, Indicates the number of revolutions of the workpiece gear. Indicates the processing time, Indicates the number of workpiece gear revolutions required to complete honing. Indicates the area of ​​the tooth surface processing area, Indicates the abrasive particle size, Indicates the honing wheel organization number.

[0045] In some embodiments, a convolution calculation is performed based on the abrasive cutting characteristics and the number of cutting times of each contact point to obtain a convolution result, including:

[0046] in, represents the convolution result, represents the number of cuts in the matrix Line The number of cutting times of the contact point, represents a single height removal matrix, represents the convolution calculation, Represents the point in the mth row and nth column of the bottom surface of the spherical cap.

[0047] In some embodiments, predicting the microscopic morphology of the tooth surface of a workpiece of internal meshing honing according to the convolution result includes:

[0048] in, represents the predicted internal meshing honing surface micro-topography height matrix, represents the initial tooth surface height matrix, represents the convolution result, Represents the tooth surface normal vector The mold length.

[0049] In this embodiment, the cutting range and intensity of the abrasive on the three-dimensional space surface can be considered through the convolution operation, so the morphology creation at any local position of the tooth surface can be accurately predicted. In addition, the convolution operation reveals the creation mechanism of the micro-morphology of the workpiece surface through mathematical equations, and can accurately map the changes in processing parameters to the micro-morphology of the workpiece surface. It has the characteristics of fast calculation and real-time adjustment, which improves the robustness and universality of the prediction.

[0050] To facilitate understanding by those skilled in the art, a set of best embodiments is provided below: Faced with the wave of electrification, the transmission systems of high-end equipment have put forward higher requirements on gears, which urgently requires the use of more advanced gear processing technologies to improve the processing quality and manufacturing accuracy of gears, so as to ensure the high-reliability service performance of high-end equipment in complex environments and complex working conditions.

[0051] Internal gear honing is a key process for precision machining of gears and is one of the key processes for precision machining of high-end components such as new energy vehicles, high-speed rail, and aerospace. However, due to the unique cross-axis meshing method of internal gear honing and the very complex movement of abrasive particles during machining, there is almost no relevant research on the prediction model of the microscopic morphology of the machined surface. The current surface visualization model of internal gear honing can only represent the movement direction of each contact point on a macro scale, and the research on the abrasive honing mechanism and the creation of surface microscopic morphology is not in-depth enough. This inhibits the further application and promotion of internal gear honing technology in the field of precision manufacturing.

[0052] Therefore, this embodiment proposes a convolution-based method for predicting the micromorphology of the surface of cylindrical gear internal meshing honing, which can achieve accurate prediction of the micromorphology and microtexture characteristics of the honing workpiece surface, and is expected to provide practical guidance for the high-precision manufacturing of high-end gears.

[0053] Mathematically speaking, the convolution operation is to combine two functions to produce a new function, which represents the result of one function being processed by another function. and , their convolution is defined as:

[0054] The essence of convolution operation can be understood as a weighted summation process, which is highly consistent with the behavior of abrasive particles moving on the workpiece surface and accumulating cutting in grinding. The material removal mechanism of internal meshing honing is similar to that of traditional grinding. The surface abrasive particles of the honing wheel are pressed into the workpiece surface through the feed motion, and the surface material of the workpiece is removed during relative motion. As the cutting action of a large number of randomly distributed abrasive particles is superimposed on each other, the microscopic morphology of the workpiece tooth surface after material removal is formed. Through mathematical modeling, the material removal height distribution of honing can be described as the cutting characteristics of a single abrasive particle according to the accumulation of the number of cuts.

[0055] Specifically, the cutting characteristics of the abrasive are the cutting marks determined by the cutting direction of the abrasive and the depth and radius of the embedded surface. They are abstracted as convolution kernels, which reflect the weight of the influence of the abrasive on a certain position of the workpiece tooth surface; the distribution of the number of cutting times is used as the convolution function, which reflects the contact form between the abrasive and the workpiece tooth surface. The product of the two is the cumulative cutting depth of the abrasive. When the abrasive cuts a certain position on the tooth surface, the adjacent position will also have a cutting effect on the current position, and the influence is defined by the convolution kernel. After the convolution kernel traverses the entire tooth surface, the function after the convolution operation is obtained, that is, the height removal function. Finally, the height removal is performed along the normal direction of the tooth surface point on the initial contour to obtain the predicted surface micro-morphology data of the internal meshing honing workpiece.

