Cleaning control system and method for sapphire double-polished sheet

Abstract

The invention discloses a cleaning control system and method for a sapphire double-polished wafer, and belongs to the field of cleaning control of the sapphire double-polished wafer. Cleaning data are acquired, images of the sapphire double-polished wafer and data before and after cleaning are acquired, the images are processed, and a cleaning effect evaluation model is constructed; scratch related parameters and the number of surface particles before and after cleaning are imported into a cleaning effect evaluation model to be evaluated, a brush abrasion degree evaluation model is constructed, process parameters of the process of cleaning the sapphire double-polished sheet by the brush are imported into the brush abrasion degree evaluation model to evaluate the brush abrasion degree, and a brush remaining life evaluation model is constructed. The brush abrasion loss, the brush cleaning effect and the brush thickness are imported into the brush residual life evaluation model to evaluate the brush residual life, the brush abrasion condition is evaluated by monitoring the cleaning effect in real time, the brush life is predicted based on the abrasion model, and the negative influence of the brush on the double-polishing-piece cleaning process is reduced.

Description

Technical Field

[0001] The invention belongs to the field of cleaning control of sapphire double-polished sheets, and in particular relates to a cleaning control system and method for sapphire double-polished sheets. Background Art

[0002] Sapphire double-polished wafers are widely used in LED substrates, optical windows, semiconductor substrates and other fields. Their surface quality has an important impact on subsequent processing and device performance. During the grinding, polishing and cleaning process, tiny particles, scratches or other defects may remain on the surface of sapphire double-polished wafers. If the cleaning effect is not good, it may cause device failure in the subsequent process and affect the product yield.

[0003] Traditional sapphire double-polished sheet cleaning mainly relies on manual experience to judge the cleaning effect, which is difficult to achieve quantitative control. In addition, the service life of the brush is mainly replaced at a fixed period, and it fails to be dynamically adjusted according to the actual wear conditions, resulting in waste caused by replacing the brush too early, or replacing it too late to affect the cleaning quality. The present invention proposes a cleaning control system and method for sapphire double-polished sheets, which can monitor the cleaning effect in real time, evaluate the wear condition of the brush, and predict the life of the brush based on the wear model to ensure the stability of the cleaning process, and can replace the brush in time to reduce the negative impact of the brush on the double-polished sheet cleaning process. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention proposes a cleaning control system and method for sapphire double-polished wafers.

[0005] To achieve the above object, the present invention provides the following technical solutions: The cleaning control method for sapphire double-polished wafers comprises the following specific steps: Acquire cleaning data, obtain sapphire double-polished wafer images and data before and after cleaning, and process the images; Construct a cleaning effect evaluation model, and import scratch-related parameters and the number of surface particles before and after cleaning into the cleaning effect evaluation model for evaluation; A brush wear degree evaluation model was constructed, and the process parameters of brush cleaning of sapphire double-polished wafers were imported into the brush wear degree evaluation model to evaluate the brush wear degree; A brush remaining life assessment model is constructed, and the brush wear, brush cleaning effect and brush thickness are imported into the brush remaining life assessment model to evaluate the brush remaining life.

[0006] Preferably, the step of obtaining cleaning data, obtaining the sapphire double-polished sheet image and data before and after cleaning, and processing the image comprises the following specific steps: S11. Use a high-resolution camera to collect images of the sapphire double-polished sheet before and after double-sided washing. Take the center of the sapphire double-polished sheet as the coordinate origin to establish a rectangular coordinate system. Use a Gaussian filter to perform denoising on the collected images of the sapphire double-polished sheet before and after double-sided washing. The Gaussian filter formula is: , where (x, y) is the pixel coordinate in the image, σ is the standard deviation, and k is the radius of the filter window; S12, use the maximum inter-class variance method to perform threshold segmentation on the image threshold, traverse all possible grayscale thresholds, calculate the variance between the foreground and background classes under each threshold, select the threshold corresponding to the maximum variance as the optimal segmentation threshold, separate the scratch area from the background, and remove the background of the image by image subtraction to highlight the scratch area, subtract the two two-dimensional image data and take the absolute value to obtain the difference between the two images, and output a difference image data, wherein the image subtraction calculation formula is: ,in, is the image after threshold segmentation, is the background control image; S13, measuring the depth, three-dimensional morphology and quantity distribution of scratches on the surface of the double-polished wafer after cleaning by a shape measurement laser microscope system, and obtaining the scratch position by an established rectangular coordinate system; S14, using a particle detector to detect the number of particles on the surface of the sapphire double-polished sheet before and after cleaning, to obtain the number of particles on the surface before and after cleaning.

