Machined surface evaluation device, machined surface evaluation method, and computer program

Abstract

The present invention provides a technology for evaluating machined surfaces with higher precision than heretofore. Provided is a machined surface evaluation device using BRDF data, i.e., a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on a machined surface of a workpiece. This machined surface evaluation device deems the angle with the highest reflected light intensity in the BRDF data to be the specular reflection angle, calculates gloss and / or haze based on the reflected light intensity at the angle deemed to be the specular reflection angle, and evaluates the machined surface on the basis of the calculated gloss and / or haze.

Description

Machined surface evaluation device, machined surface evaluation method, and computer program

[0001] The present disclosure relates to a machined surface evaluation device, a machined surface evaluation method, and a computer program.

[0002] Conventionally, the bidirectional reflectance distribution function (hereinafter referred to as BRDF data) is known, which represents the angular distribution characteristics of reflected light when light is incident on the machined surface of a workpiece. Since the BRDF data is data that correlates with the surface shape of the machined surface, gloss and haze are calculated from this BRDF data, and the machined surface is evaluated based on the obtained gloss and haze.

[0003] However, measuring BRDF data requires a specialized device, and therefore, studies are underway to obtain BRDF data by simulation from surface shape data such as surface roughness data.

[0004] For example, Non-Patent Document 1 discloses a technique for predicting BRDF data based on surface roughness data of a metal surface through simulation using a microfacet model. The technique described in Non-Patent Document 1 assumes that a plurality of sufficiently small meshes called microfacets are present on the processed surface, and that light incident on each mesh is perfectly specularly reflected by each mesh. Furthermore, a half vector is defined by adding the light source direction and the viewpoint direction vector, and the microfacet normal distribution function (NDF) is a probability distribution function that represents the number of microfacet normals pointing in the half vector direction. The technique is said to be able to acquire BRDF data by mathematically modeling the NDF using a general GGX function or the like.

[0005] Dong et al, ACM Trans. Graph, Vol. 35, No. 1 (2015)

[0006] However, the applicant's investigation has revealed that when gloss and haze are calculated from BRDF data of a processed surface obtained by simulation, the results do not reflect the surface quality that is actually visible to the naked eye, and are different from those obtained by visual evaluation. Therefore, there is a need for a technology for evaluating processed surfaces with higher accuracy than conventional methods.

[0007] The present disclosure has been made in consideration of the above-mentioned problems, and aims to provide a technique for evaluating a machined surface with higher accuracy than conventional techniques.

[0008] The present disclosure provides a machined surface evaluation device that uses BRDF data, which is a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on the machined surface of a workpiece, and that regards the angle at which the amount of reflected light in the BRDF data is greatest as the specular reflection angle, calculates gloss and / or haze based on the amount of reflected light at the angle regarded as the specular reflection angle, and evaluates the machined surface based on the calculated gloss and / or haze.

[0009] The present disclosure also provides a machined surface evaluation method that uses BRDF data, which is a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on the machined surface of a workpiece, in which the angle at which the amount of reflected light in the BRDF data is greatest is regarded as the specular reflection angle, gloss and / or haze are calculated based on the amount of reflected light at the angle regarded as the specular reflection angle, and the machined surface is evaluated based on the calculated gloss and / or haze.

[0010] The present disclosure also provides a computer program that causes a computer to evaluate a processed surface using BRDF data, which is a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on the processed surface of a workpiece, and that considers the angle in the BRDF data at which the amount of reflected light is greatest to be the specular reflection angle, calculates gloss and / or haze based on the amount of reflected light at the angle considered to be the specular reflection angle, and causes the computer to evaluate the processed surface based on the calculated gloss and / or haze.

[0011] According to the present disclosure, it is possible to provide a technique for evaluating a machined surface with higher accuracy than conventional techniques.

[0012] 1 is a functional block diagram of a BRDF simulation device according to an embodiment of the present disclosure. FIG. 1 is a diagram illustrating an example of surface roughness data of a machined surface of a workpiece. FIG. 2 is a diagram for explaining conversion of surface roughness data. FIG. 3 is a diagram illustrating a matrix and mesh of surface roughness data. FIG. 4 is a diagram illustrating the inclination of a type 1 mesh with respect to the XY plane. FIG. 5 is a diagram illustrating the deviation amount -2θ of the specular reflection angle. FIG. 6 is a diagram illustrating an example of BRDF data according to the embodiment. FIG. 7 is a diagram illustrating an example of a two-dimensional display graph of the reflection intensity of a matte-finished surface generated based on the BRDF data according to the embodiment. FIG. 8 is a diagram illustrating an example of a two-dimensional display graph of the reflection intensity of a high-gloss-finished surface generated based on the BRDF data according to the embodiment. FIG. 9 is a diagram illustrating an example of a three-dimensional display graph of the reflection intensity of a matte-finished surface generated based on the BRDF data according to the embodiment. FIG. 10 is a diagram illustrating gloss and haze. FIG. 11 is a diagram illustrating the relationship between gloss and haze calculated based on the BRDF data according to the embodiment and the acquisition width of the surface roughness data. FIG. 12 is a diagram illustrating the actual measurement results of forward gloss. FIG. 13 is a diagram illustrating the simulation results of forward gloss according to the embodiment. FIG. 14 is a diagram illustrating the actual measurement results of perpendicular gloss. FIG. 1 is a diagram showing a simulation result of vertical gloss according to the embodiment. FIG. 2 is a diagram showing an actual measurement result of forward haze according to the embodiment. FIG. 3 is a diagram showing a simulation result of forward haze according to the embodiment. FIG. 4 is a diagram showing an actual measurement result of vertical haze according to the embodiment. FIG. 5 is a diagram showing a simulation result of vertical haze according to the embodiment. FIG. 6 is a diagram showing a simulation result of forward gloss considering a Gaussian beam according to the embodiment. FIG. 7 is a diagram showing a simulation result of vertical gloss considering a Gaussian beam according to the embodiment. FIG. 8 is a diagram showing a simulation result of forward haze considering a Gaussian beam according to the embodiment. FIG. 9 is a diagram showing an example of a two-dimensional display graph of gloss and haze according to the embodiment. FIG. 10 is a diagram showing an example of a two-dimensional display graph of pseudo gloss and pseudo haze according to the embodiment. FIG. 11 is a diagram showing pseudo gloss and pseudo haze.1 is a diagram showing the relationship between gloss and visual judgment according to the embodiment; FIG. 2 is a diagram showing the relationship between pseudo-gloss and visual judgment according to the embodiment; FIG. 3 is a flowchart showing the processing procedure for processing surface evaluation according to the embodiment;