[0056] Reference Figure 2 The technical solution of this embodiment specifically includes the following contents: Step 1: Calculate the velocity vector of the abrasive particles. First, we need to analyze the geometric motion of the internal meshing honing process and calculate the velocity vector of the abrasive particles on the surface of the honing wheel at each contact point on the workpiece tooth surface. Internal meshing honing is a processing method in which the honing wheel is axially and radially reciprocating. Figure 3 The coordinate system shown and the following explanations are given: is the workpiece gear fixed coordinate system, is the workpiece gear motion coordinate system, For the workpiece gear The angle through which the shaft rotates is ; is the fixed coordinate system of the honing wheel, is the motion coordinate system of the honing wheel, For honing wheel The angle through which the shaft rotates is . Due to the axial angle between the workpiece gear and the honing wheel , so set the transition coordinate system , The distance between the center , , They are the radial feed speed of the honing wheel and the axial feed speed of the honing wheel respectively.

[0057] The calculation of the relative speed of each point between the workpiece gear and the honing wheel tooth surface must be performed in the same coordinate system. The following formula can be used to realize the mutual transformation between any coordinate systems:

[0058] in, , , , .

[0059] If is the reference coordinate system. Through coordinate transformation, the speed of the honing wheel tooth surface relative to the workpiece tooth surface can be expressed as:

[0060] like Figure 4 As shown in the figure, the tooth surface of the workpiece is rotated at equal angles along the tooth profile direction from the beginning to the end of meshing, and several contact lines are obtained on the tooth surface. Then, the points on the contact lines are discretized along the tooth direction, which are called the contact points between the abrasive grains and the tooth surface of the workpiece. When the abrasive grains start to cut the tooth surface, their position coordinates must be at the contact point. Therefore, the velocity vector of the abrasive grains can be obtained by substituting the contact point position coordinates ( , , ) is solved into the above formula (2).

[0061] Step 2: Calculate the cutting characteristics of abrasive particles. Assume that the abrasive particles have a diameter of The radius of a single abrasive particle embedded in the workpiece tooth surface can be calculated using the following formula :

[0062] in, Indicates the cutting depth.

[0063] Figure 5 The process of sliding cutting of abrasive particles on the tooth surface of the workpiece along the velocity vector of the abrasive particles is simulated. Figure 5 (a) is a schematic diagram showing the process of abrasive particles sliding on the workpiece tooth surface along the motion velocity vector of the abrasive particles and contacting discrete points on the tooth surface. Figure 5 (b) shows the schematic diagram of the abrasive embedded in the workpiece tooth surface. The part of the abrasive embedded in the workpiece tooth surface is regarded as a radius of , the height is The ball crown, , Figure 5 The contact points in (a) represent the discrete points on the tooth surface that the abrasive particles touch when they move a small distance along the velocity vector of the abrasive particles. These discrete points on the tooth surface will be highly removed. The removed height is the vertical distance from each discrete point on the tooth surface to the spherical crown surface, which is expressed as:

[0064] in, is a single height removal function. Consider the bottom of the spherical cap as a matrix consisting of m×n points, then the radius corresponding to the point in the mth row and nth column is It can be expressed as , the single height removal amount of this point is D(m,n).

[0065] Step 3: Calculate the number of abrasive cutting. During the internal meshing honing process, only some abrasives are effectively cut, and these abrasives are called effective abrasives. The abrasives that do not participate in cutting are invalid abrasives. Assume that the amount of material removal produced by each effective abrasive is the same. For any local position on the tooth surface, considering the uneven distribution of abrasives and the difference in the height of the cutting edge, a discrete matrix can be used to represent the number of cutting times at each contact point, and the following constraints are made:

[0066] in, is the total number of abrasive cutting times, It represents the number of cutting times of the abrasive at the contact point of the i-th row and j-th column on the local position of the tooth surface. Since the ineffective abrasive does not participate in the cutting behavior, the number of cutting times at its contact point is 0. Figure 6 The schematic diagram of the number of cutting times at each contact point on the tooth surface is shown. The calculation process is as follows: Assuming that the abrasive grains on the surface of the honing wheel are evenly distributed, according to the abrasive grain size Organization number of honing wheels , the average spacing between abrasive particles can be calculated for:

[0067] Then the number of abrasive grains used to process any tooth surface position can be expressed as:

[0068] in, Indicates the area of ​​the tooth surface machining area.

