Grinding wheel three-dimensional landform measurement method and system based on silica gel copying and density clustering

Abstract

The invention discloses a grinding wheel three-dimensional landform measuring method and system based on silica gel copying and density clustering, and belongs to the technical field of precision machining.The measuring system comprises a grinding wheel landform copying device used for copying the landform of a to-be-detected area of a grinding wheel to obtain a grinding wheel landform copy; the three-dimensional measuring device is used for measuring the three-dimensional shape of the surface of the grinding wheel landform copy; the computer processing device is used for operating a three-dimensional data processing algorithm; and the three-dimensional data processing system is used for carrying out denoising and feature extraction on the three-dimensional shape of the grinding wheel based on a three-dimensional data processing algorithm. The problems that a large-size grinding wheel is difficult to directly detect, the geomorphic measurement noise of a fine-grained grinding wheel is large, and the abrasive particle recognition precision is poor are solved.

Description

Technical Field

[0001] This invention belongs to the field of precision machining technology, specifically relating to a method and system for measuring three-dimensional terrain using grinding wheels based on silicone copying and density clustering. Background Technology

[0002] Grinding wheels are widely used in precision and ultra-precision grinding of hard and brittle materials such as glass, ceramics, and cemented carbide due to their advantages of high surface quality, good wear resistance, and high processing efficiency. The microscopic topographic parameters of the grinding wheel, such as the tip height and abrasive grain density, directly affect the grinding force and material removal method, decisively influencing the final surface quality and serving as important reference factors for changes in surface morphology before and after wheel dressing. However, because the diameter of grinding wheels used in actual grinding is often large, it is difficult to fit the entire wheel into a high-precision measuring instrument to measure its topography. Furthermore, the randomness of abrasive grain shape, tip height, and distribution position leads to complex surface morphology and difficulty in abrasive grain identification. Therefore, high-precision detection of the topographic features of fine-grained grinding wheels has always been a crucial problem that the grinding field hopes to solve.

[0003] Many scholars have conducted relevant research on grinding wheel topography measurement. Luo et al. (LUO F, RENY, CHEN G, et al. Effect of surface topography of fiber laser dressed resin-bond diamond wheel on its grinding performance [J]. The International Journal of Advanced Manufacturing Technology, 2023, 127(7-8): 3427–40.) used ultra-depth-of-field microscopy to obtain the three-dimensional surface morphology of a laser-dressed resin-bonded diamond grinding wheel (200#), and obtained the variation law of abrasive grain tip height with laser dressing parameters. However, the measurement accuracy of the depth-of-field synthesis method is limited, making it difficult to achieve micron-level topographic feature measurement of fine-grained grinding wheels. Yan Lan et al. (YAN L, RONG YM, JIANG F, et al. Three-dimensional surface characterization of grinding wheel using white light interferometer [J]. The International Journal of Advanced Manufacturing Technology, 2010, 55(1-4): 133–41.) used a white light interferometer to measure the surface topography of alumina grinding wheels and calculated three-dimensional surface parameters such as abrasive density, abrasive sharpness, and chip space. Huo Fengwei et al. (HUO F, GUO D, KANG R, et al. Characteristics of the Wheel Surface Topography in Ultra-precision Grinding of Silicon Wafers; proceedings of the 11th International Symposium on Advances in Abrasive Technology, Awaji City, JAPAN, F Sep 30–Oct 03) measured the surface morphology of a 3000# diamond grinding wheel based on a high-resolution scanning white light interferometer and derived the abrasive grain tip height and effective abrasive grain density.Although current grinding wheel topography measurement and parametric evaluation technologies have made significant progress in acquiring three-dimensional contour data and characterizing parameters such as abrasive grain tip height, problems still exist, such as the difficulty in directly detecting large-size grinding wheels, high noise in fine-grained grinding wheel topography measurement, and poor abrasive grain identification accuracy. Summary of the Invention