[0007] Preferably, the construction of the cleaning effect evaluation model and importing the scratch-related parameters and the number of surface particles before and after cleaning into the cleaning effect evaluation model for evaluation comprises the following specific steps: S21. Substituting scratch-related parameters into a scratch comprehensive evaluation index calculation formula to evaluate the scratch degree, wherein the scratch comprehensive evaluation index calculation formula is: , where S is the single-side area of ​​the sapphire double-polished film, d i is the depth of the i-th scratch, h i is the length of the i-th scratch, n is the total number of scratches on both sides; S22, substituting the number of particles on the surface of the sapphire double-polished sheet before and after cleaning into the particle removal rate calculation formula to calculate the particle removal rate, wherein the particle removal rate calculation formula is: , where D1 is the number of surface particles on both sides of the sapphire double-polished sheet before cleaning, and D2 is the number of surface particles on both sides of the sapphire double-polished sheet after cleaning.

[0008] Preferably, the construction of the brush wear degree evaluation model and the importation of the process parameters of brush cleaning of sapphire double-polished sheets into the brush wear degree evaluation model to evaluate the brush wear degree include the following specific steps: S31, comparing the scratch comprehensive evaluation index with the scratch evaluation threshold, if the scratch comprehensive evaluation index is greater than the scratch evaluation threshold, immediately replacing the brush, and at the same time comparing the particle removal rate with the minimum particle removal rate threshold, if the particle removal rate is less than the minimum particle removal rate threshold, immediately replacing the brush; S32. If the scratch comprehensive evaluation index and the particle removal rate are both within the threshold range, the process parameters of brush cleaning of sapphire double polishing sheet are substituted into the brush wear calculation formula to calculate the brush wear. The brush wear calculation formula per unit time is based on the Archard wear equation. The brush wear is quantified by the brush material properties, pressure, sliding distance and the corrosiveness of the cleaning fluid to the brush. The brush wear calculation formula per unit time is: , K is the wear coefficient, F is the pressure applied by the brush, L is the sliding distance between the brush and the sapphire sheet per unit time, Z is the hardness of the brush material, and C is the corrosion coefficient of the cleaning fluid on the brush. The calculation formula for the sliding distance is: , where r is the contact radius of the brush, v is the rotation speed of the brush, and t is the unit time.

[0009] Preferably, the construction of the brush remaining life assessment model, importing the brush wear amount, brush cleaning effect and brush thickness into the brush remaining life assessment model to assess the brush remaining life comprises the following specific steps: S41, substituting the brush wear amount and the brush thickness into the brush remaining life calculation formula to calculate the brush remaining life, wherein the brush remaining life calculation formula is: ,in, is the cleaning evaluation factor, H0 is the real-time thickness of the brush, H min is the minimum thickness allowed for the brush, where the calculation formula for the cleaning assessment factor is: , where A is the comprehensive scratch evaluation index, Ar is the scratch evaluation threshold, P is the particle removal rate, P r is the particle removal rate threshold, and the impact of the actual working state of the brush on the remaining life is comprehensively evaluated by incorporating the scratch comprehensive evaluation index and particle removal rate into the cleaning evaluation factor; S42: Compare the remaining life of the brush with the brush life threshold. If it is less than or equal to the threshold, replace the brush immediately. If it is close to the threshold, issue a reminder warning.

[0010] A cleaning control system for sapphire double-polished wafers, which is implemented based on the above-mentioned cleaning control method for sapphire double-polished wafers, specifically includes: The data acquisition module is used to acquire the sapphire double-polished wafer image and the data before and after cleaning, and process the image; A cleaning effect evaluation module is used to evaluate the cleaning effect through scratch-related parameters and the number of surface particles before and after cleaning; The brush wear degree evaluation module is used to evaluate the brush wear degree through the process parameters of brush cleaning sapphire double-polished wafers; The brush remaining life assessment module is used to assess the brush remaining life based on brush wear, brush cleaning effect and brush thickness.

[0011] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned cleaning control method for sapphire double-polished wafers by calling the computer program stored in the memory.