[0069] The contact between the honing wheel and the workpiece tooth surface is a one-way line contact, that is, in each rotation cycle of the workpiece gear, a single abrasive grain will only come into contact with any position of the tooth surface once, and cut the tooth surface along the direction of relative motion. After multiple cycles, the cutting action of a single abrasive grain continues to accumulate, and the cutting action of all abrasive grains is superimposed to complete the cutting of the entire processing area. Therefore, the product of the number of workpiece gear revolutions required to complete honing and the number of abrasive grains is the total number of cutting times. Then, the honing processing area is The expression for the total number of cuts required for the area is:

[0070] in, Indicates the number of revolutions of the workpiece gear. Indicates processing time.

[0071] Step 4: Convolution calculates the cumulative material removal height. Because the surface height matrix is ​​not a continuous function, the convolution should use the summation sign to convert the cutting number matrix As the convolved matrix, a single height removal matrix As the convolution kernel, perform convolution calculation:

[0072] in, represents the convolution calculation, It represents the cumulative height removal matrix, which describes the total height change of the workpiece tooth surface after honing. The schematic diagram of the rough surface profile obtained by convolution material removal is shown in Figure 7 shown.

[0073] Step 5: Generate surface micro-morphology data. Figure 8 As shown, Added in the normal direction of the corresponding tooth surface point, the predicted micro-morphology data is obtained:

[0074] in, represents the initial tooth surface height matrix, Represents the tooth surface normal vector The module length, Represents the predicted internal gear honing surface micro-topography height matrix.

[0075] Fig. 9 and Fig.10 The results of the experimental and simulated workpiece tooth surface micro-morphology are shown respectively. It can be clearly seen from the figure that the two have the same direction of honing lines. The local enlarged image of the measured morphology also shows the randomly distributed abrasive grains on the micro-tooth surface, reflecting the interaction between the abrasive grains on the honing wheel surface and the processed tooth surface during the honing process. This cutting mark is also reflected in the simulated morphology. By comparing the surface height parameters of the experimental and simulated morphologies, the results show that the average height The error is 5.57%, the RMS height The error is 8.56%, which proves the accuracy of the prediction model. In addition, the two-dimensional profiles of the experimental and simulated micromorphologies are compared, such as Fig.11 As shown, the curve presents a random oscillation form, which further illustrates that the convolution operation simulates the motion process of the abrasive particles randomly contacting the tooth surface and forming a rough tooth profile.

[0076] In summary, the feasibility and accuracy of the convolution-based surface micromorphology prediction method for internal honing of cylindrical gears were verified.

[0077] Compared with the prior art, the technical solution of this embodiment has the following advantages: (1) Research on abrasive cutting simulation generally simplifies the cutting marks of abrasives on the tooth surface into a two-dimensional indentation profile to reduce computational complexity. However, the convolution operation can consider the cutting range and intensity of abrasives on a three-dimensional surface, and can accurately predict the morphology of any local position on the tooth surface. At the same time, when a large number of random abrasives are cutting at the same or adjacent positions on the tooth surface, the convolution can correctly accumulate these effects, which is closer to the actual processing process.

[0078] (2) The prediction model of the micro-morphology of the grinding surface is usually extracted and summarized through statistical methods such as neural networks and regression analysis, and then the prediction model is established. Although this type of method has high prediction accuracy, it is easily affected by external factors, cannot be widely applied, and has a long operation cycle. The convolution operation reveals the creation mechanism of the micro-morphology of the workpiece surface through mathematical equations, and can accurately map the changes in processing parameters to the micro-morphology of the workpiece surface. It has the characteristics of fast calculation and real-time adjustment, which improves the robustness and universality of the prediction model.

[0079] (3) Compared with the method of using the direction of motion to represent the macroscopic surface texture of the internal meshing honing workpiece, the convolution operation can simulate the formation process of the honing texture at the micro level and output the microscopic morphology of the workpiece honing surface, accurately reflecting the roughness, waviness, and processing traces of the machined tooth surface and the relationship between them and the processing parameters. This provides a method for active control of processing quality and coordinated optimization of process parameters for the precision manufacturing of gears, which can effectively reduce the additional costs caused by experimental adjustments and processing errors.