[0004] This invention provides a method and system for measuring three-dimensional terrain of grinding wheels based on silicone copying and density clustering. The purpose is to address the problems of large-size grinding wheels being difficult to detect directly, high noise in terrain measurement of fine-grained grinding wheels, and poor accuracy in abrasive grain identification.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A three-dimensional geomorphological measurement system based on silicone copying and density clustering using grinding wheels includes: A grinding wheel terrain copying device is used to copy the terrain of the area to be inspected by the grinding wheel, and obtain a grinding wheel terrain copy. A three-dimensional measuring device for measuring the three-dimensional morphology of the surface of a grinding wheel topographic copy; Computer processing unit, used to run three-dimensional data processing algorithms; The three-dimensional data processing system uses three-dimensional data processing algorithms to denoise and extract features from the three-dimensional morphology of grinding wheels.

[0006] A further improvement of the present invention is that the grinding wheel landform copying device consists of a silicone-based material and a copying mold. The copying mold is fixed at the sampling position of the grinding wheel. When the silicone-based material is poured into the copying mold, a copy of the grinding wheel landform can be obtained after it solidifies.

[0007] A further improvement of this invention is that the three-dimensional measuring device is a laser confocal microscope, which can obtain the three-dimensional morphology of the surface of the grinding wheel terrain copy. ,in Indicates the position as The height value at that location.

[0008] A further improvement of the present invention is that the computer processing device is a computer.

[0009] A further improvement of the present invention is that the three-dimensional data processing system includes: The preprocessing module is used to fit the 3D data and correct the tilt and 3D data with initial surface curvature to a plane; The burr identification, cleaning, and data repair module is used to identify, clean, and recalculate burr data in the 3D data. Burr cleaning refers to identifying and deleting outliers that deviate from the main body of the 3D data. Data repair refers to refilling the deleted data back into the 3D data according to a preset calculation method. The automatic filtering module automatically sets the filter cutoff frequency based on the characteristics of the three-dimensional data to filter out high-frequency signals; The abrasive grain identification module identifies protruding abrasive grains by density clustering. Protruding abrasive grains refer to abrasive grains in the grinding wheel topography that are higher than the binder. The edge protrusion height evaluation module is used to calculate the height value of the edge protrusion abrasive grains and their probability distribution.

[0010] A three-dimensional geomorphological measurement method based on silicone copying and density clustering using grinding wheels includes the following steps: The grinding wheel terrain copying device copies the terrain of the area to be inspected by the grinding wheel, thus obtaining a grinding wheel terrain copy; A three-dimensional measuring device is used to measure the three-dimensional morphology of the surface of a grinding wheel geomorphological copy. The computer processing unit executes the three-dimensional data processing algorithm; The three-dimensional data processing system uses three-dimensional data processing algorithms to denoise and extract features from the three-dimensional shape of the grinding wheel.

[0011] A further improvement of the present invention is that the three-dimensional data processing system includes: The preprocessing module fits the 3D data and corrects the tilt and 3D data with a set surface curvature to a plane; The burr identification, cleaning, and data repair module is used to identify, clean, and recalculate burr data in the 3D data. Burr cleaning refers to identifying and deleting outliers that deviate from the main body of the 3D data. Data repair refers to refilling the deleted data back into the 3D data according to a preset calculation method. The automatic filtering module automatically sets the filter cutoff frequency based on the characteristics of the three-dimensional data to filter out high-frequency signals; The abrasive grain identification module identifies protruding abrasive grains by density clustering. Protruding abrasive grains refer to abrasive grains in the grinding wheel topography that are higher than the binder. The edge protrusion height evaluation module calculates the height value of the abrasive grains protruding from the edge and their probability distribution.

