阅读说明：本技术 一种基于表面微观三维形貌的最小加工余量预测方法 (Minimum machining allowance prediction method based on surface microscopic three-dimensional morphology ) 是由 闫宁 陆静 赵延军 徐西鹏 姜峰 王宁昌 徐帅 吴晓磊 于 2020-06-08 设计创作，主要内容包括：本发明公开了一种基于表面微观三维形貌的最小加工余量预测方法,首先将需要加工的样品在提前设定好参数的白光干涉仪上进行三维形貌的检测,得到三维形貌检测图和测量数据,对每个测量区域得到的测量数据均进行表面重构并分别计算重构后每个测量区域表面最高点和最低点之间的材料体积V,取所有测量区域的材料体积的平均值,作为需要去除的材料余量体积V<Sub>1</Sub>,根据测量区域的面积以及需要去除的材料余量体积V<Sub>1</Sub>计算得到整个加工区域需要去除的材料体积。本发明提供的预测方法能对精密超精密加工中下一道材料需要去除的材料体积进行预测,还能用于光电、半导体材料加工流程中研磨、磨削等工序加工量的预估,应用范围广。(The invention discloses a minimum machining allowance prediction method based on surface microscopic three-dimensional topography, which comprises the steps of firstly, detecting the three-dimensional topography of a sample to be machined on a white light interferometer with preset parameters to obtain a three-dimensional topography detection graph and measurement data, carrying out surface reconstruction on the measurement data obtained in each measurement area, respectively calculating the material volume V between the highest point and the lowest point of the surface of each measurement area after reconstruction, and taking the average value of the material volumes of all the measurement areas as the material allowance volume V to be removed 1 According to the area of the measuring area and the residual volume V of the material to be removed 1 Calculating to obtain the material body to be removed in the whole processing areaAnd (4) accumulating. The prediction method provided by the invention can predict the volume of the material to be removed in the next material in the precise ultra-precision machining, can also be used for predicting the machining amount of grinding, grinding and other procedures in the photoelectric and semiconductor material machining processes, and has wide application range.)

1. A minimum machining allowance prediction method based on surface microscopic three-dimensional morphology is characterized by comprising the following steps: the method comprises the following steps:

a. placing a sample to be processed on a white light interferometer, selecting a multiple and a resolution according to the roughness of the sample, determining the requirement of the selected multiple and resolution to obtain the surface roughness and waviness information of the sample, and then entering the next step;

b. selecting a sampling area as a measurement area according to the area of the test visual field under the selected specific multiple and resolution and the size of the sample, and then entering the next step;

c. if the area of the measuring region does not exceed the area of the testing visual field under the specific multiple and the resolution, entering the step e, and if the area of the measuring region exceeds the area of the testing visual field under the specific multiple and the resolution, entering the step d;

d. selecting a splicing mode for detection, selecting a splicing overlapping proportion and the number of blocks of a measurement area to be spliced according to the area of splicing before the splicing mode is detected, and entering the step e;

e. detecting the three-dimensional morphology of the measurement areas, detecting each measurement area for not less than 5 times to obtain a three-dimensional morphology detection graph and measurement data, and entering the step f;

f. performing surface reconstruction on the measurement data obtained from each measurement area, and then entering the next step;

g. respectively calculating the volume V of the material between the highest point and the lowest point of the surface of each measurement area after reconstruction, and then entering the next step;

h. taking the average value of the material volume of all the measuring areas as the residual volume V of the material to be removed₁And then proceed to the next step;

i. according to the area of the measuring area and the volume V of the material to be removed₁Calculating to obtain the volume V of the material to be removed in the whole processing area₂。

2. The method for predicting the minimum machining allowance based on the microscopic three-dimensional topography of the surface according to claim 1, wherein: in the step a, the white light interferometer adopts a Wyko NT9300 optical profiler for measuring three-dimensional height information of the surface of the sample.

3. The method for predicting the minimum machining allowance based on the microscopic three-dimensional topography of the surface according to claim 1, wherein: in the step b, the shape of the sampling area is square, and the side length of the square is not less than 5 times of the period of the sample surface waviness.

4. The method for predicting the minimum machining allowance based on the microscopic three-dimensional topography of the surface according to claim 1, wherein: in the step d, the selected splicing overlapping proportion is 5-30%, and the selected overlapping proportion cannot influence the quality of spliced data.

5. The method for predicting the minimum machining allowance based on the microscopic three-dimensional topography of the surface according to claim 1, wherein: in the step f, the step of surface reconstruction includes denoising, filtering and filling.

6. The method for predicting the minimum machining allowance based on the microscopic three-dimensional topography of the surface according to claim 5, wherein: specifically, the denoising method includes removing impurity information on the surface of the sample, where the impurity information includes burrs and peaks caused by pixel deletion during detection.