[0080] Reference Fig.12 The embodiment of the present application further provides a convolution-based micro-morphology prediction system for the surface of cylindrical gear internal meshing honing, the system comprising a first calculation unit 100, a second calculation unit 200, a third calculation unit 300, a fourth calculation unit 400, a convolution calculation unit 500 and a micro-morphology prediction unit 600, wherein: The first calculation unit 100 is used to calculate the motion velocity vector of the abrasive grains on the surface of the honing wheel at the contact point of the tooth surface of the workpiece according to the velocity equation of the motion of the tooth surface of the honing wheel relative to the tooth surface of the workpiece; The second calculation unit 200 is used to simulate the sliding cutting process of the abrasive particles on the tooth surface of the workpiece along the motion velocity vector and calculate the abrasive particle cutting characteristics; The third calculation unit 300 is used to calculate the total number of cutting times of the abrasive particles according to the number of revolutions of the workpiece gear and the number of abrasive particles; A fourth calculation unit 400 is used to calculate the number of cutting times of the abrasive particles at each contact point on the tooth surface of the workpiece based on the total number of cutting times of the abrasive particles; A convolution calculation unit 500 is used to perform convolution calculation based on the abrasive cutting characteristics and the number of cutting times of each contact point to obtain a convolution result; The micro-morphology prediction unit 600 is used to predict the micro-morphology of the tooth surface of the workpiece of the internal meshing honing according to the convolution result.

[0081] It should be noted that since the convolution-based cylindrical gear internal meshing honing surface micromorphology prediction system in this embodiment and the above-mentioned convolution-based cylindrical gear internal meshing honing surface micromorphology prediction method are based on the same inventive concept, the corresponding contents in the method embodiment are also applicable to the system embodiment and will not be described in detail here.

[0082] An embodiment of the present application also provides an electronic device, comprising: at least one control processor and a memory for communicating with the at least one control processor.

[0083] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0084] The non-transient software program and instructions required to implement the above-mentioned embodiment of a method for predicting the micro-morphology of the internal meshing honing of cylindrical gears based on convolution are stored in the memory. When executed by the processor, the above-mentioned embodiment of a method for predicting the micro-morphology of the internal meshing honing of cylindrical gears based on convolution is executed, for example, the above-mentioned method is executed. Figure 1 The method comprises steps S100 to S600.

[0085] The system embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0086] The present application also provides a computer-readable storage medium storing computer-executable instructions, which are executed by one or more control processors to enable the one or more control processors to execute a convolution-based cylindrical gear internal meshing honing surface micromorphology prediction method in the above method embodiment, for example, to execute the above described Figure 1 The functions of method steps S100 to S600 in the embodiment.

[0087] It will be appreciated by those skilled in the art that all or some of the steps and systems in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or transient medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0088] The above is a specific description of the preferred implementation of the embodiments of the present application, but the embodiments of the present application are not limited to the above-mentioned implementation methods. Technical personnel familiar with the field can also make various equivalent modifications or substitutions without violating the spirit of the embodiments of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the embodiments of the present application.

[0089] The embodiments of the present application are described in detail above in conjunction with the accompanying drawings, but the present application is not limited to the above embodiments. Various changes can be made within the knowledge scope of ordinary technicians in the relevant technical field without departing from the purpose of the present application.

Claims

1. A convolution-based method for predicting the micro-morphology of the surface of cylindrical gear internal meshing honing, characterized in that: The method comprises: According to the velocity equation of the honing wheel tooth surface moving relative to the workpiece tooth surface, the velocity vector of the abrasive grains on the honing wheel surface at the contact point of the workpiece tooth surface is calculated; Simulating the sliding cutting process of the abrasive particles on the tooth surface of the workpiece along the motion velocity vector, and calculating the abrasive particle cutting characteristics; According to the number of revolutions and the number of abrasive grains of the workpiece gear being processed, the total number of abrasive grain cutting times is calculated; Calculating the number of cutting times of the abrasive grains at each contact point on the tooth surface of the workpiece based on the total number of cutting times of the abrasive grains; Performing convolution calculation based on the abrasive cutting characteristics and the number of cutting times of each contact point to obtain a convolution result; According to the convolution result, the microstructure of the tooth surface of the workpiece of internal meshing honing is predicted.

2. The convolution-based method for predicting the micro-morphology of the cylindrical gear internal meshing honing surface according to claim 1 is characterized in that: The process of simulating the sliding cutting of the abrasive particles on the tooth surface of the workpiece along the motion velocity vector and calculating the abrasive particle cutting characteristics includes: Simulating the sliding cutting process of the abrasive particles on the tooth surface of the workpiece along the motion velocity vector, and obtaining the cutting depth of the abrasive particles and the discrete points on the tooth surface contacted during the sliding cutting process; According to the cutting depth, calculating the radius of the abrasive grain embedded in the tooth surface of the workpiece; The portion of the abrasive grain embedded in the tooth surface of the workpiece is regarded as a spherical cap, the radius of the spherical cap is the radius of the abrasive grain embedded in the tooth surface of the workpiece, and the height of the spherical cap is equal to the cutting depth; The vertical distance from the discrete point on the tooth surface to the spherical cap curved surface is used as the abrasive cutting feature, and the discrete point on the tooth surface is a point within the radius of the spherical cap during the sliding cutting process.

