A method and apparatus for creating a subsurface standard defect database for transparent samples.

Abstract

This invention provides a method and apparatus for creating a subsurface standard defect database for transparent samples. The method includes: creating a virtual transparent sample based on preset subsurface standard defect parameters; using simulated laser light to act on the subsurface of the virtual transparent sample to obtain near-field light field distribution data corresponding to the subsurface standard defects of the virtual transparent sample; determining the corresponding target far-field light intensity distribution data based on the near-field light field distribution data; and creating a subsurface standard defect database for transparent samples based on the target far-field light intensity distribution data and the corresponding subsurface standard defect parameters. Thus, a corresponding virtual transparent sample can be created based on the required standard defect parameters, resulting in higher sample production efficiency compared to the standard sample production methods in the prior art. Furthermore, this application utilizes simulation data to determine the final target far-field light intensity distribution data, reducing human experimental errors and improving the accuracy of the standard defect database.

Description

Technical Field

[0001] This application relates to the field of optical inspection technology, and in particular to a method and apparatus for creating a standard subsurface defect database for transparent samples. Background Technology

[0002] For transparent optical components (such as windows), traditional grinding and polishing processes inevitably introduce structural defects such as bubbles, scratches, and microcracks in the subsurface layer. These defects can severely reduce the laser damage threshold of optical components in high-power laser environments.

[0003] In related technologies, the common approach is to prepare samples with various standard defects, use methods such as laser confocal microscopy and optical microscopy to obtain defect information through experimental analysis, and establish a subsurface standard defect database so that the type of subsurface defect of a certain optical component can be quickly determined based on the database.

[0004] However, existing technologies require the preparation of a large number of standard samples, which are difficult, time-consuming, and costly to process. Furthermore, the detection equipment has low detection resolution and low detection efficiency. Moreover, human error is easily introduced during the experiment, making it impossible to ensure the accuracy and efficiency of the sample subsurface standard defect database. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a method and apparatus for creating a standard defect database for the subsurface of transparent samples, thereby solving or partially solving the technical problem that the creation efficiency and accuracy cannot be guaranteed when creating a standard defect database for the subsurface of transparent samples in the prior art.

[0006] The technical solution of this invention is implemented as follows:

[0007] A first aspect of the present invention provides a method for creating a database of subsurface standard defects for transparent samples, the method comprising:

[0008] A virtual transparent sample is created based on preset subsurface standard defect parameters; the subsurface standard defect parameters include: defect type, defect size, defect depth, and material; the subsurface of the virtual transparent sample is provided with subsurface standard defects;

[0009] By applying simulated laser light to the subsurface of the virtual transparent sample, near-field optical field distribution data corresponding to standard defects on the subsurface of the virtual transparent sample are obtained.

[0010] Determine the corresponding target far-field light intensity distribution data based on the near-field light field distribution data;

[0011] A database of standard subsurface defects for transparent samples is created based on the target far-field light intensity distribution data and the corresponding subsurface standard defect parameters.

[0012] In the above scheme, the step of creating a virtual transparent sample based on subsurface standard defect parameters includes:

[0013] Create a virtual transparent sample;

[0014] Based on the subsurface standard defect parameters, corresponding subsurface standard defects are set on the subsurface of the virtual transparent sample.

[0015] In the above scheme, after creating a virtual transparent sample based on preset subsurface standard defect parameters, the method further includes:

[0016] Set the type of light absorption boundary condition according to the simulation requirements.

[0017] In the above scheme, the step of using simulated laser light to act on the subsurface of the virtual transparent sample to obtain near-field optical field distribution data corresponding to standard defects on the subsurface of the virtual transparent sample includes:

[0018] The simulated laser is diffracted after passing through the subsurface standard defect of the virtual transparent sample to obtain near-field diffraction data;

[0019] The near-field diffraction data is processed to obtain the near-field light field distribution data corresponding to the subsurface standard defects of the virtual transparent sample.

[0020] In the above scheme, determining the corresponding target far-field light field distribution data based on the near-field light field distribution data includes:

[0021] According to the formula The near-field light field distribution data is converted into far-field light field distribution data U. f (x f ,y f );

[0022] The far-field light field distribution data is moduloed to obtain the target far-field light intensity distribution data; the target far-field light intensity distribution data is a far-field light intensity distribution image; wherein...

[0023] F represents Fourier transform, j is the imaginary number of Fourier transform, λ is the wavelength of the simulated laser, f is the focal length of the objective lens, there is a preset distance between the virtual transparent sample and the front focal plane of the objective lens, and U0(x0,y0) is the near-field light field distribution data.