[0012] A further improvement of this invention is that the method for fitting three-dimensional data refers to using a cubic polynomial. The three-dimensional data is fitted, and the calculation formula is shown in (1):

[0013] Among them, These are the fitting coefficients. p , q yes x and y The power of , satisfying p , q ≥0 and p + qLess than or equal to 3 ; The method for correcting 3D data to a plane is to subtract the height of that location, fitted by a cubic polynomial, from the height of each position in the original 3D data, thus obtaining the corrected 3D data. The calculation formula is shown in (2):

[0014] A further improvement of this invention is that the method for burr identification and cleaning refers to calculating the corrected three-dimensional data. mean with standard deviation σ The calculation formulas are shown in (3) and (4):

[0015] The values ​​of M and N are determined by the sampling size of the three-dimensional shape data. , ; greater than or less than Data is labeled as burrs And delete it;

[0016] in, This represents the upper boundary of the labeled data, i.e., beyond the mean. Plus three standard deviations σ Data other than; This represents the lower boundary of the labeled data, i.e., beyond the mean. Subtract three standard deviations σ Data other than; This indicates that the data is marked as a glitch. This indicates that the data is non-glitch; Data repair refers to the calculation of data marked as glitch. Maximum of 15 around The mean of the non-spurious data within a 15-neighborhood is used, and this mean is filled into the locations of the data identified as spurs to obtain the 3D data after spur cleaning and repair. .

[0017] A further improvement of this invention lies in that the automatic filtering method calculates the three-dimensional data after burr cleaning and repair. The power spectral density requires, first, the three-dimensional data to be processed. Perform Fourier transform to obtain The calculation formula is shown in (6):

[0018] In the formula, The expression is:

[0019] in, , , They are along Spatial frequency of direction, It is the physical sampling interval of discrete points, in μm; The power spectral density is the squared value of the Fourier transform of the original data, which, after normalization, can be expressed in terms of a unit area ( Power spectral density under ) The calculation formula is shown in (8):

[0020] The frequency at the top 5% of the power spectral density is set as the cutoff frequency. And perform a low-pass filter based on the cutoff frequency. The filtered three-dimensional data is obtained. ; The abrasive grain identification method uses the density clustering algorithm DBSCAN. The abrasive grain diameter is set as the neighborhood radius of the clustering algorithm. The top 5% of the peak data in the filtered 3D data are clustered, thus classifying similar, clustered peak signals within a defined range as edge-exit peak data caused by the same abrasive grain in that region. ; The method for evaluating the cutting edge height involves calculating the mean of the cutting edge peak data and using it as the cutting edge height of the grinding wheel topography. Statistical analysis of the cutting edge peak data is then performed to obtain the probability density distribution.

[0021] Compared with the prior art, the present invention has at least the following beneficial technical effects: I. This invention utilizes silicone copying technology to locally copy large-size grinding wheel topography, breaking through the limitations of traditional high-precision measuring equipment on the size of the sample to be tested, and can obtain surface topography data non-destructively and efficiently.

[0022] Second, by combining statistical glitch removal with power spectral density-based low-pass filtering, this invention can efficiently remove abnormal data and high-frequency background noise in three-dimensional data while minimizing damage to the original data.

[0023] Third, this invention introduces density clustering algorithm into the neighborhood of abrasive grain feature recognition of grinding wheels, which can effectively solve the problem of repeated abrasive grain statistics caused by multiple peaks on the same abrasive grain surface.

[0024] This invention overcomes the limitations of traditional measuring equipment for large-size grinding wheels by utilizing high-precision measurements with silicone photocopying and laser confocal microscopy, enabling non-destructive and efficient acquisition of grinding wheel surface morphology data. By employing an automatic power spectral density filtering method and density clustering algorithm, noise is effectively removed and abrasive grain characteristics are enhanced, significantly improving the accuracy of abrasive grain identification and the automation of data processing, resulting in more precise measurement results. Compared to traditional measurement methods, this invention provides a more stable and accurate grinding wheel morphology characterization technology. This invention can be widely applied to the quality inspection and performance optimization of fine-grained diamond grinding wheels, playing a positive role in improving the accuracy of grinding wheel surface morphology detection. Attached Figure Description