[0012] A computer-readable storage medium, characterized in that it stores instructions, and when the instructions are run on a computer, the computer executes the above-mentioned cleaning control method for sapphire double-polished wafers.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention obtains cleaning data, obtains sapphire double-polished wafer images and data before and after cleaning, processes the images, constructs a cleaning effect evaluation model, imports scratch-related parameters and the number of surface particles before and after cleaning into the cleaning effect evaluation model for evaluation, constructs a brush wear degree evaluation model, imports process parameters of brush cleaning sapphire double-polished wafers into the brush wear degree evaluation model to evaluate the brush wear degree, constructs a brush remaining life evaluation model, imports the brush wear amount, brush cleaning effect and brush thickness into the brush remaining life evaluation model to evaluate the brush remaining life. The present invention evaluates the brush wear condition by real-time monitoring of the cleaning effect, predicts the brush life based on the wear model, and reduces the negative impact of the brush on the double-polished wafer cleaning process. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the overall flow of the cleaning control method for sapphire double-polished wafers of the present invention; Figure 2 Flow chart for calculation of comprehensive scratch evaluation index; Figure 3 Flow chart for calculating the remaining life of the brush; Figure 4 The figure is a schematic diagram of the overall framework of the cleaning control system for sapphire double-polished wafers of the present invention. DETAILED DESCRIPTION

[0015] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0016] Example 1 See also Figure 1-3 The present invention provides an embodiment: a cleaning control method for a sapphire double-polished wafer, which comprises the following specific steps: Acquire cleaning data, obtain sapphire double-polished wafer images and data before and after cleaning, and process the images; Construct a cleaning effect evaluation model, and import scratch-related parameters and the number of surface particles before and after cleaning into the cleaning effect evaluation model for evaluation; A brush wear degree evaluation model was constructed, and the process parameters of brush cleaning of sapphire double-polished wafers were imported into the brush wear degree evaluation model to evaluate the brush wear degree; A brush remaining life assessment model is constructed, and the brush wear, brush cleaning effect and brush thickness are imported into the brush remaining life assessment model to evaluate the brush remaining life.

[0017] In this embodiment, it should be specifically explained that obtaining cleaning data, obtaining sapphire double-polished wafer images and data before and after cleaning, and processing the images include the following specific steps: S11. Use a high-resolution camera to collect images of the sapphire double-polished sheet before and after double-sided washing. Take the center of the sapphire double-polished sheet as the coordinate origin to establish a rectangular coordinate system. Use a Gaussian filter to perform denoising on the collected images of the sapphire double-polished sheet before and after double-sided washing. The Gaussian filter formula is: , where (x, y) is the pixel coordinate in the image, σ is the standard deviation, σ determines the smoothness of the filter, a larger σ makes the filtering effect smoother, and k is the radius of the filter window; S12, use the maximum inter-class variance method to perform threshold segmentation on the image threshold, traverse all possible grayscale thresholds, calculate the variance between the foreground and background classes under each threshold, select the threshold corresponding to the maximum variance as the optimal segmentation threshold, separate the scratch area from the background, and remove the background of the image by image subtraction to highlight the scratch area, subtract the two two-dimensional image data and take the absolute value to obtain the difference between the two images, and output a difference image data, wherein the image subtraction calculation formula is: ,in, is the image after threshold segmentation, is the background control image; S13, measuring the depth, three-dimensional morphology and quantity distribution of scratches on the surface of the double-polished wafer after cleaning by a shape measurement laser microscope system, and obtaining the scratch position by an established rectangular coordinate system; S14, using a particle detector to detect the number of particles on the surface of the sapphire double-polished sheet before and after cleaning, to obtain the number of particles on the surface before and after cleaning.