[0013] Hereinafter, an embodiment of the present disclosure will be described in detail with reference to the drawings.

[0014] A machined surface evaluation device 1 according to an embodiment of the present disclosure generates, by simulation, BRDF data, which is a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on the machined surface of a workpiece, and evaluates the machined surface by calculating gloss and haze from the generated BRDF data. In the present disclosure, there are no limitations on the BRDF simulation algorithm itself, but for example, the machined surface evaluation device 1 according to this embodiment generates BRDF data by simulation based on microfacet theory, calculates gloss and haze for each specular reflection angle based on the generated BRDF data, and evaluates the machined surface based on the calculated gloss and haze.

[0015] In other words, in the BRDF simulation of this embodiment, it is assumed that there are multiple sufficiently small meshes called microfacets on a machined surface, such as a cut surface, which can be considered to be a plane macroscopically even if it is actually a curved surface rather than a flat surface. In this case, the meshes are small enough to be considered to be a plane. Furthermore, if the workpiece is, for example, metal, it can be assumed that light incident on each mesh is completely mirror-reflected by each mesh without scattering.

[0016] The BRDF simulation of this embodiment is based on the following assumptions: light is treated as a particle and the wave effect is ignored, so the simulation is applicable when the size of a microscopic surface is larger than a fraction of the wavelength. Also, because the wave effect is ignored, the diffraction phenomenon is not taken into account.

[0017] Furthermore, differences in reflectivity due to wavelength and polarization are ignored. Also, light is assumed to be perpendicular to the processed surface and to be uniformly parallel light across the entire surface. Reflection is considered only once. In other words, there is no reflection, and it is assumed that light does not hit another location after reflecting.

[0018] Based on the above assumptions, the machined surface evaluation device 1 according to this embodiment generates BRDF data by simulation. Unlike conventional methods, the machined surface evaluation device 1 according to this embodiment can acquire BRDF data without using a mathematical modeling technique such as a GGX function.

[0019] As shown in Figure 1, the machined surface evaluation device 1 according to this embodiment includes a surface shape data acquisition unit 11, a surface shape data conversion unit 12, a mesh partition unit 13, a specular reflection angle deviation calculation unit 14, a BRDF data generation unit 15, a pseudo-gloss pseudo-haze calculation unit 16, and an evaluation unit 17.

[0020] The machined surface evaluation device 1 is configured using a computer including memories such as a ROM (read only memory) and a RAM (random access memory), a CPU (control processing unit), and a communication control unit, which are connected to each other via a bus. The functions and operations of each functional unit, which will be described later, are achieved by the cooperation of the CPU and memory installed in the computer, and the control program stored in the memory.

[0021] The surface shape data acquisition unit 11 acquires surface shape data of the machined surface of the workpiece. The surface shape data may be any data that correlates with the surface shape of the machined surface of the workpiece, such as surface roughness data.

[0022] The surface shape data acquiring unit 11 acquires surface shape data input to the BRDF simulation device 1 through an input operation by a user or transmission from an external device. Alternatively, the surface shape data acquiring unit 11 reads and acquires surface shape data that has been input in advance to the machined surface evaluation device 1 and stored in a storage unit (not shown).

[0023] Surface shape data such as surface roughness data can be data measured using a surface shape measuring device such as a surface roughness measuring device. Surface roughness measuring devices can be of either contact or non-contact type, but for example, a surface roughness measuring device using a non-contact laser microscope can be preferably used.

[0024] Note that the BRDF simulation according to this embodiment, which will be described later, is a program for two-dimensional calculations, and therefore two-dimensional surface roughness data is assumed as the surface shape data. Therefore, in the case of one-dimensional roughness data called line roughness data, the one-dimensional line roughness data is simply copied as is into one or more additional columns to form an array of N × 2 or more, and then the BRDF simulation of this embodiment is executed, thereby enabling a very simple BRDF simulation without creating a new program for one dimension.

[0025] Furthermore, surface shape data such as surface roughness data can also be used as surface shape data of the machined surface estimated based on machining position data when the workpiece is machined by a machine tool. The machining position data is obtained from a computer numerical control (CNC) that controls the machine tool, and is any one of the machining program, servo control commands for the servo motor that drives the machine tool, and feedback information from the servo motor and the machine tool. Using this machining position data, the machined parts and the parts that remain unmachined on the workpiece can be calculated, and the surface shape data of the machined surface can be estimated.

[0026] The surface shape data is preferably surface shape data in increments of 0.1 μm to 15.0 μm. This is because if the increment width of the surface shape data, i.e., the data acquisition width, is less than 0.1 μm, the amount of simulation calculation and calculation time for the BRDF data will be enormous. Furthermore, since the mesh slope described below is calculated by dividing the data by the increment width, if the increment width exceeds 15.0 μm, the mesh slope will become too small, reducing the accuracy of the BRDF data. More preferably, the surface shape data is surface shape data in increments of 0.1 μm to 10.0 μm, and even more preferably, the surface shape data is surface shape data in increments of 0.1 μm to 5.0 μm.