[0024] In the above scheme, the step of creating a transparent sample subsurface standard defect database based on the target far-field light intensity distribution data and the corresponding subsurface standard defect parameters includes:

[0025] The target far-field light intensity distribution data, defect type, defect size, defect depth, and corresponding material are written into a preset image library to form the subsurface standard defect database of the transparent sample; wherein...

[0026] The image library stores the correspondence between the target far-field light intensity distribution data, the defect type, the defect size, and the defect depth.

[0027] A second aspect of the present invention provides an apparatus for creating a database of subsurface standard defects for transparent samples, the apparatus comprising:

[0028] The first creation unit is used to create a virtual transparent sample based on preset subsurface standard defect parameters; the subsurface standard defect parameters include: defect type, defect size, defect depth and material; the subsurface of the virtual transparent sample is provided with subsurface standard defects;

[0029] The acquisition unit is used to obtain near-field light field distribution data corresponding to the subsurface standard defects of the virtual transparent sample by applying simulated laser to the subsurface defects of the virtual transparent sample.

[0030] The determining unit is used to determine the corresponding target far-field light intensity distribution data based on the near-field light field distribution data.

[0031] The second creation unit is used to create a transparent sample subsurface standard defect database based on the target far-field light intensity distribution data and the corresponding subsurface standard defect parameters.

[0032] In the above scheme, the determining unit is specifically used for:

[0033] According to the formula The near-field light field distribution data is converted into far-field light field distribution data U. f (x f ,y f );

[0034] The far-field light field distribution data is moduloed to obtain the target far-field light intensity distribution data; the target far-field light intensity distribution data is a far-field light intensity distribution image; wherein...

[0035] F represents Fourier transform, j is the imaginary number of Fourier transform, λ is the wavelength of the simulated laser, f is the focal length of the objective lens, there is a preset distance between the virtual transparent sample and the front focal plane of the objective lens, and U0(x0,y0) is the near-field light field distribution data.

[0036] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method described in any of the first aspects.

[0037] A fourth aspect of the present invention provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the steps of the method described in any of the first aspects.

[0038] This invention provides a method and apparatus for creating a sub-standard surface defect database for transparent samples. The method includes: creating a virtual transparent sample based on preset sub-surface standard defect parameters; the sub-surface standard defect parameters include: defect type, defect size, defect depth, and material; the sub-surface of the virtual transparent sample is provided with sub-surface standard defects; using simulated laser to act on the sub-surface of the virtual transparent sample to obtain near-field light field distribution data corresponding to the sub-surface standard defects of the virtual transparent sample; determining the corresponding target far-field light intensity distribution data based on the near-field light field distribution data; and creating a sub-surface standard defect database for transparent samples based on the target far-field light intensity distribution data and the corresponding sub-surface standard defect parameters. Thus, a corresponding virtual transparent sample can be created according to the required standard defect parameters, which is more efficient than the standard sample production in the prior art. Furthermore, this application uses simulation data to determine the final target far-field light intensity distribution data, reducing human experimental error and improving the accuracy of the standard defect database. Attached Figure Description

[0039] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings.

[0040] In the attached diagram:

[0041] Figure 1 A schematic flowchart illustrating a method for creating a standard subsurface defect database for transparent samples according to an embodiment of the present invention is shown.

[0042] Figure 2 This illustration shows a schematic diagram of the principle of obtaining near-field optical field distribution data to the far field after simulated laser action, according to an embodiment of the present invention.

[0043] Figure 3 A schematic diagram of near-field optical field distribution data according to an embodiment of the present invention is shown;

[0044] Figure 4 This diagram illustrates the target far-field light intensity distribution data according to an embodiment of the present invention.

[0045] Figure 5 A schematic diagram of the structure of a device for creating a standard subsurface defect database for transparent samples according to an embodiment of the present invention is shown;

[0046] Figure 6 A schematic diagram of a computer device structure according to an embodiment of the present invention is shown;

[0047] Figure 7 A schematic diagram of a computer-readable storage medium structure according to an embodiment of the present invention is shown. Detailed Implementation

[0048] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0049] This embodiment provides a method for creating a subsurface standard defect database for transparent samples, which can be applied to simulation platforms, such as the FDTD simulation platform. Figure 1 As shown, the method includes:

[0050] S110, Create a virtual transparent sample based on preset subsurface standard defect parameters; the subsurface standard defect parameters include: defect type, defect size, defect depth and material; the subsurface of the virtual transparent sample is provided with subsurface standard defects;

[0051] To improve sample fabrication efficiency, this embodiment allows for the creation of virtual transparent samples within a simulation platform based on preset subsurface standard defect parameters, and the setting of corresponding subsurface standard defects. Defect parameters include: defect type, defect size, defect depth, and material, etc. The specific implementation is as follows:

[0052] Create a virtual transparent sample;

[0053] Based on the subsurface standard defect parameters, corresponding subsurface standard defects are set on the subsurface of the virtual transparent sample.