[0025] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of the main steps of the present invention; Figure 2 This is a schematic diagram of a grinding wheel terrain copying device; Figure 3 A schematic diagram of three-dimensional data of grinding wheel topography obtained using a three-dimensional measuring device; Figure 4 This is a schematic diagram of the three-dimensional data after correction using a cubic polynomial; Figure 5 This is a schematic diagram of burr identification in 3D data; Figure 6 A schematic diagram of the 3D data after removing burrs and performing data repair. Figure 7 The diagram illustrates the settings for the power spectral density image and cutoff frequency of three-dimensional data. Figure 8 This is a schematic diagram of three-dimensional data after low-pass filtering based on the cutoff frequency; Figure 9 (a) is a schematic diagram showing the marked positions of the top 5% of the peaks in the three-dimensional data. Figure 9 (b) is a schematic diagram of the peak position marking after abrasive grain identification using a clustering algorithm; Figure 10 This is a schematic diagram of the statistical results of the abrasive grain protrusion height identified by the clustering algorithm; Figure 11 It is the original scan morphology of the silicone mold made by the grinding wheel; Figure 12 It is the corrected tilted grinding wheel landform; Figure 13 This is a schematic diagram of burr points identified based on statistics; Figure 14 This is a schematic diagram of filling the burr removal area based on the extended neighborhood method; Figure 15 This is a diagram illustrating automatic cutoff frequency finding based on PSD. Figure 16 This is a schematic diagram of an adaptive Gaussian filter; Figure 17 This is a schematic diagram of the wave crest distribution on the surface of the grinding wheel before clustering; Figure 18 This is a schematic diagram of the wave crest distribution on the surface of the grinding wheel after clustering; Figure 19 It is a probability density diagram of the height difference between each point on the grinding wheel and the base surface; Figure 20 It is a probability density map of the height difference between the peak and the base plane after clustering.

[0027] Explanation of reference numerals in the attached figures: 1 is the grinding wheel being tested, 2 is the copying mold, 3 is the silicone material, 4 is the burr data, and 5 is the wave peak mark. Detailed Implementation

[0028] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0029] In the description of this invention, it should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0030] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0031] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0032] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0033] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0034] Example 1 like Figure 1 As shown, the present invention provides a three-dimensional terrain measurement system for grinding wheels based on silicone copying and density clustering, which achieves local non-destructive testing of large-size grinding wheels using a laser confocal microscope. Addressing the problems of numerous abnormal burrs and high-frequency noise in laser-measured three-dimensional data, a combination of statistical burr removal and adaptive PSD filtering is proposed. This method eliminates the need for manual threshold setting and automatically adjusts based on the characteristics and distribution of the three-dimensional data, effectively overcoming noise interference. Furthermore, the application of density clustering algorithms to abrasive grain identification effectively improves the problem of repeated abrasive grain identification, thereby significantly enhancing the accuracy of abrasive grain identification and statistical analysis. This achieves a novel high-precision non-destructive testing technology for the cutting edge height and density of fine-grained diamond grinding wheels.

[0035] like Figure 1 As shown, the grinding wheel topography measurement system of the present invention includes: A grinding wheel terrain copying device is used to copy the terrain of the area to be inspected by the grinding wheel, and obtain a grinding wheel terrain copy. A three-dimensional measuring device for measuring the three-dimensional morphology of the surface of a grinding wheel topographic copy; Computer processing unit, used to run three-dimensional data processing algorithms; The three-dimensional data processing system uses three-dimensional data processing algorithms to denoise and extract features from the three-dimensional morphology of grinding wheels.

[0036] Furthermore, the aforementioned grinding wheel terrain copying device, as... Figure 2 As shown, the grinding wheel landform copying device consists of a silicone-based material and a copying mold. The copying mold is fixed at the sampling position of the grinding wheel. The silicone-based material is poured into the copying mold, and after solidification, a grinding wheel landform copy can be obtained.

[0037] Furthermore, the three-dimensional measuring device is a laser confocal microscope, which can obtain images of silicone photocopies such as... Figure 3 The three-dimensional data shown ,in Indicates the position as The height value at the specified location, and the aforementioned three-dimensional data, can be imported into a computer processing device for processing.

[0038] Furthermore, the computer processing device is a computer used to process three-dimensional data according to the data processing system of the present invention.