[0027] Fig. 2 is a diagram showing an example of surface roughness data of a machined surface of a workpiece. The surface roughness data shown in Fig. 2 is surface roughness data measured using a commercially available laser microscope. More specifically, the surface roughness data is acquired at intervals of 1 µm, and as shown in Fig. 2, height (Z direction) data (µm) is stored for each 1 µm pitch in the X and Y directions on the machined surface.

[0028] The surface shape data conversion unit 12 converts the surface shape data acquired by the surface shape data acquisition unit 11 into a matrix. Fig. 3 is a diagram for explaining the conversion of surface roughness data. As shown in Fig. 3, the surface shape data conversion unit 12 converts the surface roughness data into a matrix using coordinates (X, Y, Z) in an XYZ space consisting of an X direction (the direction in which the number of columns increases), a Y direction (the direction in which the number of rows increases), and a Z direction (the height direction) perpendicular to an XY plane defined by these X and Y directions.

[0029] Fig. 4 shows a matrix and mesh of surface roughness data. Specifically, Fig. 4 shows the surface roughness data of Fig. 2 in a matrix form as a graph, and at each vertex of a grid formed by data acquired at 1 μm pitches in both the X and Y directions, data on the Z coordinate in the height direction is stored in addition to the X and Y coordinates. For example, in Fig. 4, the Z coordinate (height) of the vertex whose X coordinate and Y coordinate are 0 is -0.616.

[0030] The mesh partitioning unit 13 divides the machining surface into a plurality of meshes. In the example shown in FIG. 4 , the mesh partitioning unit 13 divides each square grid on the machining surface into two isosceles triangular meshes by dividing each grid into two equal parts. These two meshes are called type 1 mesh and type 2 mesh, respectively. A triangular mesh is preferable as the shape of the mesh, as it is easy to represent the inclination with respect to the XY plane and to perform calculations. However, the shape of the mesh is not particularly limited, and polygons other than triangles can also be used. Furthermore, the shape of all meshes does not need to be the same; meshes of different shapes may be included, or meshes of different areas may be included.

[0031] Here, since the area of ​​the type 1 mesh and the type 2 mesh is very small compared to the entire processing surface, it is assumed that the shape of the reflected light when light is incident on the processing surface from a specific angle is the same. Because BRDF data basically discusses the reflection direction, there is no major problem even if the reflection shape is ignored. Therefore, in this embodiment, it is assumed that the shape of the reflected light is the same for the type 1 mesh and the type 2 mesh, although the direction in which the incident light is reflected is different.

[0032] The specular reflection angle deviation calculation unit 14 calculates the tilt θ of each mesh relative to the XY plane, which is represented by the tilt angle θx in the X direction and the tilt angle θy in the Y direction, based on the surface shape data of the processed surface, and calculates the deviation amount -2θ of the specular reflection angle of each mesh from the calculated tilt θ of each mesh. The calculation of the specular reflection angle deviation -2θ by the specular reflection angle deviation calculation unit 14 will be described in detail below with reference to Figures 5 and 6. Note that the calculation method for the specular reflection angle deviation -2θ is the same for type 1 mesh and type 2 mesh, so the following description will be given taking type 1 mesh (hereinafter simply referred to as mesh) as an example.

[0033] 5 is a diagram showing the inclination of a type 1 mesh relative to the XY plane. If the inclination of the mesh relative to the XY plane is θ, the inclination θ is expressed by the inclination angle θx of the mesh in the X direction and the inclination angle θy of the mesh in the Y direction, as shown in the following mathematical formula (1) using the data acquisition width d. θx is the height of the mesh in the X direction relative to the XY plane, and is calculated by Tan using ΔZx, which is the deviation from the XY plane. －１ (ΔZx / d), and θy is the height of the mesh in the Y direction relative to the XY plane, and is calculated by using ΔZy, which is the deviation from the XY plane, －１ It is expressed as (ΔZy / d).

[0034]

[0035] FIG. 6 is a diagram showing the deviation amount -2θ of the specular reflection angle. Specifically, FIG. 6 is a diagram showing incident light and reflected light viewed from the surface direction of the XY plane, i.e., a direction perpendicular to the Z direction. As shown in FIG. 6, the mesh is tilted at an angle θ with respect to the XY plane. When parallel light is incident on the XY plane at an incident angle φ, the incident angle and specular reflection angle with respect to the mesh are φ-θ. Therefore, the specular reflection angle with respect to the XY plane at this time is φ-2θ, and the deviation amount from the specular reflection angle can be expressed as -2θ. The specular reflection angle deviation calculation unit 14 calculates this deviation amount -2θ of the specular reflection angle for each mesh.

[0036] The BRDF data generator 15 generates three-dimensional BRDF data that represents the amount of reflected light relative to the tilt angle in the X direction and the tilt angle in the Y direction. Specifically, the BRDF data generator 15 adds a constant or a value obtained by multiplying the constant by the area of ​​the mesh to a box corresponding to the calculated deviation amount of the specular reflection angle of each mesh, −2θ, for multiple boxes in an array defined based on the tilt angle in the X direction and the tilt angle in the Y direction of each mesh. In this way, the BRDF data is generated.