[0054] For example, the subsurface standard defect parameters for testing might include: a cuboid shape, dimensions of 50nm × 50nm × 100nm, a glass material, and a depth of 20μm from the upper surface of the transparent glass. Then, a virtual transparent sample can be created arbitrarily, and the corresponding subsurface standard defect can be created on the sample's subsurface based on the subsurface standard defect parameters. This means that a standard defect with a cuboid shape and dimensions of 50nm × 50nm × 100nm exists 20μm below the sample surface.

[0055] In this way, this embodiment can determine the subsurface standard defect parameters according to the test requirements, and quickly create the corresponding virtual transparent sample based on the subsurface standard defect parameters, thereby improving the sample preparation efficiency.

[0056] S111, using simulated laser to act on the subsurface of the virtual transparent sample, the near-field light field distribution data corresponding to the standard defects on the subsurface of the virtual transparent sample is obtained;

[0057] Then, set the light absorption boundary condition type according to the simulation requirements; for example, set the light absorption boundary condition type to a perfectly matched layer, and then use the simulated laser to act on the subsurface standard defect of the virtual transparent sample to obtain the near-field light field distribution data corresponding to the subsurface standard defect of the virtual transparent sample.

[0058] For reference Figure 2 The simulated laser 21 acts on the subsurface of the virtual transparent sample 22 (the surface where the defect is closer to the surface). The laser 21 interacts with the standard defect on the subsurface of the virtual transparent sample 22, resulting in diffraction. The near-field light field distribution data of the diffraction is obtained through simulation.

[0059] That is, by simulating the action of a laser on the subsurface standard defect of the virtual transparent sample, the near-field optical field distribution data corresponding to the subsurface standard defect of the virtual transparent sample is obtained through simulation, including:

[0060] The simulated laser is diffracted through the subsurface defects of the virtual transparent sample to obtain near-field diffraction data.

[0061] The diffraction data is processed to obtain the near-field optical field distribution data corresponding to the subsurface defects of the virtual transparent sample. The near-field optical field distribution data can be found by referring to... Figure 3 .

[0062] S112, determine the corresponding target far-field light intensity distribution data based on the near-field light field distribution data;

[0063] You can continue to refer to this. Figure 2 The virtual transparent sample 22 is positioned at the front focal plane of the objective lens 23, at a predetermined distance from it. The near-field light field propagates in space and converges into the far-field light field after traveling the propagation distance of the objective lens 23. The propagation distance is determined by the focal length of the objective lens 23, which includes the focal length f5 of the front surface and the focal length f6 of the rear surface of the objective lens 23.

[0064] In one implementation, determining the corresponding target far-field optical field distribution data based on near-field optical field distribution data includes:

[0065] According to the formula Converting near-field optical field distribution data to far-field optical field distribution data U f(x f ,y f );

[0066] The far-field light field distribution data is moduloed to obtain the target's far-field light intensity distribution data, which is then presented as a far-field light intensity distribution image.

[0067] F represents the Fourier transform, j is the imaginary number of the Fourier transform, λ is the wavelength of the simulated laser, f is the focal length of the objective lens, there is a preset distance between the transparent sample 22 and the front focal plane of the objective lens 23, and U0(x0,y0) is the near-field light field distribution data.

[0068] In this embodiment, the final determined far-field light intensity distribution image can be referenced. Figure 4 As shown.

[0069] In this way, a corresponding far-field light intensity distribution image can be determined for each type of subsurface standard defect.

[0070] S113, Create a transparent sample subsurface standard defect database based on the target far-field light intensity distribution data and the corresponding subsurface standard defect parameters.

[0071] After the target far-field light intensity distribution data is determined, in one embodiment, a transparent sample subsurface standard defect database is created based on the target far-field light intensity distribution data and the corresponding subsurface standard defect parameters, including:

[0072] The target far-field light intensity distribution data, defect type, defect size, defect depth, and corresponding material are written into a preset image library to form the subsurface standard defect database of the transparent sample; wherein...