[0039] Furthermore, the aforementioned three-dimensional data processing system includes a preprocessing module for fitting three-dimensional data and correcting tilted or tilted three-dimensional data with a set surface curvature to a plane; a burr identification, cleaning, and data repair module, wherein burr cleaning refers to identifying and deleting outliers that deviate from the main body of the three-dimensional data within a certain range, and data repair refers to refilling the deleted data back into the three-dimensional data according to a preset calculation method, used to identify, remove, and recalculate burr data in the three-dimensional data; an automatic filtering module, wherein the automatic filtering module automatically sets the filter cutoff frequency to filter out high-frequency signals based on the characteristics of the three-dimensional data; an abrasive grain identification module, wherein the abrasive grain identification module identifies the cutting edge abrasive grains by density clustering, wherein the cutting edge abrasive grains are abrasive grains higher than the binder in the grinding wheel topography; and a cutting edge height evaluation module, wherein the cutting edge height module calculates the height value of the cutting edge abrasive grains and its probability distribution.

[0040] Example 2 The present invention provides a method for measuring three-dimensional terrain using a grinding wheel based on silicone copying and density clustering, comprising the following steps: The grinding wheel terrain copying device copies the terrain of the area to be inspected by the grinding wheel, thus obtaining a grinding wheel terrain copy; A three-dimensional measuring device is used to measure the three-dimensional morphology of the surface of a grinding wheel geomorphological copy. The computer processing unit executes the three-dimensional data processing algorithm; The three-dimensional data processing system uses three-dimensional data processing algorithms to denoise and extract features from the three-dimensional shape of the grinding wheel.

[0041] Furthermore, the method for fitting three-dimensional data refers to using a cubic polynomial. The three-dimensional data is fitted, and the calculation formula is shown in (1):

[0042] Among them, These are the fitting coefficients. p , q yes x and y The power of , satisfying p , q ≥0 and p + q Less than or equal to 3 .

[0043] The method for correcting 3D data to a plane involves subtracting the height of each position in the original 3D data from the height fitted by a cubic polynomial at that position, thus obtaining the result as shown below. Figure 4 The corrected 3D data shown The calculation formula is shown in (2):

[0044] Furthermore, the aforementioned method for burr identification and cleaning refers to calculating the corrected three-dimensional data. mean The formulas for calculating the standard deviation σ are shown in (3) and (4):

[0045] The values ​​of M and N are determined by the sampling size of the three-dimensional shape data. , ; greater than or less than Data is labeled as burrs And delete it.

[0046]

[0047] in, This represents the upper boundary of the labeled data, i.e., beyond the mean. Plus three standard deviations σ Data other than; This represents the lower boundary of the labeled data, i.e., beyond the mean. Subtract three standard deviations σ Data other than; This indicates that the data is marked as a glitch. This indicates that the data is non-bursting.

[0048] The data repair mentioned above refers to calculating data marked as glitch. Maximum of 15 around The mean of the non-spiculated data within a 15-neighborhood is used, and this mean is filled into the data positions identified as spiculated, resulting in the following: Figure 6 The 3D data shown is after burr cleaning and repair. .

[0049] Furthermore, the automatic filtering method involves calculating the 3D data after burr cleaning and repair. The power spectral density requires, first, the three-dimensional data to be processed. Perform Fourier transform to obtain The calculation formula is shown in (6):

[0050] In the formula, The expression is:

[0051] in, , , They are along Spatial frequency of direction, It is the physical sampling interval of discrete points, in μm; The power spectral density is the squared value of the Fourier transform of the original data, which, after normalization, can be expressed in terms of a unit area ( Power spectral density under ) The calculation formula is shown in (8):

[0052] like Figure 7 As shown, the frequencies at the top 5% of the power spectral density are set as the cutoff frequencies. And perform a low-pass filter based on the cutoff frequency. , to obtain Figure 8 The filtered 3D data shown .