[0037] Here, for example, "1" can be used as the constant, which simplifies the calculation. Furthermore, the following are examples of cases where it is preferable to add a value obtained by multiplying a constant by the area of ​​a mesh to the box corresponding to the calculated deviation amount of specular reflection angle -2θ for each mesh. For example, this includes cases where the multiple meshes partitioned by the mesh partitioning unit 13 are not the same shape or area, or where the inclination of the mesh with respect to the XY plane is large and varies greatly, resulting in a large difference between the actual mesh area and the apparent area of ​​the mesh when viewed from above on the machined surface, and where the variation is large and non-uniform. In these cases, adding a value obtained by multiplying a constant by the area of ​​the mesh makes it possible to obtain BRDF data with higher accuracy.

[0038] FIG. 7 is a diagram showing an example of BRDF data according to this embodiment, generated by the BRDF data generation unit 15. In FIG. 7, the horizontal axis is the X axis of the BRDF, and the vertical axis is the Y axis of the BRDF. The X axis of the BRDF is the angle obtained by multiplying the inclination angle of the mesh in the X direction with respect to the XY plane by -2, and represents -2θx. The Y axis of the BRDF is the angle obtained by multiplying the inclination angle of the mesh in the Y direction with respect to the XY plane by -2, and represents -2θy. Both the X axis and the Y axis of the BRDF are arbitrary angles, which may be in increments of 1° or 2°. In the BRDF data array shown in FIG. 7, for example, the value in the top left box is 20. This means that when a constant 1 is added to the box corresponding to the deviation amount of the specular reflection angle of each mesh, −2θ, there are 20 meshes that are oriented in the direction of the deviation amount of the specular reflection angle of −2θ.

[0039] 7, the thick vertical line represents X=0, the thick horizontal line represents Y=0, and the center of the array, which is the intersection of these thick vertical and horizontal lines, represents (X, Y)=(0, 0). Since the array in FIG. 7 represents the distribution of the deviation amount -2θ of the specular reflection angle, the center (0, 0) of this array corresponds to the angle of incidence φ and the angle of specular reflection φ. In other words, in the BRDF data of this embodiment, the angle of incidence can be ignored as 0° in calculations. Note that in this embodiment, as described above, it is assumed that the light reflected from all meshes has the same shape, and in addition, it is assumed that the reflectance is the same even if the angle changes.

[0040] Here, the accuracy of the BRDF data acquired by the BRDF simulation process according to this embodiment will be described below.

[0041] Fig. 8A is a diagram showing an example of a two-dimensional display graph of reflection intensity on a matte-finished surface generated based on the BRDF data according to this embodiment. Fig. 8B is a diagram showing an example of a two-dimensional display graph of reflection intensity on a high-gloss-finished surface generated based on the BRDF data according to this embodiment. Fig. 9A is a diagram showing an example of a three-dimensional display graph of reflection intensity on a matte-finished surface generated based on the BRDF data according to this embodiment. Fig. 9B is a diagram showing an example of a three-dimensional display graph of reflection intensity on a high-gloss-finished surface generated based on the BRDF data according to this embodiment. In all of Figs. 8A, 8B, 9A, and 9B, hatching is applied according to the reflection intensity (light amount), and in all cases, the reflection intensity (light amount) is high near the center.

[0042] 8A and 9A are graphs of the numerical values ​​in boxes of the BRDF data array of this embodiment (see FIG. 7 for an example) acquired on a matte surface of a workpiece, plotted as reflection intensity. 8B and 9B are graphs of the numerical values ​​in boxes of the BRDF data array of this embodiment (see FIG. 7 for an example) acquired on a high-gloss surface of a workpiece, plotted as reflection intensity. 8A and 9A are data for the same matte surface, and 8B and 9B are data for the same high-gloss surface.

[0043] In the two-dimensional graphs of Figures 8A and 8B, the XY coordinates of the center of the graph are (X, Y) = (0, 0), the direction to the right from the center is the +X axis direction, the direction to the left from the center is the -X axis direction, the direction up from the center is the -Y axis direction, and the direction down from the center is the +Y axis direction. In both Figures 8A and 8B, the maximum value of the reflection intensity is near the center, and it can be seen that the matte surface of Figure 8A, which diffuses light more, has a greater spread in reflection intensity than the high-gloss surface of Figure 8B.

[0044] 9A and 9B, the XY coordinates of the center of the graph are (X, Y) = (0, 0), and the height direction perpendicular to the XY plane represents the reflection intensity. In both Figures 9A and 9B, the maximum value of the reflection intensity is near the center, and it can be seen that the matte surface of Figure 9A, which diffuses light more, has a wider range of reflection intensity than the high-gloss surface of Figure 9B.

[0045] Next, the relationship between the gloss and haze calculated based on the BRDF data according to this embodiment and the acquisition width of the surface roughness data will be described.

[0046] Fig. 10 is a diagram showing gloss and haze. Fig. 10 corresponds to the BRDF data array of this embodiment in Fig. 7, and the coordinates of the center of Fig. 10 are (X, Y) = (0, 0). In Fig. 10, the direction to the right from the center is the +X axis direction, the direction to the left from the center is the -X axis direction, the direction upward from the center is the -Y axis direction, and the direction downward from the center is the +Y axis direction.

[0047] Here, gloss is defined as a difference in the tilt angle in the X direction and the tilt angle in the Y direction that is within a range of −1° to +1° when compared with the center (0,0) of the BRDF data array of this embodiment, which corresponds to the specular reflection angle φ. Haze is defined as a difference in the tilt angle in the X direction and the tilt angle in the Y direction that is within a range of −3° to −1° and +1° to +3° when compared with the center (0,0) of the BRDF data array of this embodiment, which corresponds to the specular reflection angle φ.