3. The convolution-based method for predicting the micro-morphology of the cylindrical gear internal meshing honing surface according to claim 2 is characterized in that: The method of taking the vertical distance from the discrete point on the tooth surface to the spherical cap surface as the abrasive cutting feature comprises: in, represents a single height removal function, represents the diameter of the abrasive grains, The radius corresponding to the point on the bottom of the spherical cap, represents the height of the spherical crown, Represents the radius of the spherical cap.

4. The convolution-based method for predicting the micro-morphology of the cylindrical gear internal meshing honing surface according to claim 1, characterized in that: The method of calculating the total number of cutting times of the abrasive grains according to the number of revolutions of the workpiece gear and the number of abrasive grains includes: Obtain the workpiece gear rotation number and tooth surface processing area required to complete honing; According to the abrasive grain size and the organization number of the honing wheel, the average spacing between the abrasive grains is calculated; Calculating the number of abrasive grains based on the average spacing between the abrasive grains and the area of ​​the tooth surface processing region; The number of workpiece gear revolutions required to complete the honing is multiplied by the number of abrasive grains to obtain the total number of abrasive grain cutting times.

5. The convolution-based method for predicting the micro-morphology of the cylindrical gear internal meshing honing surface according to claim 4 is characterized in that: The step of multiplying the number of workpiece gear revolutions required to complete the honing by the number of abrasive grains to obtain the total number of abrasive grain cutting times includes: in, Indicates the total number of abrasive cutting times, Indicates the number of abrasive particles, Indicates the number of revolutions of the workpiece gear. Indicates the processing time, Indicates the number of workpiece gear revolutions required to complete honing. Indicates the area of ​​the tooth surface processing area, Indicates the abrasive particle size, Indicates the honing wheel organization number.

6. The convolution-based method for predicting the micro-morphology of the cylindrical gear internal meshing honing surface according to claim 1, characterized in that: The convolution calculation is performed based on the abrasive cutting characteristics and the number of cutting times of each contact point to obtain a convolution result, including: in, represents the convolution result, represents the number of cuts in the matrix Line The number of cutting times of the contact point, represents a single height removal matrix, represents the convolution calculation, Represents the point at the mth row and nth column of the bottom surface of the spherical cap.

7. The convolution-based method for predicting the micro-morphology of the cylindrical gear internal meshing honing surface according to claim 1, characterized in that: The method of predicting the microscopic morphology of the tooth surface of the workpiece of the internal meshing honing according to the convolution result includes: in, represents the predicted internal meshing honing surface micro-topography height matrix, represents the initial tooth surface height matrix, represents the convolution result, Represents the tooth surface normal vector The mold length.

8. A convolution-based cylindrical gear internal meshing honing surface micro-morphology prediction system, characterized in that: The system comprises: A first calculation unit is used to calculate the motion velocity vector of the abrasive grains on the surface of the honing wheel at the contact point of the tooth surface of the workpiece according to the velocity equation of the motion of the tooth surface of the honing wheel relative to the tooth surface of the workpiece; A second calculation unit is used to simulate the sliding cutting process of the abrasive particles on the tooth surface of the workpiece along the motion velocity vector, and calculate the abrasive particle cutting characteristics; A third calculation unit is used to calculate the total number of cutting times of the abrasive grains according to the number of revolutions of the workpiece gear and the number of abrasive grains; A fourth calculation unit, configured to calculate the number of cutting times of the abrasive grains at each contact point on the tooth surface of the workpiece based on the total number of cutting times of the abrasive grains; A convolution calculation unit, configured to perform convolution calculation based on the abrasive cutting characteristics and the number of cutting times of each contact point to obtain a convolution result; The micro-morphology prediction unit is used to predict the micro-morphology of the tooth surface of the workpiece of the internal meshing honing according to the convolution result.

9. An electronic device, characterized in that: It includes at least one control processor and a memory for communicating with the at least one control processor; the memory stores instructions that can be executed by the at least one control processor, and the instructions are executed by the at least one control processor so that the at least one control processor can execute the convolution-based cylindrical gear internal meshing honing surface micromorphology prediction method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the convolution-based cylindrical gear internal meshing honing surface micromorphology prediction method as described in any one of claims 1 to 7.

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