[0053] Furthermore, the aforementioned abrasive grain identification method refers to using the density clustering algorithm DBSCAN, setting the abrasive grain diameter as the neighborhood radius of the clustering algorithm, and clustering the top 5% of the peak data in the filtered 3D data, thereby identifying abrasive grains... Figure 9 (a) shows a cluster of similar, clustered peak signals within a certain range, as follows: Figure 9 (b) Data on the exit peak caused by the same abrasive grain in this region .

[0054] Furthermore, the method for evaluating the cutting edge height refers to calculating the mean of the cutting edge peak data and using it as the cutting edge height of the grinding wheel topography, and then performing statistical analysis on the cutting edge peak data to obtain, as shown below. Figure 10 The probability density distribution shown is shown.

[0055] Example 3 This invention utilizes high-precision molding silicone (E610, Shenzhen Hongyejie Technology Co., Ltd., China) to perform high-precision copying of the microscopic morphology of grinding wheel surfaces. Components A and B are mixed in a 1:1 ratio and stirred thoroughly. The mixture is then placed in a vacuum drying oven to remove internal micro-air bubbles, preventing cavities from remaining on the surface of the copied part after molding. The mold is then placed in a resin-based mold that conforms to the grinding wheel surface. After curing, the mold is removed. Because the mold size is significantly smaller than the grinding wheel itself, it can be easily placed in high-precision measuring equipment such as a laser confocal microscope. The object measured is a resin-based D7 circular arc diamond grinding wheel (D7KC75, Saint-Gobain Winter, Germany), with a diameter of Φ150mm, an arc radius of 35mm, and a width of 20mm. Three-dimensional data of the grinding wheel's topography are obtained using a laser confocal microscope (OLS4000, OLYMPUS, Japan) in laser observation mode. After replicating the morphology of a resin-bonded circular diamond grinding wheel with a particle size of D7 using a wheel mold, the surface three-dimensional morphology was observed under a 20x objective lens using a laser confocal microscope, as shown below. Figure 11 As shown, the field of view area is ,total Each sampling point has a horizontal and vertical spacing of 0.629 μm between each pixel. After obtaining the 3D data of the grinding wheel terrain replica, this invention first corrects the measured grinding wheel terrain using a cubic polynomial fitting surface to obtain... Figure 12 The 3D image shown contains numerous burrs. Burr data identified using the 3σ principle is as follows: Figure 13 As shown, after completing and removing data using the extended neighborhood method, as... Figure 14 As shown, the data quality has been significantly improved, but it still contains a lot of high-frequency noise. The power spectral density plot calculated based on the power spectral density (PSD) function and the cutoff frequency are shown below. Figure 15 As shown, adaptive filtering of the terrain based on the cutoff frequency removes burrs and noise from the grinding wheel terrain data. Figure 16 As shown. To identify abrasive grains and statistically analyze their cutting edge height and abrasive grain density, since a single abrasive grain often exhibits multiple local peaks, a suitable feature selection method is needed to merge the peaks at the abrasive grain level. This invention employs the density-based spatial clustering (DBSCAN) algorithm, whose core parameters are the neighborhood radius ε and the minimum number of neighborhood points minPts. For each data sample, DBSCAN calculates the number of samples within its ε-neighborhood. If the number is greater than or equal to minPts, the sample is considered a core sample. The algorithm starts from any core point, expands the clustering through density reachability relationships, and groups density-reachable points into the same cluster. The sample set uses the pre-screened peak coordinate set as input, and its neighborhood radius ε is set according to half the upper limit of the abrasive grain diameter. The grinding wheel used in this invention is a D7 diamond grinding wheel, and its abrasive grain diameter... The size is 5-10 μm, and the physical size of each pixel grid in the laser confocal microscope used is... The value is 0.629 μm, so the neighborhood radius ε is set to 5 pixels, slightly larger than the maximum abrasive grain radius. The minimum cluster size minPts is set to 1, allowing single-point clusters. The peak data labeling before clustering is as follows: Figure 17 As shown, there is obvious clustering and overlap, and the peak data after clustering is labeled as follows. Figure 18 As shown, the overlap phenomenon is significantly improved. Finally, the processed three-dimensional terrain height distribution of the grinding wheel is statistically analyzed as follows: Figure 19 The distribution of abrasive grain exit heights, as shown in the figure, corresponds to the extraction of representative peaks from each cluster. Figure 20 As shown, the height distribution basically conforms to a normal distribution, indicating that the grinding wheel has a good topography and the abrasive grains have not been dulled, which is why the right end of the distribution map is truncated.