[0048] Based on the above definitions, gloss and haze are each represented by the hatched areas in Figure 10, and it can be seen that two appear in each of the areas along the X-axis direction and the Y-axis direction. The gloss area along the X-axis direction is called forward gloss, and the gloss area along the Y-axis direction is called perpendicular gloss. Similarly, the haze area along the X-axis direction is called forward haze, and the haze area along the Y-axis direction is called perpendicular haze.

[0049] 11 is a diagram showing the relationship between the gloss and haze calculated based on the BRDF data according to this embodiment and the acquisition width of the surface roughness data. In FIG. 11, the horizontal axis represents the data acquisition width (μm) of the surface roughness data, and the vertical axis represents the gloss / haze. Also, FIG. 11 shows the forward gloss, the perpendicular gloss, the forward haze, and the perpendicular haze, respectively.

[0050] As shown in Figure 11, for all of forward gloss, normal gloss, forward haze, and normal haze, when the acquisition width of surface roughness data exceeds 5 μm, the difference becomes larger compared to when the data acquisition width is 1 μm. This is because the mesh slope is calculated by dividing the data by the increment width (acquisition width), and when the increment width (acquisition width) exceeds 5.0 μm, the mesh slope becomes smaller and the accuracy of the BRDF data decreases. From this result, it can be said that the preferable surface roughness data, taking calculation time into consideration, is surface roughness data in increments of 0.1 μm to 5.0 μm.

[0051] Next, the BRDF simulation results according to this embodiment are compared with the BRDF actual measurement values ​​measured using a conventionally known dedicated BRDF measurement device. Specifically, for the machined surface of the same workpiece, the gloss and haze calculated by the BRDF simulation according to this embodiment are compared with the gloss and haze based on the actually measured BRDF data.

[0052] Here, FIG. 12A is a diagram showing actual measurement results of forward gloss. FIG. 12B is a diagram showing simulation results of forward gloss according to this embodiment. FIG. 13A is a diagram showing actual measurement results of vertical gloss. FIG. 13B is a diagram showing simulation results of vertical gloss according to this embodiment. From these figures, it can be said that the gloss obtained from the BRDF simulation results of this embodiment shows roughly the same overall trends as the actual measured values ​​in both the forward and vertical directions. However, the two show different trends in the details. This is thought to be because the BRDF simulation of this embodiment does not take into account light diffraction, and the actual measured values ​​are attenuated by light being collected and measured using an optical system such as a slit or lens.

[0053] FIG. 14A is a diagram showing the results of actual measurements of forward haze. FIG. 14B is a diagram showing the results of a simulation of forward haze according to this embodiment. FIG. 15A is a diagram showing the results of actual measurements of perpendicular haze. FIG. 15B is a diagram showing the results of a simulation of perpendicular haze according to this embodiment. From these figures, it can be said that the haze obtained from the BRDF simulation results of this embodiment, like the gloss described above, shows roughly the same overall tendency as the actual measurements in both the forward and perpendicular directions. However, the two show different tendencies in the details. This is thought to be because the BRDF simulation of this embodiment does not take into account the diffraction of light, and the actual measurements are measured by focusing light using an optical system such as a slit or lens, which attenuates the light.

[0054] As described above, the BRDF simulation of this embodiment produces results that are comparable to those of the conventional BRDF simulation, but when compared with the actual BRDF measurements, there is room for improvement, as there are tendencies for differences in details, and it can be said that it would be very effective if correlation with the actual measurements could be obtained. Therefore, this embodiment makes it possible to perform a BRDF simulation that takes into account the attenuation effect with respect to the radiation angle.

[0055] Specifically, in this embodiment, the attenuation effect is preferably taken into account using a Gaussian beam, and the BRDF data obtained by simulation is approximated using a Gaussian beam. ０ , y ０ ), the attenuation rate at coordinates (x, y) is expressed by the following formula (2): Note that w in formula (2) is the beam waist, which is the diameter at the position where the light is most narrowed.

[0056]

[0057] Using the above formula (2), we investigated the beam waist w that fits the BRDF measurement device, and found that w = 2 × 2 １／２ Since the specifications of BRDF measurement devices vary from manufacturer to manufacturer, it can be said that the beam waist w is preferably between 1 and 5.

[0058] Fig. 16 is a diagram showing a simulation result of forward gloss considering the Gaussian beam of this embodiment. Fig. 17 is a diagram showing a simulation result of perpendicular gloss considering the Gaussian beam of this embodiment. Fig. 18 is a diagram showing a simulation result of forward haze considering the Gaussian beam of this embodiment. Fig. 19 is a diagram showing a simulation result of perpendicular haze considering the Gaussian beam of this embodiment.

[0059] 16 and 12A (measurement results of forward gloss), 17 and 13A (measurement results of perpendicular gloss), 18 and 14A (measurement results of forward haze), and 19 and 15A (measurement results of perpendicular haze), it can be seen that the BRDF simulation of this embodiment, which takes a Gaussian beam into consideration, has improved the trends that differed in the details compared to the actual measurements for both gloss and haze. Therefore, it can be said that approximating the BRDF data obtained by simulation to a Gaussian beam is effective.

[0060] According to the BRDF simulation of this embodiment described above, it is possible to simulate a BRDF simply by calculating the deviation amount -2θ of the specular reflection angle for the entire machined surface of the workpiece and plotting a histogram based on the tilt angle in the X direction and the tilt angle in the Y direction of each mesh. Therefore, while the amount of calculation and calculation time required for simulating BRDF data have conventionally been enormous, according to this embodiment, the BRDF calculation time can be significantly reduced.

[0061] Specifically, commercially available optical design and analysis software can only divide the mesh up to 2.5 million, and the calculation time for 1 million mesh is as long as 20 minutes. In contrast, the BRDF simulation algorithm of this embodiment allows for extremely fast calculations, with the calculation time for 200 million mesh at the 1 μm level being approximately 10 to 20 minutes. Therefore, it can be said that this algorithm is sufficiently usable even on a general-purpose personal computer.

