A material surface and subsurface three-dimensional microstructure imaging method and application

Abstract

A method and application for imaging the three-dimensional microstructure of material surfaces and subsurfaces. The method includes: scanning, acquiring, and calculating samples using an OCT system to obtain micron-level three-dimensional microstructure images of the material surface and subsurfaces; extracting the phase information of the complex signal of the region of interest (ROI) in the micron-level three-dimensional microstructure image to achieve nanometer-level microstructure imaging of that region. The advantages and beneficial effects of this invention compared to existing technologies are: simplicity and efficiency, enabling rapid imaging of micron-level three-dimensional microstructures of material surfaces and subsurfaces; and achieving nanometer-level microstructure imaging of the region of interest.

Description

Technical Field

[0001] This invention belongs to the field of materials imaging and materials testing technology, and specifically relates to a method and application for imaging the three-dimensional microstructure of material surfaces and subsurfaces. Background Technology

[0002] Precision component manufacturing is a crucial component of the electronics and information industry, serving as a necessary foundation for the development of communications, automotive, computer systems, and terminal products. Among its key aspects, the detection of surface and subsurface defects is an indispensable part of precision component manufacturing. Surface defects include cracks, scratches, and embrittlement, while subsurface defects refer to impurities, bubbles, and cracks existing below the surface. During the manufacturing process of precision components, surface and subsurface defects typically range from micrometers to nanometers in size, impacting product quality and performance.

[0003] Various microstructure imaging techniques provide means to analyze the surface and subsurface structural properties of materials. The detection effect on the surface and subsurface of precision components depends on the level of imaging technology. Currently, commonly used methods include scanning electron microscopy (SEM) and fluorescence imaging. However, these methods have certain limitations. SEM is time-consuming and cannot directly image subsurfaces; fluorescence imaging mainly detects the fluorescence emitted by contaminants on the surface and subsurface of products, and cannot visualize structural defects.

[0004] Optical coherence tomography (OCT) is a non-destructive, high-resolution, three-dimensional visualization and real-time imaging technique. Based on the principles of interferometry and heterodyne detection, and relying on a broadband light source, it can achieve imaging of the microstructures of material surfaces and subsurfaces. However, conventional OCT structural imaging or visualization methods typically only achieve micrometer-level resolution, making it difficult to image nanoscale structures.

[0005] Therefore, there is an urgent need for a method for imaging the three-dimensional microstructures of material surfaces and subsurfaces, which can quickly, non-destructively, and comprehensively visualize the micron to nanometer scale of material surface and subsurface structures. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a method for imaging the three-dimensional microstructure of material surfaces and subsurfaces, optimizing the microstructure imaging capability of OCT, and enabling rapid, non-destructive and comprehensive visualization of micron to nanometer-scale structures in material surfaces and subsurfaces.

[0007] To achieve the above objectives, the present invention provides a method for imaging the three-dimensional microstructure of material surfaces and subsurfaces, comprising:

[0008] Step 1: Use an optical coherence tomography (OCT) system to scan, acquire, and calculate the sample to obtain three-dimensional OCT images of the material surface and subsurface with micron-level resolution;

[0009] Step 1.1: Use an OCT system to scan the sample and acquire a three-dimensional interference spectral signal containing information about the sample's depth dimension;

[0010] Step 1.2: Perform a Fourier transform along the depth dimension on the three-dimensional interference spectral signal to obtain a three-dimensional complex signal containing sample structural information;

[0011] Step 1.3: Extract the amplitude information of the three-dimensional complex signal to generate a three-dimensional OCT image of the sample with micron-level resolution.

[0012] Step 2: Extract the phase information of the complex signal of the region of interest in the three-dimensional OCT image to realize the imaging of the nanoscale microstructure of the region of interest;

[0013] Step 2.1: Select the region of interest in the three-dimensional OCT image of the sample, extract the phase information of the three-dimensional complex signal of the region of interest, calculate the phase difference at a certain position P in the region of interest, and generate the phase difference image of the region of interest;

[0014] Step 2.2: Using a frequency domain filtering method to remove interference fringes, long-period interference fringes caused by equal thickness or equal inclination interference in the phase difference image are filtered out to obtain a phase difference image with the interference fringes removed;

[0015] Step 2.3: For the phase difference image with the interference fringes filtered out, calculate the nanometer-level depth difference of the sample surface or subsurface within the region of interest to achieve nanometer-level microstructure imaging of the region of interest.