7. The method for predicting the minimum machining allowance based on the microscopic three-dimensional topography of the surface according to claim 5, wherein: the filtering is specifically to remove other information of the sample and only keep the roughness information of the sample.

8. The method for predicting the minimum machining allowance based on the microscopic three-dimensional topography of the surface according to claim 5, wherein: the filling is specifically to complement missing data points in the denoised and filtered sample so that the height information of the sample is continuous.

Technical Field

The invention relates to the technical field of machining allowance prediction, in particular to a minimum machining allowance prediction method based on surface microscopic three-dimensional morphology.

Background

The part machining process is a process of removing material from the blank, the total amount of material removed being the total machining allowance. As the demand for machining accuracy is higher and higher, the process stages are strictly divided, and the total machining allowance is allocated to each process. The machining allowance of each process is strictly controlled, so that a machining defect layer of the previous process is removed, and small defects generated in the process are ensured, so that the requirement of minimum machining allowance is met.

Patent CN201410454345.4 discloses an automatic allocation method for crankshaft axial machining allowance, which utilizes a measurement system of a machining center to actually measure the macroscopic geometric dimension of a part, and compares the macroscopic geometric dimension with the outline required by part machining, thereby calculating the machining allowance of each process. The method is a machining allowance prediction method based on the macroscopic geometry, and the influence of the surface microscopic three-dimensional morphology on the machining allowance is not considered. However, in many existing machining occasions, especially in the occasions of precise and ultra-precise machining, such as the occasion of semiconductor machining, the machining allowance is extremely small, the minimum machining allowance cannot be accurately obtained by using a macroscopic method for detection, the error is large, the material removal rate is high during machining, and the machining time is long.

The prior art does not see patents related to the minimum machining allowance of precision machining. The minimum machining allowance is mainly determined by a table look-up method or an empirical method in actual machining, and the minimum machining allowance is difficult to accurately determine in the ultra-precision machining process.

Disclosure of Invention

The invention aims to provide a minimum machining allowance prediction method based on surface microscopic three-dimensional morphology, which can predict the volume of a material to be removed in precision and ultra-precision machining, enables the determination of the minimum machining allowance to be more accurate, reduces the machining time and the cost, can be used for predicting machining process allowances such as wire cutting, grinding and the like in the photoelectric and semiconductor material machining processes, and has wide application range.

The technical scheme adopted by the invention is as follows: a minimum machining allowance prediction method based on surface microscopic three-dimensional morphology comprises the following steps:

a. placing a sample to be processed on a white light interferometer, selecting a multiple and a resolution according to the roughness of the sample, wherein the selected multiple and resolution require to obtain the surface roughness and waviness information of the sample, and then entering the next step;

b. selecting a sampling area as a measurement area according to the area of the test visual field under the selected specific multiple and resolution and the size of the sample, and then entering the next step;

c. if the area of the measuring region does not exceed the area of the testing visual field under the specific multiple and the resolution, entering the step e, and if the area of the measuring region exceeds the area of the testing visual field under the specific multiple and the resolution, entering the step d;

d. selecting a splicing mode for detection, selecting a splicing overlapping proportion and the number of blocks of a measurement area to be spliced according to the area of splicing before the splicing mode is detected, and entering the step e;

e. detecting the three-dimensional morphology of the measurement areas, detecting each measurement area for not less than 5 times to obtain a three-dimensional morphology detection graph and measurement data, and entering the step f;

f. performing surface reconstruction on the measurement data obtained from each measurement area, and then entering the next step;

g. respectively calculating the volume V of the material between the highest point and the lowest point of the surface of each measurement area after reconstruction, and then entering the next step;

h. taking the average value of the material volume of all the measuring areas as the residual volume V of the material to be removed₁And then proceed to the next step;

i. according to the area of the measuring area and the volume V of the material to be removed₁Calculating to obtain the volume V of the material to be removed in the whole processing area₂。

Preferably, in the step a, the white light interferometer uses a Wyko NT9300 optical profiler for measuring three-dimensional height information of the surface of the sample.

Preferably, in step b, the sampling area is square, and the side length of the square is not less than 5 times the period of the sample surface waviness, that is, the square contains at least 5 peaks and valleys.

Preferably, in the step c, the selected splicing overlap ratio is 5-30%, and the selected overlap ratio cannot affect the quality of spliced data.

Preferably, in the step f, the step of surface reconstruction includes denoising, filtering and filling.

Preferably, the denoising specifically includes removing impurity information on the surface of the sample, where the impurity information includes a burr and a peak caused by pixel missing during detection.

Preferably, the filtering specifically is to remove other information of the sample and only retain roughness information of the sample.

Preferably, the filling is specifically to complement missing data points in the denoised and filtered sample, so that the height information of the sample is continuous.