[0062] Furthermore, in conventional BRDF simulation techniques, the mathematical modeling process using a microfacet normal distribution function NDF, such as the GGX function, includes an averaging process, resulting in low accuracy of the obtained BRDF data. This tendency becomes particularly pronounced when applied to a wide-area machined surface. In contrast, the BRDF simulation according to this embodiment does not involve mathematical modeling using the GGX function or the like, thereby obtaining highly accurate BRDF data.

[0063] Furthermore, with conventional BRDF simulation technology, it is difficult to mathematically model the machined surface, making it difficult to generate a CG image of the machined surface. From the perspective of digital twinning of computer numerical control devices (CNC), which has been actively studied in recent years, there is a demand for a BRDF data simulation technology that can generate high-speed, realistic CG images of the machined surface. According to the BRDF simulation of this embodiment, the arrayed BRDF data enables simple, realistic CG imaging. Therefore, this embodiment can provide a BRDF data simulation technology that can be applied to evaluating the machined surface of a workpiece.

[0064] 1 , the pseudo-gloss / pseudo-haze calculation unit 16 calculates one or both of the pseudo-gloss and pseudo-haze, which will be described later. Furthermore, the evaluation unit 17 performs evaluation of the processed surface based on one or both of the pseudo-gloss and pseudo-haze calculated by the pseudo-gloss / pseudo-haze calculation unit 16. Preferably, the pseudo-gloss / pseudo-haze calculation unit 16 calculates both the pseudo-gloss and pseudo-haze, and the evaluation unit 17 performs evaluation of the processed surface based on both the pseudo-gloss and pseudo-haze.

[0065] As described above, the applicant's research has revealed that when gloss and haze are calculated from BRDF data of a processed surface obtained by simulation, the results do not reflect the actual surface quality visible to the naked eye and are different from visual evaluation. Furthermore, the applicant's research has also revealed that processed surfaces, unlike normal surfaces, have streaks or other imperfections on the surface, which can cause the peak of specular reflection to not appear as a specular reflection angle. Therefore, in this embodiment, the angle at which the reflected light quantity is greatest in the BRDF data is considered to be the specular reflection angle, and gloss and haze are calculated. The gloss and haze calculated in this manner are defined and referred to as pseudo-gloss and pseudo-haze, respectively.

[0066] Fig. 20 is a diagram showing an example of a two-dimensional display graph of gloss and haze according to this embodiment. More specifically, Fig. 20 is a two-dimensional graph of gloss and haze calculated from BRDF data (see Fig. 7) generated by the BRDF simulation according to this embodiment. In Fig. 20, the horizontal dashed line represents the X-axis of the BRDF, and the vertical dashed line represents the Y-axis of the BRDF, with the intersection of these X-axis and Y-axis representing the center (X, Y) = (0, 0). Also, Fig. 20 is hatched according to the reflection intensity.

[0067] In Figure 20, G along the Y-axis direction represents vertical gloss, and H along the Y-axis direction represents vertical haze. G along the X-axis direction represents forward gloss, and H along the X-axis direction represents forward haze. In the example shown in Figure 20, the proportion of vertical gloss, vertical haze, forward gloss, and forward haze is 10.5%, 20.5%, 14.3%, and 31.2%, respectively, relative to the total amount of reflected light. As is clear from Figure 20, the peak of specular reflection is shifted from the center (0,0) (shifted downward in Figure 20), and the peak of specular reflection does not appear at the specular reflection angle.

[0068] In contrast, Fig. 21 is a diagram showing an example of a two-dimensional display graph of pseudo-gloss and pseudo-haze according to this embodiment. More specifically, Fig. 21 is a two-dimensional graph of pseudo-gloss and pseudo-haze calculated based on the BRDF data generated by the BRDF simulation of this embodiment (see Fig. 7), where the angle at which the amount of reflected light is greatest is considered to be the specular reflection angle, and the amount of reflected light at the angle considered to be the specular reflection angle is used as a reference. In Fig. 21, the horizontal dashed line represents the X-axis of the BRDF, and the vertical dashed line represents the Y-axis of the BRDF, with the intersection of these X-axis and Y-axis representing the center (X, Y) = (0, 0). Also, Fig. 21 is hatched according to the reflection intensity.

[0069] In Figure 21, the pseudo-G along the Y-axis direction represents the vertical pseudo-gloss, and the pseudo-H along the Y-axis direction represents the vertical pseudo-haze. The pseudo-G along the X-axis direction represents the forward pseudo-gloss, and the pseudo-H along the X-axis direction represents the forward pseudo-haze. In the example shown in Figure 21, the proportion of the vertical pseudo-gloss, the vertical pseudo-haze, the forward pseudo-gloss, and the forward pseudo-haze are 10.5%, 20.5%, 20.8%, and 30.5%, respectively, relative to the total amount of reflected light. As is clear from Figure 21, the position of the X-axis is shifted downward. This is because the specular reflection peak in Figure 20 was shifted downward from the center (0,0), as described above, and the specular reflection peak position has been moved back to the center (0,0).

[0070] Comparing gloss and haze with pseudo gloss and pseudo haze, it can be seen that the forward gloss ratio is 14.3%, while the forward pseudo gloss ratio has changed to 20.8%. It can also be seen that the forward haze ratio is 31.2%, while the forward pseudo haze ratio has changed to 30.5%. This can also be confirmed by the fact that in Figure 22, which shows pseudo gloss and pseudo haze, the position of the X-axis is shifted downward, and both the forward pseudo gloss region and the forward pseudo haze region are shifted downward.