[0016] Further: In step 2.1, the phase difference of the complex signals of two adjacent and symmetrical positions P1 and P2 in the region of interest is calculated. (As the phase difference at position P), generate a phase difference image of the region of interest. As can be expressed by formula (1):

[0017]

[0018] in, Let C be the phase difference at a location P in the region of interest. P1 and C P2 Let P1 and P2 be complex signals, and Angle() denotes taking the phase of the complex signal.

[0019] Furthermore, the interference fringe filtering method for frequency domain filtering described in step 2.2 includes:

[0020] Step 2.2.1: For the phase difference image of the region of interest, perform a one-dimensional Fourier transform on the image along the undulation direction of the long-period interference fringes in the image to obtain the frequency domain image of the interference fringes in the image;

[0021] Step 2.2.2: Detect the peak value in the frequency domain image of the interference fringes. The position corresponding to the peak value is the frequency position of the interference fringes.

[0022] Step 2.2.3: Set the frequency intensity corresponding to the interference fringes to zero or reduce it to the background noise level to filter out the frequencies corresponding to the interference fringes from the frequency domain image;

[0023] Step 2.2.4: Perform an inverse Fourier transform on the frequency domain image after filtering out the frequencies corresponding to the interference fringes to obtain the complex signal after filtering out the interference fringes;

[0024] Step 2.2.5: Extract the real part information of the complex signal after filtering out the interference fringes to obtain the phase difference image of the filtered interference fringes.

[0025] Further: For the phase difference image of the filtered interference fringes, calculate the nanometer-scale depth difference Δz of the sample surface or subsurface within the region of interest. P To achieve nanoscale microstructure imaging of the region of interest, Δz P As can be expressed by formula (2):

[0026]

[0027] in, Let λ be the phase difference at a location P in the region of interest. c λ is the center wavelength of the OCT system light source, and n is the refractive index of the sample to be tested.

[0028] The material surface and subsurface three-dimensional microstructure imaging method of the present invention can be applied to the detection of material surface roughness and realize non-contact measurement.

[0029] The material surface and subsurface three-dimensional microstructure imaging method of the present invention can also be applied to the detection of microstructure defects on the material surface and subsurface, realizing non-contact measurement.

[0030] The advantages and beneficial effects of this invention compared with the prior art are:

[0031] (1) The method of the present invention can perform three-dimensional imaging of the micron- and nano-scale microstructures of the surface and subsurface of materials;

[0032] (2) The present invention adopts a simple and efficient method of imaging from coarse to fine, which can quickly realize the imaging of micron-level three-dimensional microstructures on the surface and subsurface of materials; and realize the imaging of nanoscale microstructures in the region of interest. Attached Figure Description

[0033] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation on the scope.

[0034] Figure 1 This is a schematic diagram of the process for imaging the three-dimensional microstructure of material surfaces and subsurfaces.

[0035] Figure 2 This is a flowchart illustrating the interference fringe removal method based on frequency domain filtering.

[0036] Figure 3 This is a schematic diagram of an OCT system;

[0037] Figure 4 This is a schematic diagram of the region of interest in a 3D image.

[0038] Figure 5 This is a flowchart example of an interference fringe removal method using frequency domain filtering; where (a) is the phase difference image of the region of interest, and (b) is the image along the frequency domain. Figure 5 (a) Frequency domain image of interference fringes obtained by performing a one-dimensional Fourier transform on the wavy direction of long-period interference fringes; (c) Frequency domain image after filtering out the frequencies corresponding to the interference fringes; (d) Phase difference image of the filtered interference fringes obtained by extracting the real part of the complex signal after performing an inverse Fourier transform on the frequency domain image.