[0018] In this embodiment, it should be specifically explained that constructing a cleaning effect evaluation model and importing scratch-related parameters and the number of surface particles before and after cleaning into the cleaning effect evaluation model for evaluation includes the following specific steps: S21. Substitute the scratch-related parameters into the scratch comprehensive evaluation index calculation formula to evaluate the scratch degree. The scratch degree after cleaning is comprehensively evaluated by the depth, length and number of scratches on both sides of the sapphire double-polished sheet after cleaning, and the negative impact of the bristles during the cleaning process is evaluated. The scratch comprehensive evaluation index calculation formula is: , where S is the single-side area of ​​the sapphire double-polished film, d i is the depth of the i-th scratch, h i is the length of the i-th scratch, n is the total number of double-sided scratches, the scratch depth and length directly reflect the severity of the scratch on the double-polished sheet surface damage, longer or deeper scratches will penetrate a larger area of ​​the double-polished sheet surface, increasing the negative impact on the surface quality, the formula comprehensively considers the scratch depth, length and the overall area of ​​the double-polished sheet, larger scratch depth and length will lead to an increase in the index value, indicating that the scratch is more serious, and a smaller index value indicates that the scratch has little effect on the surface quality of the double-polished sheet; S22. Substitute the number of particles on the surface of the sapphire double-polished sheet before and after cleaning into the particle removal rate calculation formula to calculate the particle removal rate, evaluate the particle removal effect of the brush cleaning double-polished sheet, and reflect the change in the cleanliness of the double-polished sheet after cleaning compared with before cleaning through the change in the number of particles before and after cleaning. The particle removal rate calculation formula is: , where D1 is the number of surface particles on both sides of the sapphire double-polished sheet before cleaning, and D2 is the number of surface particles on both sides of the sapphire double-polished sheet after cleaning.

[0019] In this embodiment, it should be specifically explained that constructing a brush wear degree evaluation model and importing the process parameters of brush cleaning sapphire double-polished sheets into the brush wear degree evaluation model to evaluate the brush wear degree includes the following specific steps: S31. Compare the scratch comprehensive evaluation index with the scratch evaluation threshold. If the scratch comprehensive evaluation index is greater than the scratch evaluation threshold, replace the brush immediately. Meanwhile, compare the particle removal rate with the minimum particle removal rate threshold. If the particle removal rate is less than the minimum particle removal rate threshold, replace the brush immediately. The scratch evaluation threshold and the minimum particle removal rate threshold are determined based on the product quality standard of double-polished films and actual production experience. In the production and application of double-polished films, different products have different tolerances to scratches. Through the dual judgment of the scratch evaluation threshold and the minimum particle removal rate threshold, the brush life can be timely estimated. S32. If the scratch comprehensive evaluation index and the particle removal rate are both within the threshold range, the process parameters of brush cleaning of sapphire double polishing sheet are substituted into the brush wear calculation formula to calculate the brush wear. The brush wear calculation formula per unit time is based on the Archard wear equation. The brush wear is quantified by the brush material properties, pressure, sliding distance and the corrosiveness of the cleaning fluid to the brush. The brush wear calculation formula per unit time is: , K is the wear coefficient, which is determined by the characteristics of the brush material, F is the pressure applied by the brush. The greater the pressure, the stronger the contact force between the brush and the double-polished surface, the stronger the friction, and the greater the wear amount. L is the sliding distance between the brush and the sapphire sheet per unit time, Z is the hardness of the brush material. The higher the hardness, the stronger the brush's ability to resist wear. C is the corrosion coefficient of the cleaning fluid on the brush. The calculation formula for the sliding distance is: , where r is the contact radius of the brush, v is the rotation speed of the brush, and t is the unit time. The contact radius is related to the shape of the brush and the range of action on the double-polished surface. A larger contact radius means that the brush covers a larger area per unit time, and the sliding distance increases accordingly. At the same time, the faster the rotation speed, the longer the distance the brush travels on the double-polished surface per unit time.

[0020] In this embodiment, it should be specifically explained that constructing a brush remaining life evaluation model, importing the brush wear amount, brush cleaning effect and brush thickness into the brush remaining life evaluation model to evaluate the brush remaining life includes the following specific steps: S41, substituting the brush wear amount and the brush thickness into the brush remaining life calculation formula to calculate the brush remaining life, wherein the brush remaining life calculation formula is: ,in, is the cleaning evaluation factor, H0 is the real-time thickness of the brush, obtained by an online thickness gauge, and H min is the minimum thickness allowed for the brush, where the calculation formula for the cleaning assessment factor is: , where A is the comprehensive scratch evaluation index, Ar is the scratch evaluation threshold, P is the particle removal rate, P r is the particle removal rate threshold, the scratch comprehensive evaluation index reflects the impact of the brush on the scratches on the double-polished sheet surface, and the particle removal rate reflects the cleaning effect of the brush. A lower particle removal rate means that the cleaning ability of the brush is reduced, which will also affect its remaining life. By incorporating the scratch comprehensive evaluation index and particle removal rate into the cleaning evaluation factors, the impact of the actual working status of the brush on the remaining life is comprehensively evaluated. S42. Compare the remaining life of the brush with the brush life threshold. If it is less than or equal to the threshold, replace the brush immediately. If it is close to the threshold, issue a reminder warning to prompt the operator to pay attention to the brush status in time and prepare to replace the brush in advance to avoid production interruption due to sudden failure of the brush.