[0071] FIG. 23 is a diagram showing the relationship between gloss and visual judgment according to this embodiment. Specifically, FIG. 23 examines the relationship between visual judgment by users and gloss (vertical gloss) for 32 workpiece machined surfaces. In FIG. 23, the horizontal axis shows the ranking of users' visual judgments from 1st to 32nd, and the vertical axis shows gloss. As is clear from FIG. 23, it can be seen that the higher the gloss, the better the visual judgment result. In other words, many cases were confirmed in which there was no correlation between gloss and visual judgment, and it can be seen that evaluation of machined surfaces based on gloss may not reflect the surface quality that is actually visible to the naked eye.

[0072] In contrast, FIG. 24 is a diagram showing the relationship between pseudo gloss and visual judgment according to this embodiment. Specifically, like FIG. 23 , FIG. 24 examines the relationship between visual judgment by users and pseudo gloss (vertical pseudo gloss) for 32 workpiece machined surfaces (using the same machined surfaces as in FIG. 23 ). In FIG. 24 , the horizontal axis represents the ranking of users' visual judgments, from 1st to 32nd, and the vertical axis represents pseudo gloss. As is clear from FIG. 24 , the correlation between pseudo gloss and visual judgment is significantly improved compared to the correlation between gloss and visual judgment. Specifically, when the pseudo gloss is 0.17 or higher, i.e., gloss is present, the pseudo gloss and visual judgment are nearly consistent, indicating a high correlation between the two. This is not limited to the vertical pseudo gloss, but also applies to the vertical pseudo haze, forward pseudo gloss, and forward pseudo haze. Therefore, from these results, it can be said that by evaluating the processed surface based on pseudo-gloss and / or pseudo-haze, it is possible to show the surface quality that is actually visible to the naked eye, and highly accurate evaluation results that are approximately consistent with visual evaluation can be obtained.

[0073] When BRDF data is actually measured using specialized equipment, the measurement is currently performed with the center shifted. The same is true for experimental gloss and haze, but in actual experiments, the specular reflection angle is often slightly adjusted to match the maximum specular reflection value with the specular reflection angle. Therefore, it is thought that the values ​​actually obtained may be pseudo-gloss or pseudo-haze. In such cases, the conventional simulation results and measurement results do not match, so it can be said that it is necessary to shift the specular reflection angle (central angle) to the reflection peak.

[0074] Next, the procedure of the machining surface evaluation process according to this embodiment will be described with reference to Fig. 25. Fig. 25 is a flowchart showing the procedure of the machining surface evaluation process according to this embodiment. Note that the machining surface evaluation process according to this embodiment is started by a machining surface evaluation start signal in response to an input operation by a user, etc.

[0075] In step S11, surface shape data is acquired. Specifically, surface shape data such as surface roughness data is acquired by the surface shape data acquisition unit 11. Then, the process proceeds to step S12.

[0076] In step S12, the surface shape data is converted. Specifically, the surface shape data obtained in step S11 is converted into a matrix by the surface shape data conversion unit 12 and graphed (see FIG. 4). Then, the process proceeds to step S13.

[0077] In step S13, the machining surface is divided into a plurality of meshes. Specifically, the machining surface is divided into, for example, triangular meshes by the mesh dividing unit 13. Then, the process proceeds to step S14.

[0078] In step S14, the inclination θ of each mesh relative to the XY plane is calculated. Specifically, the inclination θ of each mesh relative to the XY plane is calculated by the specular reflection angle deviation calculation unit 14. Then, the process proceeds to step S15.

[0079] In step S15, the specular reflection angle deviation amount -2θ of each mesh is calculated. Specifically, the specular reflection angle deviation amount -2θ of each mesh is calculated by the specular reflection angle deviation amount calculation unit 14. Then, the process proceeds to step S16.

[0080] In step S16, BRDF data is generated by adding a constant or the like to a box corresponding to the specular reflection angle deviation of each mesh in an array of angles obtained by multiplying the mesh's X and Y tilt angles by -2. Specifically, the BRDF data generation unit 15 adds a constant or a value obtained by multiplying the constant by the mesh's area to a box corresponding to the specular reflection angle deviation of each mesh in an array defined based on the mesh's X and Y tilt angles. This generates three-dimensional BRDF data that represents the amount of reflected light for the X-direction tilt angle and the Y-direction tilt angle. Then, the process proceeds to step S17.

[0081] In step S17, one or both of pseudo gloss and pseudo haze are calculated based on the BRDF data generated in step S16. Specifically, the pseudo gloss / pseudo haze calculation unit 16 regards the angle at which the amount of reflected light in the BRDF data is greatest as the specular reflection angle, and calculates one or both of pseudo gloss and pseudo haze based on the amount of reflected light at the angle regarded as the specular reflection angle. Then, the process proceeds to step S18.

[0082] In step S18, the processed surface is evaluated. Specifically, the evaluation unit 17 evaluates the processed surface based on one or both of the pseudo gloss and pseudo haze calculated in step S17. Thereafter, this process ends.

[0083] According to the machined surface evaluation device 1 according to the present embodiment described above, the following effects are achieved.

[0084] According to the machined surface evaluation device 1 of this embodiment, in the BRDF data, which is a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on the machined surface of a workpiece, the angle at which the amount of reflected light is greatest is considered to be the specular reflection angle, and the pseudo-gloss and / or pseudo-haze are calculated based on the amount of reflected light at the angle considered to be the specular reflection angle, and the machined surface is evaluated based on the calculated pseudo-gloss and / or pseudo-haze. This makes it possible to show the surface quality that is actually visible to the naked eye, and to obtain highly accurate evaluation results that are approximately consistent with visual evaluation.