The invention has the beneficial effects that: the method comprises selecting a measurement region on the surface of a sample to be processed, and then using a white light interferometer to select the selected regionSequentially carrying out three-dimensional detection on the surface with the measurement area, carrying out surface reconstruction on the surface after obtaining three-dimensional shape measurement data, then obtaining three-dimensional height information of the corresponding area of the processed surface, respectively calculating the material volume V between the highest point and the lowest point of the material in the measurement area selected after the surface of each measurement area is reconstructed, and taking the average value as the residual volume V of the material to be removed₁Finally predicting the volume V of the material to be removed of the whole sample according to the ratio of the area of the measuring region to the area of the sample₂. The minimum machining allowance prediction method provided by the invention is obtained by calculating by detecting the microscopic three-dimensional morphology of the surface of the sample, so that the determination of the minimum machining allowance is more accurate, the machining quality is improved, the machining time is reduced, the minimum machining allowance prediction method can be used for predicting the machining amount of grinding, grinding and other procedures in the photoelectric and semiconductor material machining processes, and the application range is widened.

Drawings

FIG. 1 is a schematic view of the location of a measurement area according to the present invention;

FIG. 2 is a schematic diagram of the three-dimensional surface topography of the diamond substrate before de-noising according to the present invention;

FIG. 3 is a schematic diagram of the distribution of the surface height of the diamond substrate before de-noising according to the present invention;

FIG. 4 is a schematic diagram of the three-dimensional surface topography of the diamond substrate sheet after denoising according to the present invention;

FIG. 5 is a schematic diagram of the distribution of the height of the de-noised surface of the diamond substrate wafer according to the present invention;

FIG. 6 is a graph illustrating the determination of the cutoff frequency according to the present invention;

FIG. 7 is a schematic diagram of the surface three-dimensional topography of the diamond substrate sheet after surface reconstruction according to the present invention;

FIG. 8 is a schematic view showing the height distribution of the surface of the diamond substrate sheet after surface reconstruction according to the present invention;

FIG. 9 is a schematic view of the surface profile of a diamond substrate sheet according to the present invention;

FIG. 10 is a graphical representation of the material volume V versus the relative height of a diamond substrate sheet in accordance with the present invention;

FIG. 11 is a graph showing the relationship between the estimated machining allowance and the feed rate of the diamond substrate piece according to the present invention.

Detailed Description

The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

A minimum machining allowance prediction method based on surface microscopic three-dimensional morphology comprises the following steps:

a. placing a sample to be processed on a white light interferometer, wherein the white light interferometer is used for measuring three-dimensional height information of the surface of the sample, a Wyko NT9300 optical profiler can be adopted, the selected times and resolution are determined according to the roughness selection times and resolution of the sample, the surface roughness and waviness information of the sample can be obtained, and then the next step is carried out;

b. selecting a sampling area as a measuring area according to the area of a testing visual field under a selected specific multiple and resolution and the size of a sample, wherein the shape of the sampling area is square, the side length of the square is not less than 5 times of the period of the surface waviness of the sample, namely, the square contains at least 5 wave crests and wave troughs, the number of the measuring areas is set to a certain interval proportion according to the shape and the area of the sample, the proportion is 5-30 times of the side length of the shape of the measuring area, and then entering the next step;

c. if the area of the measuring region does not exceed the area of the testing visual field under the specific multiple and the resolution, entering the step e, and if the area of the measuring region exceeds the area of the testing visual field under the specific multiple and the resolution, entering the step d;

d. selecting a splicing mode for detection, selecting a splicing overlap ratio and the number of blocks of a measurement area to be spliced according to the area of splicing before the splicing mode is detected, wherein the selected splicing overlap ratio is 5-30%, the selected overlap ratio cannot influence the quality of data after splicing, and entering a step e;

e. detecting the three-dimensional morphology of the measurement areas, detecting each measurement area for not less than 5 times to obtain a three-dimensional morphology detection graph and measurement data, and entering the step f;

f. performing surface reconstruction on the measurement data obtained in each measurement area, wherein the surface reconstruction comprises denoising, filtering and filling, the denoising specifically comprises removing impurity information on the surface of a sample, the impurity information comprises burrs and peaks caused by pixel deletion during detection, the filtering specifically comprises removing other information of the sample and only retaining roughness information of the sample, and the filling specifically comprises complementing missing data points in the denoised and filtered sample to enable the height information of the sample to be continuous, and then entering the next step;

g. respectively calculating the volume V of the material between the highest point and the lowest point of the surface of each measurement area after reconstruction, and then entering the next step;

h. taking the average value of the material volume of all the measuring areas as the residual volume V of the material to be removed₁And then proceed to the next step;

i. according to the area of the measuring area and the volume V of the material to be removed₁Calculating to obtain the volume V of the material to be removed in the whole processing area₂。

The following is a detailed description with reference to the examples:

selecting a diamond substrate sheet with the size of 10mm multiplied by 10mm as a sample to be processed, placing the diamond substrate sheet on a workbench of a Wyko NT9300 optical profiler, measuring three-dimensional height information of the surface of the diamond substrate sheet, firstly adjusting the height of a Z axis to find interference fringes, and adjusting the width of the interference fringes to ensure that the lowest point and the highest point of the interference fringes in a visual field can be simultaneously measured during measurement.