[0021] It should be noted that the method of taking values ​​of various setting parameters in this embodiment is as follows: various parameters in the representative sapphire double-polished wafer cleaning process are obtained, and at the same time, the surface state parameters of the double-polished wafer before and after cleaning are obtained, the production requirements and quality standards of the double-polished wafer are obtained, and experts are hired to manually judge the qualified state of the double-polished wafer cleaning, and at the same time, the calculation results and judgment results of each step in this embodiment are substituted into the fitting software by the obtained historical data, and the values ​​of various setting parameters that meet the highest judgment accuracy are output; The advantages of this embodiment over the prior art are: The present invention obtains cleaning data, obtains sapphire double-polished wafer images and data before and after cleaning, processes the images, constructs a cleaning effect evaluation model, imports scratch-related parameters and the number of surface particles before and after cleaning into the cleaning effect evaluation model for evaluation, constructs a brush wear degree evaluation model, imports process parameters of brush cleaning sapphire double-polished wafers into the brush wear degree evaluation model to evaluate the brush wear degree, constructs a brush remaining life evaluation model, imports the brush wear amount, brush cleaning effect and brush thickness into the brush remaining life evaluation model to evaluate the brush remaining life. The present invention evaluates the brush wear condition by real-time monitoring of the cleaning effect, predicts the brush life based on the wear model, and reduces the negative impact of the brush on the double-polished wafer cleaning process.

[0022] Example 2 like Figure 4 As shown, a cleaning control system for sapphire double-polished wafers is implemented based on the above-mentioned cleaning control method for sapphire double-polished wafers, and specifically includes a data acquisition module, a cleaning effect evaluation module, a brush wear degree evaluation module and a brush remaining life evaluation module. The data acquisition module is used to acquire the sapphire double-polished wafer image and data before and after cleaning, and process the image; the cleaning effect evaluation module is used to evaluate the cleaning effect through scratch-related parameters and the number of surface particles before and after cleaning; the brush wear degree evaluation module is used to evaluate the brush wear degree through the process parameters of brush cleaning sapphire double-polished wafers; the brush remaining life evaluation module is used to evaluate the brush remaining life through the brush wear amount, brush cleaning effect and brush thickness.

[0023] Example 3 This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned cleaning control method for sapphire double-polished wafers by calling the computer program stored in the memory.

[0024] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the cleaning control method for sapphire double-polished wafers provided in the above method embodiment. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0025] Example 4 This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon; When the computer program is executed on a computer device, the computer device is caused to execute the above-mentioned cleaning control method for sapphire double-polished wafers.

[0026] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0027] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0028] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0029] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

Claims

1. A cleaning control method for sapphire double-polished wafers, characterized in that: It includes the following specific steps: Acquire cleaning data, obtain sapphire double-polished wafer images and data before and after cleaning, and process the images; Construct a cleaning effect evaluation model, and import scratch-related parameters and the number of surface particles before and after cleaning into the cleaning effect evaluation model for evaluation; A brush wear degree evaluation model was constructed, and the process parameters of brush cleaning of sapphire double-polished wafers were imported into the brush wear degree evaluation model to evaluate the brush wear degree; A brush remaining life assessment model is constructed, and the brush wear, brush cleaning effect and brush thickness are imported into the brush remaining life assessment model to evaluate the brush remaining life.

2. The cleaning control method for sapphire double-polished wafer according to claim 1, characterized in that: The step of obtaining cleaning data, obtaining a sapphire double-polished sheet image and data before and after cleaning, and processing the image comprises the following specific steps: S11, using a high-resolution camera to collect images of the sapphire double-polished sheet before and after double-sided washing, establishing a rectangular coordinate system with the center of the sapphire double-polished sheet as the coordinate origin, and using a Gaussian filter to perform denoising on the collected images of the sapphire double-polished sheet before and after double-sided washing; S12, using the maximum inter-class variance method to perform threshold segmentation on the image threshold, traverse all possible grayscale thresholds, calculate the variance between the foreground and background classes under each threshold, select the threshold corresponding to the maximum variance as the optimal segmentation threshold, separate the scratch area from the background, and remove the background of the image by image subtraction to highlight the scratch area, subtract the two two-dimensional image data and take the absolute value to obtain the difference between the two images, and output a difference image data; S13, measuring the depth, three-dimensional morphology and quantity distribution of scratches on the surface of the double-polished wafer after cleaning by a shape measurement laser microscope system, and obtaining the scratch position by an established rectangular coordinate system; S14, using a particle detector to detect the number of particles on the surface of the sapphire double-polished sheet before and after cleaning, to obtain the number of particles on the surface before and after cleaning.