[0073] The image library stores the correspondence between the target far-field light field distribution data, the defect type, the defect size, and the defect depth.

[0074] This embodiment can create corresponding virtual transparent samples based on the required subsurface standard defect parameters. Compared with the production of standard samples in the prior art, the production efficiency of virtual transparent samples is higher, and multiple defect types can be simulated quickly. It can also simulate defects at the nanometer scale. Furthermore, this application uses simulation data to determine the final target far-field light intensity distribution data, reducing human experimental errors and improving the accuracy and creation efficiency of the database.

[0075] Based on the same inventive concept as in the foregoing embodiments, this embodiment also provides an apparatus for creating a database of subsurface standard defects for transparent samples, such as... Figure 5 As shown, the device includes:

[0076] The first creation unit 51 is used to create a virtual transparent sample according to preset subsurface standard defect parameters; the subsurface standard defect parameters include: defect type, defect size, defect depth and material; the subsurface of the virtual transparent sample is provided with subsurface standard defects;

[0077] The acquisition unit 52 is used to obtain near-field light field distribution data corresponding to the subsurface standard defects of the virtual transparent sample by using simulated laser to act on the subsurface defects of the virtual transparent sample.

[0078] Determining unit 53 is used to determine the corresponding target far-field light intensity distribution data based on the near-field light field distribution data;

[0079] The second creation unit 54 is used to create a transparent sample subsurface standard defect database based on the target far-field light intensity distribution data and the corresponding subsurface standard defect parameters.

[0080] The determining unit 53 is specifically used for:

[0081] According to the formula The near-field light field distribution data is converted into the far-field light field distribution data U. f (x f ,y f );

[0082] The far-field light field distribution data is moduloed to obtain the target far-field light intensity distribution data; the target far-field light intensity distribution data is a far-field light intensity distribution image; wherein...

[0083] F represents Fourier transform, j is the imaginary number of Fourier transform, λ is the wavelength of the simulated laser, f is the focal length of the objective lens, there is a preset distance between the virtual transparent sample and the front focal plane of the objective lens, and U0(x0,y0) is the near-field light field distribution data.

[0084] Since the apparatus described in the embodiments of this invention is used to implement the method for creating a standard subsurface defect database for transparent samples according to the embodiments of this invention, those skilled in the art can understand the specific structure and variations of the apparatus based on the method described in the embodiments of this invention, and therefore will not be described in detail here. All apparatuses used in the methods of the embodiments of this invention fall within the scope of protection of this invention.

[0085] Based on the same inventive concept, this embodiment provides a computer device 600, such as... Figure 6 As shown, it includes a memory 610, a processor 620, and a computer program 611 stored in the memory 610 and executable on the processor 620. When the processor 620 executes the computer program 611, it implements any step of the method described above.

[0086] Based on the same inventive concept, this embodiment provides a computer-readable storage medium 700, such as... Figure 7 As shown, a computer program 711 is stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0087] Through one or more embodiments of the present invention, the present invention has the following beneficial effects or advantages:

[0088] This invention provides a method and apparatus for creating a sub-standard surface defect database for transparent samples. The method includes: creating a virtual transparent sample based on preset sub-surface standard defect parameters; the sub-surface standard defect parameters include: defect type, defect size, defect depth, and material; the sub-surface of the virtual transparent sample is provided with sub-surface standard defects; using simulated laser to act on the sub-surface of the virtual transparent sample to obtain near-field light field distribution data corresponding to the sub-surface standard defects of the virtual transparent sample; determining the corresponding target far-field light intensity distribution data based on the near-field light field distribution data; and creating a sub-surface standard defect database for transparent samples based on the target far-field light intensity distribution data and the corresponding sub-surface standard defect parameters. Thus, a corresponding virtual transparent sample can be created according to the required standard defect parameters, which is more efficient than the standard sample production in the prior art. Furthermore, this application uses simulation data to determine the final target far-field light intensity distribution data, reducing human experimental error and improving the accuracy of the standard defect database.

[0089] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0090] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0091] Similarly, it should be understood that, in order to simplify this disclosure and aid in understanding one or more of the various aspects of the invention, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, this method of disclosure should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into this detailed description, wherein each claim itself is a separate embodiment of the invention.

[0092] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0093] Furthermore, those skilled in the art will understand that although some embodiments herein include certain features included in other embodiments but not others, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.