[0039] Figure 6 The images show three-dimensional microstructure diagrams of the surface and subsurface of a 1500-mesh single-sided scattering sheet; (a) is a three-dimensional microstructure diagram of the scattering surface and subsurface of the 1500-mesh single-sided scattering sheet detected by the detection method and system in this embodiment; (b) is a nanoscale microstructure diagram of the scattering surface of the 1500-mesh single-sided scattering sheet detected by the detection method and system in this embodiment; and (c) is a nanoscale microstructure diagram of the smooth surface of the 1500-mesh single-sided scattering sheet detected by the detection method and system in this embodiment. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0041] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without inventive effort are within the scope of protection of this invention.

[0042] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0043] Figure 1 This is a schematic diagram of the process for imaging the micron- to nanometer-scale microstructures of material surfaces and subsurfaces based on an OCT system according to the present invention. The OCT system used to acquire interference spectral information includes, but is not limited to: a full-field OCT system, a time-domain OCT system, a spectral-domain OCT system, and a swept-frequency source OCT system. The imaging method includes:

[0044] Step 100: Use an OCT system to scan the sample to be tested and acquire a three-dimensional interference spectrum signal containing the depth dimension information of the sample. The OCT system used in this embodiment is a spectral domain OCT system, as shown in the attached figure. Figure 3 As shown.

[0045] Step 200: Perform a Fourier transform along the depth dimension on the three-dimensional interference spectral signal to obtain a three-dimensional complex signal containing structural information of the sample to be detected.

[0046] Step 300: Extract the amplitude information of the three-dimensional complex signal to generate a three-dimensional OCT image of the sample to be tested with micron-level resolution.

[0047] Step 400: Select the region of interest (ROI) in the three-dimensional OCT image of the sample, as shown in Figure (4). Extract the phase information of the three-dimensional complex signal of the ROI. Calculate the phase difference between the complex signals of two adjacent and symmetrical positions P1 and P2 within the ROI. This phase difference is the phase difference of position P, expressed as: Generate a phase difference image of the region of interest. As can be expressed by formula (1):

[0048]

[0049] Among them, C P1 and C P2 Let P1 and P2 be complex signals, and Angle() denotes taking the phase of the complex signal.

[0050] Step 500: Using a frequency domain filtering method to remove interference fringes, long-period interference fringes caused by equal thickness or equal inclination interference in the phase difference image are filtered out, to obtain a phase difference image with the interference fringes removed, as shown in the attached figure. Figure 5 As shown.

[0051] Figure 2 This is a flowchart illustrating the interference fringe removal method for frequency domain filtering according to the present invention. The removal method includes:

[0052] Step 501: For the phase difference image of the region of interest, as shown in the attached image. Figure 5 As shown in (a), a one-dimensional Fourier transform is performed on the image along the undulation direction of the long-period interference fringes in the image to obtain the frequency domain image of the interference fringes in the image.

[0053] Step 502: Detect the peak value in the frequency domain image of the interference fringes. The position corresponding to the peak value is the frequency position of the interference fringes, as shown in the attached figure. Figure 5 As shown in (b).

[0054] Step 503: Set the frequency intensity corresponding to the interference fringes to zero or reduce it to the background noise level. This will filter out the frequencies corresponding to the interference fringes from the frequency domain image, as shown in the attached figure. Figure 5 As shown in (c).

[0055] Step 504: Perform an inverse Fourier transform on the frequency domain image after filtering out the frequencies corresponding to the interference fringes to obtain the complex signal after filtering out the interference fringes;

[0056] Step 505: Extract the real part of the complex signal after filtering out the interference fringes to obtain the phase difference image of the filtered interference fringes, as shown in the attached figure. Figure 5 As shown in (d).

[0057] Step 600: For the phase difference image with the interference fringes filtered out, calculate the nanometer-scale depth difference Δz of the sample surface or subsurface within the region of interest. P To achieve nanoscale microstructure imaging of the region of interest, Δz P As can be expressed by formula (2):

[0058]

[0059] in, Let λ be the phase difference at a location P in the region of interest. c λ is the center wavelength of the OCT system light source, and n is the refractive index of the sample to be tested.