3. The cleaning control method for sapphire double-polished wafer according to claim 2, characterized in that: The construction of the cleaning effect evaluation model and the importation of scratch-related parameters and the number of surface particles before and after cleaning into the cleaning effect evaluation model for evaluation include the following specific steps: S21. Substituting scratch-related parameters into the scratch comprehensive evaluation index calculation formula to evaluate the degree of scratches, comprehensively evaluating the degree of scratches after cleaning through the depth, length and number of scratches on both sides of the sapphire double-polished sheet after cleaning, and evaluating the negative impact of the bristles during the cleaning process; S22. Substitute the number of particles on the surface of the sapphire double-polished sheet before and after cleaning into the particle removal rate calculation formula to calculate the particle removal rate, evaluate the particle removal effect of the brush cleaning double-polished sheet, and reflect the change in the cleanliness of the double-polished sheet after cleaning compared to before cleaning through the change in the number of particles before and after cleaning.

4. The cleaning control method for sapphire double-polished wafer according to claim 3, characterized in that: The construction of the brush wear degree evaluation model and the importation of the process parameters of brush cleaning of sapphire double-polished sheets into the brush wear degree evaluation model for evaluating the brush wear degree include the following specific steps: S31, comparing the scratch comprehensive evaluation index with the scratch evaluation threshold, if the scratch comprehensive evaluation index is greater than the scratch evaluation threshold, immediately replacing the brush, and at the same time comparing the particle removal rate with the minimum particle removal rate threshold, if the particle removal rate is less than the minimum particle removal rate threshold, immediately replacing the brush; S32. If the scratch comprehensive evaluation index and the particle removal rate are both within the threshold range, the process parameters of brush cleaning of sapphire double-polished sheets are substituted into the brush wear calculation formula to calculate the brush wear. The brush wear calculation formula per unit time is based on the Archard wear equation, and the brush wear is quantified by the brush material properties, pressure, sliding distance, and the corrosiveness of the cleaning fluid to the brush.

5. The cleaning control method for sapphire double-polished wafer according to claim 4, characterized in that: The construction of the brush remaining life evaluation model, importing the brush wear amount, brush cleaning effect and brush thickness into the brush remaining life evaluation model to evaluate the brush remaining life includes the following specific steps: S41, substituting the brush wear amount and the brush thickness into the brush remaining life calculation formula to calculate the brush remaining life, wherein the brush remaining life calculation formula is: ,in, is the cleaning evaluation factor, H0 is the real-time thickness of the brush, H min is the minimum thickness allowed for the brush, where the calculation formula for the cleaning assessment factor is: , where A is the comprehensive scratch evaluation index, Ar is the scratch evaluation threshold, P is the particle removal rate, P r is the particle removal rate threshold; S42: Compare the remaining life of the brush with the brush life threshold. If it is less than or equal to the threshold, replace the brush immediately. If it is close to the threshold, issue a reminder warning.

6. A cleaning control system for sapphire double-polished wafers, which is implemented based on the cleaning control method for sapphire double-polished wafers according to any one of claims 1 to 5, characterized in that: Specifically include: The data acquisition module is used to acquire the sapphire double-polished wafer image and the data before and after cleaning, and process the image; A cleaning effect evaluation module is used to evaluate the cleaning effect through scratch-related parameters and the number of surface particles before and after cleaning; The brush wear degree evaluation module is used to evaluate the brush wear degree through the process parameters of brush cleaning sapphire double-polished wafers; The brush remaining life assessment module is used to assess the brush remaining life based on brush wear, brush cleaning effect and brush thickness.

7. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the cleaning control method for sapphire double-polished wafers as described in any one of claims 1 to 5 by calling the computer program stored in the memory.

8. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are run on a computer, the computer is caused to execute the cleaning control method for sapphire double-polished wafers as described in any one of claims 1 to 5.

Images