[0085] In the above embodiment, the machining surface evaluation device 1 has been described, but a machining surface evaluation method that specifies the above-mentioned machining surface evaluation processing executed by the machining surface evaluation device 1, and a computer program that causes the machining surface evaluation device 1 to execute the above-mentioned machining surface evaluation processing, are also within the scope of the present disclosure.

[0086] Although the present disclosure has been described in detail, the present disclosure is not limited to the individual embodiments described above. Various additions, substitutions, modifications, partial deletions, etc. are possible in these embodiments without departing from the gist of the present disclosure or the spirit of the present disclosure derived from the content of the claims and their equivalents. These embodiments can also be implemented in combination. For example, in the above-described embodiments, the order of each operation and the order of each process are shown as examples and are not limited to these. The same applies when numerical values ​​or mathematical expressions are used in the description of the above-described embodiments.

[0087] The following supplementary note is further disclosed regarding the above embodiment: (Supplementary note 1) A machined surface evaluation device (1) uses BRDF data, which is a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on a machined surface of a workpiece, and the machined surface evaluation device (1) considers the angle at which the amount of reflected light in the BRDF data is greatest to be the specular reflection angle, calculates gloss and / or haze based on the amount of reflected light at the angle considered to be the specular reflection angle, and evaluates the machined surface based on the calculated gloss and / or haze.

[0088] (Supplementary Note 2) In the above-mentioned machined surface evaluation device (1), the BRDF data is BRDF data calculated by simulation. The machined surface evaluation device (1) according to Supplementary Note 1.

[0089] (Supplementary Note 3) In the above-mentioned machined surface evaluation device (1), the BRDF data is three-dimensional BRDF data obtained by dividing the machined surface into a plurality of meshes, calculating an inclination θ of each mesh relative to the XY plane, which is expressed by an inclination angle in the X direction and an inclination angle in the Y direction, based on surface shape data of the machined surface, calculating a deviation amount −2θ of the specular reflection angle of each mesh from the calculated inclination θ of each mesh, and adding a constant or a value obtained by multiplying the constant by the area of ​​the mesh to a box corresponding to the calculated deviation amount −2θ of the specular reflection angle of each mesh, for a plurality of boxes in an arrangement defined based on the inclination angle in the X direction and the inclination angle in the Y direction of each mesh, and representing the amount of reflected light for the inclination angle in the X direction and the inclination angle in the Y direction.

[0090] (Appendix 4) A method for evaluating a machined surface using BRDF data, which is a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on the machined surface of a workpiece, the method comprising: regarding the angle at which the amount of reflected light in the BRDF data is greatest as the specular reflection angle; calculating gloss and / or haze based on the amount of reflected light at the angle considered to be the specular reflection angle; and evaluating the machined surface based on the calculated gloss and / or haze.

[0091] (Appendix 5) A computer program that causes a computer to evaluate a machined surface using BRDF data, which is a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on the machined surface of a workpiece, the computer program considering the angle at which the amount of reflected light in the BRDF data is greatest as the specular reflection angle, calculating gloss and / or haze based on the amount of reflected light at the angle considered to be the specular reflection angle, and causing the computer to evaluate the machined surface based on the calculated gloss and / or haze.

[0092] REFERENCE SIGNS LIST 1 Machined surface evaluation device 11 Surface shape data acquisition unit 12 Surface shape data conversion unit 13 Mesh partition unit 14 Regular reflection angle deviation amount calculation unit 15 BRDF data generation unit 16 Pseudo gloss pseudo haze calculation unit 17 Evaluation unit

Claims

1. A machined surface evaluation device that uses BRDF data, which is a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on the machined surface of a workpiece, which regards the angle in the BRDF data at which the amount of reflected light is greatest as the specular reflection angle, calculates gloss and / or haze based on the amount of reflected light at the angle regarded as the specular reflection angle, and evaluates the machined surface based on the calculated gloss and / or haze.

2. The machined surface evaluation device according to claim 1, wherein the BRDF data is BRDF data calculated by simulation.

3. The machined surface evaluation device according to claim 2, wherein the BRDF data is three-dimensional BRDF data obtained by dividing the machined surface into a plurality of meshes, calculating an inclination θ of each mesh relative to an XY plane, which is expressed by an inclination angle in the X direction and an inclination angle in the Y direction, based on surface shape data of the machined surface, calculating a deviation amount -2θ of the specular reflection angle of each mesh from the calculated inclination θ of each mesh, and adding a constant or a value obtained by multiplying a constant by an area of ​​the mesh into a box corresponding to the calculated deviation amount -2θ of the specular reflection angle of each mesh for a plurality of boxes in an array defined based on the inclination angle in the X direction and the inclination angle in the Y direction of each mesh, and expressing the amount of reflected light for the inclination angle in the X direction and the inclination angle in the Y direction.

4. A method for evaluating a machined surface using BRDF data, which is a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on the machined surface of a workpiece, comprising: considering the angle in the BRDF data at which the amount of reflected light is greatest as the specular reflection angle; calculating gloss and / or haze based on the amount of reflected light at the angle considered to be the specular reflection angle; and evaluating the machined surface based on the calculated gloss and / or haze.

5. A computer program that causes a computer to evaluate a machined surface using BRDF data, which is a bidirectional reflectance distribution function that represents the angular distribution characteristics of reflected light when light is incident on the machined surface of a workpiece, and that regards the angle in the BRDF data at which the amount of reflected light is greatest as the specular reflection angle, calculates gloss and / or haze based on the amount of reflected light at the angle regarded as the specular reflection angle, and causes the computer to evaluate the machined surface based on the calculated gloss and / or haze.