[0056] The original image had many burrs, was tilted, and had indistinct abrasive grain features. After correction, deburring, and filtering, the final image was basically burr-free, with clear surface features of the grinding wheel and distinct abrasive grain boundaries. It was able to distinguish the abrasive grains of varying heights and the bonding material on the grinding wheel surface, thus verifying the effectiveness of the invention.

[0057] The inventive points protected by this invention are as follows: I. This invention utilizes silicone copying technology to locally copy large-size grinding wheel landforms, breaking through the limitations of traditional high-precision measuring equipment on the size of the sample to be tested.

[0058] Second, by combining statistical glitch removal with power spectral density-based low-pass filtering, this invention can efficiently remove abnormal data and high-frequency background noise in three-dimensional data while minimizing damage to the original data.

[0059] Third, this invention introduces density clustering algorithm into the neighborhood of abrasive grain feature recognition of grinding wheels, which can effectively solve the problem of repeated abrasive grain statistics caused by multiple peaks on the same abrasive grain surface.

[0060] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0061] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A three-dimensional geomorphological measurement system for grinding wheels based on silicone copying and density clustering, characterized in that, include: A grinding wheel terrain copying device is used to copy the terrain of the area to be inspected by the grinding wheel, and obtain a grinding wheel terrain copy. A three-dimensional measuring device for measuring the three-dimensional morphology of the surface of a grinding wheel topographic copy; Computer processing unit, used to run three-dimensional data processing algorithms; The three-dimensional data processing system uses three-dimensional data processing algorithms to denoise and extract features from the three-dimensional morphology of grinding wheels.

2. The grinding wheel three-dimensional terrain measurement system based on silicone copying and density clustering according to claim 1, characterized in that, The grinding wheel landform copying device consists of a silicone-based material and a copying mold. The copying mold is fixed at the sampling position of the grinding wheel. When the silicone-based material is poured into the copying mold, a copy of the grinding wheel landform is obtained after it solidifies.

3. The grinding wheel three-dimensional terrain measurement system based on silicone copying and density clustering according to claim 1, characterized in that, The three-dimensional measurement device is a laser confocal microscope, which can obtain the three-dimensional morphology of the surface of a grinding wheel topographic copy. ,in Indicates the position as The height value at that location.

4. The grinding wheel three-dimensional terrain measurement system based on silicone copying and density clustering according to claim 1, characterized in that, The computer processing device is a computer.

5. The grinding wheel three-dimensional terrain measurement system based on silicone copying and density clustering according to claim 1, characterized in that, The three-dimensional data processing system includes: The preprocessing module is used to fit the 3D data and correct the tilt and 3D data with initial surface curvature to a plane; The burr identification, cleaning, and data repair module is used to identify, clean, and recalculate burr data in the 3D data. Burr cleaning refers to identifying and deleting outliers that deviate from the main body of the 3D data. Data repair refers to refilling the deleted data back into the 3D data according to a preset calculation method. The automatic filtering module automatically sets the filter cutoff frequency based on the characteristics of the three-dimensional data to filter out high-frequency signals; The abrasive grain identification module identifies protruding abrasive grains by density clustering. Protruding abrasive grains refer to abrasive grains in the grinding wheel topography that are higher than the binder. The edge protrusion height evaluation module is used to calculate the height value of the edge protrusion abrasive grains and their probability distribution.

6. A method for measuring three-dimensional terrain using a grinding wheel based on silicone copying and density clustering, characterized in that, Includes the following steps: The grinding wheel terrain copying device copies the terrain of the area to be inspected by the grinding wheel, thus obtaining a grinding wheel terrain copy; A three-dimensional measuring device is used to measure the three-dimensional morphology of the surface of a grinding wheel geomorphological copy. The computer processing unit executes the three-dimensional data processing algorithm; The three-dimensional data processing system uses three-dimensional data processing algorithms to denoise and extract features from the three-dimensional shape of the grinding wheel.