[0094] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components of the gateway, proxy server, or system according to embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing some or all of the methods described herein. Such programs implementing the present invention can be stored on a computer-readable medium or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0095] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0096] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0097] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for creating a database of subsurface standard defects for transparent samples, characterized in that, The method includes: A virtual transparent sample is created based on preset subsurface standard defect parameters; the subsurface standard defect parameters include: defect type, defect size, defect depth, and material; the subsurface of the virtual transparent sample is provided with subsurface standard defects; By applying simulated laser light to the subsurface of the virtual transparent sample, near-field optical field distribution data corresponding to standard defects on the subsurface of the virtual transparent sample are obtained. Determine the corresponding target far-field light intensity distribution data based on the near-field light field distribution data; A database of standard subsurface defects for transparent samples is created based on the target far-field light intensity distribution data and the corresponding subsurface standard defect parameters; wherein... A database of subsurface standard defects for transparent samples is created based on the target far-field light intensity distribution data and the corresponding subsurface standard defect parameters, including: The target far-field light intensity distribution data, defect type, defect size, defect depth, and corresponding material are written into a preset image library to form the subsurface standard defect database of the transparent sample; wherein... The image library stores the correspondence between the target far-field light intensity distribution data, the defect type, the defect size, and the defect depth.

2. The method as described in claim 1, characterized in that, The process of creating a virtual transparent sample based on subsurface standard defect parameters includes: Create a virtual transparent sample; Based on the subsurface standard defect parameters, corresponding subsurface standard defects are set on the subsurface of the virtual transparent sample.

3. The method as described in claim 1, characterized in that, After creating the virtual transparent sample based on preset subsurface standard defect parameters, the method further includes: Set the type of light absorption boundary condition according to the simulation requirements.

4. The method as described in claim 1, characterized in that, The method of using simulated laser light to act on the subsurface of the virtual transparent sample to obtain near-field optical field distribution data corresponding to standard defects on the subsurface of the virtual transparent sample includes: The simulated laser is diffracted after passing through the subsurface standard defect of the virtual transparent sample to obtain near-field diffraction data; The near-field diffraction data is processed to obtain the near-field light field distribution data corresponding to the subsurface standard defects of the virtual transparent sample.

5. The method as described in claim 1, characterized in that, Based on the near-field light field distribution data, the corresponding target far-field light field distribution data is determined, including: According to the formula The near-field light field distribution data is converted into far-field light field distribution data U. f (x f ,y f ); The far-field light field distribution data is moduloed to obtain the target far-field light intensity distribution data; the target far-field light intensity distribution data is a far-field light intensity distribution image; wherein... F represents Fourier transform, j is the imaginary number of Fourier transform, λ is the wavelength of the simulated laser, f is the focal length of the objective lens, there is a preset distance between the virtual transparent sample and the front focal plane of the objective lens, and U0(x0,y0) is the near-field light field distribution data.

6. An apparatus for creating a database of subsurface standard defects for transparent samples, characterized in that, The device includes: The first creation unit is used to create a virtual transparent sample based on preset subsurface standard defect parameters; the subsurface standard defect parameters include: defect type, defect size, defect depth and material; the subsurface of the virtual transparent sample is provided with subsurface standard defects; The acquisition unit is used to obtain near-field light field distribution data corresponding to the subsurface standard defects of the virtual transparent sample by applying simulated laser to the subsurface defects of the virtual transparent sample. The determining unit is used to determine the corresponding target far-field light intensity distribution data based on the near-field light field distribution data. The second creation unit is used to create a transparent sample subsurface standard defect database based on the target far-field light intensity distribution data and the corresponding subsurface standard defect parameters; wherein... A database of subsurface standard defects for transparent samples is created based on the target far-field light intensity distribution data and the corresponding subsurface standard defect parameters, including: The target far-field light intensity distribution data, defect type, defect size, defect depth, and corresponding material are written into a preset image library to form the subsurface standard defect database of the transparent sample; wherein... The image library stores the correspondence between the target far-field light intensity distribution data, the defect type, the defect size, and the defect depth.

7. The apparatus as claimed in claim 6, characterized in that, The determining unit is specifically used for: According to the formula The near-field light field distribution data is converted into far-field light field distribution data U. f (x f ,y f ); The far-field light field distribution data is moduloed to obtain the target far-field light intensity distribution data; the target far-field light intensity distribution data is a far-field light intensity distribution image; wherein... F represents Fourier transform, j is the imaginary number of Fourier transform, λ is the wavelength of the simulated laser, f is the focal length of the objective lens, there is a preset distance between the virtual transparent sample and the front focal plane of the objective lens, and U0(x0,y0) is the near-field light field distribution data.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1 to 5.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method according to any one of claims 1 to 5.

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