[0060] Figure 3This is a schematic diagram of an OCT system used in this embodiment, namely a spectral domain OCT system. The imaging system in this embodiment includes: a broadband light source 700, an optical interferometer 710 with a sample scanning device, a detection device 720, and a signal processing device 730.

[0061] In this embodiment, the broadband light source 700 is used to output a broadband light beam, which enters the optical interferometer 710 with a sample scanning device.

[0062] In this embodiment, the optical interferometer 710 uses a 50:50 unpolarized beam splitter 711 to split the beam into a reference beam and a sample detection beam. The reference beam passes through a dispersion compensator 712 and is reflected back to the beam splitter 711 by a gold mirror 713. The sample detection beam scans the sample 740 through a sample scanning device 714. The sample used in this embodiment is a 1500-mesh single-sided scattering sheet.

[0063] In the embodiment, the scanning device 714 scans the scattering sample 740 through a two-dimensional galvanometer 715 and a scanning objective lens 716. The backscattered light containing the surface structure of the scattering sample passes through the scanning device 714 and then passes through the beam splitter 711 to form interference with the reference light. After that, the interference light enters the detection device 720.

[0064] In this embodiment, the detection device 720 is a high-speed spectrometer. The spectrometer receives interference light signals and converts them into electrical signals, which are then transmitted to the signal processing device 730 for calculation. In this embodiment, the signal processing device 730 is a computer equipped with a high-speed signal acquisition card.

[0065] The interference spectrum signal acquired by the signal processing device 730 is used to realize the microstructure imaging of the sample based on the processing method described above in this invention. In this embodiment, the scattering sheet is imaged, and the micron-level three-dimensional microstructure on the surface and subsurface of the scattering sheet and the nano-level three-dimensional microstructure on both sides are realized.

[0066] Figure 4 This is a schematic diagram of the region of interest (ROI) in a 3D OCT image. In the 3D OCT image, the region to be imaged is manually selected as the ROI, and then the ROI is further imaged at the nanoscale microstructure level according to the method described above. Here, P is a location within the ROI, and P1 and P2 are two adjacent and symmetrical locations to location P.

[0067] Figure 5 This is a flowchart example of the interference fringe removal method using frequency domain filtering in this embodiment. Figure 5 (a) is the phase difference image of the region of interest. Figure 5 (b) is along Figure 5 (a) Frequency domain image of interference fringes obtained after performing a one-dimensional Fourier transform on the wavy direction of long-period interference fringes; Figure 5(c) is the frequency domain image after filtering out the frequencies corresponding to the interference fringes; Figure 5 (d) is the phase difference image obtained by extracting the real part of the complex signal after inverse Fourier transform of the frequency domain image, with interference fringes removed. (Comparison) Figure 5 (a) and Figure 5 (d) It can be seen that the interference fringe filtering method proposed in this invention can effectively filter out the influence of interference fringes.

[0068] Figure 6 This is a three-dimensional microstructure diagram of the surface and subsurface of a 1500-mesh single-sided scattering sheet. Figure 6 (a) is a three-dimensional microstructure diagram of the scattering surface and subsurface of a 1500-mesh single scattering sheet detected by the detection method and system described in this embodiment; Figure 6 (b) is a nanoscale microstructure diagram of the scattering surface of a 1500-mesh single-sided scattering sheet detected by the detection method and system described in this embodiment; Figure 6 (c) is a nanoscale microstructure diagram of the smooth surface of a 1500-mesh single-sided scattering sheet, detected using the detection method and system described in this embodiment. Figure 6 (b) and Figure 6 (c) provides a grayscale color bar, using grayscale colors to reflect the undulations of the surface microstructure. (Comparison) Figure 6 (b) and Figure 6 (c) As can be seen, the method proposed in this invention can visualize the nanoscale structure of the upper and lower surfaces of the scattering sheet, and the scattering surface has more obvious granular structure undulations compared with the smooth surface.