7. The method for three-dimensional terrain measurement using a grinding wheel based on silicone copying and density clustering according to claim 6, characterized in that, The three-dimensional data processing system includes: The preprocessing module fits the 3D data and corrects the tilt and 3D data with a set surface curvature to a plane; The burr identification, cleaning, and data repair module is used to identify, clean, and recalculate burr data in the 3D data. Burr cleaning refers to identifying and deleting outliers that deviate from the main body of the 3D data. Data repair refers to refilling the deleted data back into the 3D data according to a preset calculation method. The automatic filtering module automatically sets the filter cutoff frequency based on the characteristics of the three-dimensional data to filter out high-frequency signals; The abrasive grain identification module identifies protruding abrasive grains by density clustering. Protruding abrasive grains refer to abrasive grains in the grinding wheel topography that are higher than the binder. The edge protrusion height evaluation module calculates the height value of the abrasive grains protruding from the edge and their probability distribution.

8. The method for measuring three-dimensional terrain using a grinding wheel based on silicone copying and density clustering according to claim 7, characterized in that, The method of fitting three-dimensional data refers to using cubic polynomials. The three-dimensional data is fitted, and the calculation formula is shown in (1): Among them, These are the fitting coefficients. p , q yes x and y The power of , satisfying p , q ≥0 and p + q Less than or equal to 3 ; The method for correcting 3D data to a plane is to subtract the height of that location, fitted by a cubic polynomial, from the height of each position in the original 3D data, thus obtaining the corrected 3D data. The calculation formula is shown in (2): 。 9. The method for measuring three-dimensional terrain using a grinding wheel based on silicone copying and density clustering according to claim 7, characterized in that, The method for burr identification and cleaning refers to calculating the corrected three-dimensional data. mean with standard deviation σ The calculation formulas are shown in (3) and (4): The values ​​of M and N are determined by the sampling size of the three-dimensional shape data. , ; greater than or less than Data is labeled as burrs And delete it; in, This represents the upper boundary of the labeled data, i.e., beyond the mean. Plus three standard deviations σ Data other than; This represents the lower boundary of the labeled data, i.e., beyond the mean. Subtract three standard deviations σ Data other than; This indicates that the data is marked as a glitch. This indicates that the data is non-glitch; Data repair refers to the calculation of data marked as glitch. Maximum of 15 around The mean of the non-spurious data within a 15-neighborhood is used, and this mean is filled into the locations of the data identified as spurs to obtain the 3D data after spur cleaning and repair. .

10. The method for measuring three-dimensional terrain using a grinding wheel based on silicone copying and density clustering according to claim 7, characterized in that, The automatic filtering method calculates the 3D data after burr cleaning and repair. The power spectral density requires, first, the three-dimensional data to be processed. Perform Fourier transform to obtain The calculation formula is shown in (6): In the formula, The expression is: in, , , They are along Spatial frequency of direction, It is the physical sampling interval of discrete points, in μm; The power spectral density is the squared value of the Fourier transform of the original data, which, after normalization, can be expressed in terms of a unit area ( Power spectral density under ) The calculation formula is shown in (8): The frequency at the top 5% of the power spectral density is set as the cutoff frequency. And perform a low-pass filter based on the cutoff frequency. The filtered three-dimensional data is obtained. ; The abrasive grain identification method uses the density clustering algorithm DBSCAN. The abrasive grain diameter is set as the neighborhood radius of the clustering algorithm. The top 5% of the peak data in the filtered 3D data are clustered, thus classifying similar, clustered peak signals within a defined range as edge-exit peak data caused by the same abrasive grain in that region. ; The method for evaluating the cutting edge height involves calculating the mean of the cutting edge peak data and using it as the cutting edge height of the grinding wheel topography. Statistical analysis of the cutting edge peak data is then performed to obtain the probability density distribution.

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