According to the roughness selection multiple and the resolution of the diamond substrate slice, the surface roughness and the waviness information of the diamond substrate slice can be obtained according to the requirements of the selected multiple and the resolution, when in operation, a 5-time lens is used for carrying out pre-detection on a diamond substrate slice sample, the roughness of the sample is 1.25 mu m, the resolution is 1.98 mu m, and the size of a visual field is 1.3mm multiplied by 0.95 mm. It can be seen that the resolution of the crystal is too low with 5 times lens, and the detection is carried out with 20 times lens, which is 493.27 μm.

The sampling area is selected as the measurement area according to the area of the test field at the selected specific times and resolution and the size of the diamond substrate piece. The shape of the sampling area is selected to be square, the side length of the square is not less than 5 times of the period of the surface waviness of the diamond substrate, namely, the square comprises at least 5 wave crests and wave troughs, the sampling area selected in the way is larger and more representative, the measuring area of the sample is more accurate, 5 sampling areas are selected as measuring areas during operation, certain interval proportion is set according to the shape and the area of the diamond substrate, the certain interval proportion is taken as 5 times of the side length of the shape of the measuring area, and the 5 measuring areas are selected as shown in figure 1.

In order to ensure that the size of the visual field is 1.3mm multiplied by 0.95mm, the measurement areas need to be spliced, a default splicing overlap proportion is selected to be 20%, the height information of the sample and the width of the interference fringes are adjusted, the size of the visual field is ensured to be 1.3mm multiplied by 0.95mm, the three-dimensional morphology of the spliced measurement areas is detected, not less than 5 times of detection is carried out on each spliced measurement area, namely, each measurement area is repeatedly measured for 5 times, and a spliced three-dimensional morphology detection graph and measurement data are obtained.

And performing surface reconstruction on the measurement data obtained from each measurement region, wherein the surface reconstruction comprises the steps of denoising, filtering and filling. Specifically, the noise removal is to remove impurity information on the surface of the diamond substrate slice, where the impurity information includes burrs and peaks caused by pixel deletion during detection, the three-dimensional surface topography and the histogram of the diamond substrate slice before the noise removal processing are shown in fig. 2 and 3, and the three-dimensional surface topography and the histogram of the diamond substrate slice after the noise removal processing are shown in fig. 4 and 5, respectively. The filtering is specifically to remove other information of the diamond substrate sheet, only retain roughness information of the diamond substrate sheet, calculate a relation curve between the power spectral density and the spatial frequency of the sample surface when filtering the measured data, and select a numberThe cutoff frequency is determined in a manner shown in FIG. 6 based on the critical position point where the fluctuation tends to be linear_c＝25.8mm^-1. The filling is specifically to complement missing data points in the denoised and filtered sample, so that the height information of the sample is continuous, the filled sample cannot have pixel point missing, and cannot have the effect of influencing the test due to excessive filling, and the surface three-dimensional morphology and the histogram of the diamond substrate sheet after filling treatment are respectively shown in fig. 7 and fig. 8.

And respectively calculating the material volume between the highest point and the lowest point in each measurement region after reconstruction to be used as a material volume V to be removed, wherein the material volume V is shown as a shaded part in figure 9, the material volume V is the volume of the material in a visual field obtained by means of post-processing software integration, namely the material volume V can be directly obtained by using a reverse integration function of Wyko NT9300 optical profiler equipment Vision4.0 software, and the relation between the material volume V and the relative height of the diamond substrate slice is shown in figure 10. Then taking the average value of the material volume V of all the measuring areas as the residual volume V of the material to be removed₁And according to the area of the measuring zone and the volume V of material to be removed₁Calculating to obtain the volume V of the material to be removed in the whole processing area₂Volume of material V₂The calculation formula of (a) is as follows:

V₂＝V₁×S₂/S₁

wherein S is₁To test the area of the field of view, S₂The area of the entire processing area of the diamond substrate sheet sample. Fig. 11 shows the volume of material to be removed, i.e., the estimated machining allowance of the diamond substrate piece, obtained under different feed rate parameters.

The foregoing has described the general principles, principal features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are merely illustrative of the principles of the present invention, but that various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined by the appended claims and their equivalents.