[0069] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it. They should not be used to limit the scope of protection of the present invention. All equivalent changes or modifications made in accordance with the spirit and essence of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for imaging the three-dimensional microstructure of a material surface and subsurface, characterized in that, include: Step 1: Use an optical coherence tomography (OCT) system to scan, acquire, and calculate the sample to obtain three-dimensional OCT images of the material surface and subsurface with micron-level resolution; Step 2: For the region of interest in the 3D OCT image, extract the phase information of the complex signal of the region of interest to achieve nanoscale microstructure imaging of the region of interest, including: Step 2.1: Select the region of interest (ROI) in the 3D OCT image of the sample, extract the phase information of the 3D complex signal of the ROI, calculate the phase difference at a certain position P in the ROI, and generate a phase difference image of the ROI. The method for calculating the phase difference at a certain position P in the ROI is to calculate the phase difference of the complex signals of two adjacent and symmetrical positions P1 and P2. This phase difference is the phase difference at position P, expressed as: The calculation formula is as follows: (1) in, and The complex signals are the two positions P1 and P2. Indicates the phase of a complex signal; Step 2.2: Using a frequency domain filtering method to remove interference fringes, long-period interference fringes caused by equal thickness or equal inclination interference in the phase difference image are filtered out to obtain a phase difference image with the interference fringes removed, including: Step 2.2.1: For the phase difference image of the region of interest, perform a one-dimensional Fourier transform on the image along the undulation direction of the long-period interference fringes in the image to obtain the frequency domain image of the interference fringes in the image; Step 2.2.2: Detect the peak value in the frequency domain image of the interference fringes. The position corresponding to the peak value is the frequency position of the interference fringes. Step 2.2.3: Set the frequency intensity corresponding to the interference fringes to zero or reduce it to the background noise level to filter out the frequencies corresponding to the interference fringes from the frequency domain image; Step 2.2.4: Perform an inverse Fourier transform on the frequency domain image after filtering out the frequencies corresponding to the interference fringes to obtain the complex signal after filtering out the interference fringes; Step 2.2.5: Extract the real part of the complex signal after filtering out the interference fringes to obtain the phase difference image of the filtered interference fringes; Step 2.3: For the phase difference image with the interference fringes filtered out, calculate the nanometer-level depth difference of the sample surface or subsurface within the region of interest to achieve nanometer-level microstructure imaging of the region of interest.

2. The method for imaging the three-dimensional microstructure of material surfaces and subsurfaces according to claim 1, characterized in that... Methods for obtaining three-dimensional OCT images of material surfaces and subsurfaces with micrometer-level resolution by scanning, acquiring, and calculating using an OCT system include: Step 1.1: Use an OCT system to scan the sample and acquire a three-dimensional interference spectral signal containing information about the sample's depth dimension; Step 1.2: Perform a Fourier transform along the depth dimension on the three-dimensional interference spectral signal to obtain a three-dimensional complex signal containing sample structural information; Step 1.3: Extract the amplitude information of the three-dimensional complex signal to generate a three-dimensional OCT image of the sample with micron-level resolution.

3. The method for imaging the three-dimensional microstructure of material surfaces and subsurfaces according to claim 1, characterized in that... Calculate the nanometer-scale depth difference of the sample surface or subsurface within the region of interest. The method for imaging the nanoscale microstructure of the region of interest is calculated using the following formula (2): (2) in, Let P be the phase difference at a certain location P in the region of interest. λ is the center wavelength of the OCT system light source, and n is the refractive index of the sample.

4. The application of the material surface and subsurface three-dimensional microstructure imaging method according to any one of claims 1 to 3, characterized in that... This method can be applied to the detection of material surface roughness, enabling non-contact measurement.

5. The application of the material surface and subsurface three-dimensional microstructure imaging method according to any one of claims 1 to 3, characterized in that... This method can be applied to the detection of microstructural defects on and subsurface surfaces of materials, enabling non-contact measurement.

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