A material laser damage threshold measurement method, system, device and storage medium

Abstract

The present application relates to the technical field of engineering optical element surface laser damage evaluation, and particularly relates to a material laser damage threshold measurement method, system, device and storage medium, the method obtains and gray scale processes the optical microscopic image of the femtosecond laser irradiation area; low-frequency information extraction is carried out on the image after gray scale processing to remove noise and detail interference, the extracted low-frequency information is optimized, laser damage characteristic areas are identified and extracted, and the diameter of the laser damage characteristic area and its relationship with laser energy are calculated to realize the calculation of the laser damage threshold. Compared with the traditional experimental method, the method can complete the automatic identification and area calculation of the ablation area in a short time, greatly improve the measurement efficiency, and no longer rely on tedious manual operation, avoid the uncertainty caused by the subjective factors of the measurement personnel and local defects, and solve the problems of low measurement efficiency and poor precision of the material femtosecond laser damage threshold in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of laser damage evaluation of optical element surface, in particular to a material laser damage threshold measurement method, system, device and storage medium, and especially to a material laser damage threshold automatic calculation method, system, device and storage medium using machine recognition algorithm. BACKGROUND

[0002] Hard and brittle materials such as diamond, sapphire and quartz glass have been widely used in aerospace, military, high-energy physics, integrated circuits, biomedicine and optoelectronic devices. Laser processing technology is an effective, non-contact material processing technology. In the interaction between laser and matter, for a specific laser pulse duration, when the critical energy or power density of the laser exceeds this critical value, the phenomenon of changing the properties of the material will be induced in the focal region. This critical point is called laser damage threshold (LDT), which is a key parameter for laser processing and material removal efficiency. The concept of damage threshold is the basis for understanding and predicting the effect of laser processing, which is closely related to the wavelength, pulse width, beam quality of the laser and the physical and chemical properties of the material. When the energy or power density of the laser reaches or exceeds the LDT, the laser processing process can be effectively carried out, resulting in rapid modification or removal of the material. Conversely, if the energy or power density of the laser is lower than the LDT, the material will not change or the modification efficiency will be very low.

[0003] Femtosecond laser can realize the preparation of micro-nano structure of hard and brittle materials with almost no thermal influence area because its pulse duration is significantly shorter than the time scale of electron-lattice interaction. In addition, due to the existence of femtosecond laser damage threshold effect and the mechanism of nonlinear absorption, the spatial resolution of laser processing of hard and brittle materials can exceed the diffraction limit of light. Therefore, the study of LDT of materials is of great significance to improve the spatial resolution of femtosecond laser processing of materials and provide reference for processing scheme. On the other hand, diamond, sapphire and quartz glass are typical window materials in the field of high-energy physics research such as ultrafast laser wakefield acceleration, high-order harmonic generation and attosecond generation, and laser nuclear fusion. The laser damage resistance of optical window is one of the key factors restricting the progress of the above research fields. Therefore, the measurement of femtosecond laser damage threshold of typical window materials plays a key role in improving the understanding of the laser damage resistance of materials and expanding their application scenarios.

[0004] The main methods for obtaining LDT are direct measurement method, model calculation method and extrapolation method. The direct measurement method can quickly obtain data due to its simple operation, and is suitable for small batch and initial material LDT testing. The LDT of the material is related to the parameters of the laser, such as wavelength, pulse width, repetition frequency and the type of laser processing focusing objective, and a large number of measurement work is needed. In addition, due to the existence of local defects or non-uniformity of the material, early damage may occur, so that the direct measurement method experiment has the problem of uncertainty of the results, and a large number of experimental verification is needed. The model calculation method predicts the LDT by simulating the process of laser and material interaction through the computer, which avoids a large number of experimental verification, can provide accurate prediction of LDT and reveal the physical mechanism. However, the mechanism of femtosecond laser and material interaction is complex, and it is difficult to establish an accurate physical model. In addition, the physical model is complex, the calculation cost is high, and the accuracy of the parameters is high, which is difficult to meet the actual processing environment.

[0005] The extrapolation method is a method for deriving LDT by finding the relationship between laser processing parameters and damage morphology. The most commonly used method is the damage diameter extrapolation LDT method. In 2016, Chen et al. studied the single-pulse damage threshold and multi-pulse cumulative damage threshold of single crystal diamond by using this method. The extrapolation method combines the advantages of simple operation of the direct measurement method, and by measuring the diameter of the damage area with a certain area, the problem of early death area of the material is avoided. Then, the LDT of the material is predicted by using the relationship between the processing parameters and the diameter of the damage area, which avoids a large number of experiments and reduces the measurement cost. However, this method often needs a large number of experimental results for statistical analysis, and the area of the damage region is usually measured manually. Especially in the case of exploring the influence of multiple parameters on LDT, a high time cost is required, and the damage structure often appears non-standard circular symmetric structure, which also becomes a challenge for manual measurement of damage area. Therefore, how to improve the measurement efficiency and accuracy of the extrapolation method is the key to promote the development of femtosecond laser damage material threshold measurement and its application field. SUMMARY

[0006] In view of the low measurement efficiency and poor accuracy of the material femtosecond laser damage threshold in the prior art, the application provides a material laser damage threshold measurement method, system, device and storage medium.

[0007] To achieve the above purpose, the following technical solutions are adopted:

[0008] The application provides a material laser damage threshold measurement method, comprising:

[0009] Obtaining an optical microscope image of a femtosecond laser irradiation area;

[0010] Performing gray scale processing on the optical microscope image of the femtosecond laser irradiation area;

[0011] extracting image low-frequency information from the gray-scale processed optical microscopic image, and optimizing the image low-frequency information to obtain optimized image low-frequency information; wherein the image low-frequency information comprises outline information in a central region and related periodic information thereof;

[0012] extracting a laser damage feature region from the optimized image low-frequency information, and calculating a diameter of the laser damage feature region; wherein the laser damage feature region is a circular laser damage feature region or an edge-closed region;

[0013] calculating a laser damage threshold according to the diameter of the laser damage feature region.

[0014] Optionally, the method for obtaining the optical microscopic image of the femtosecond laser irradiation region comprises:

[0015] characterizing and observing the structure and morphology of the femtosecond laser irradiation region by using a high-power microscope objective lens with a magnification of 5X or more, and collecting the optical microscopic image of the femtosecond laser irradiation region by using a CCD.

[0016] Optionally, the method for extracting image low-frequency information from the gray-scale processed optical microscopic image, and optimizing the image low-frequency information to obtain optimized image low-frequency information comprises:

[0017] performing two-dimensional Fourier transform on the gray-scale processed optical microscopic image to extract outline information in a central region and related periodic information thereof, and obtaining low-frequency information;

[0018] performing low-pass filtering processing on the low-frequency information by using a circular mask with a radius of R to remove noise information of the outline information;

[0019] sequentially performing inverse Fourier transform, Gaussian blur processing and binarization processing on the low-frequency information after the low-pass filtering processing to obtain optimized image low-frequency information.

[0020] Optionally, the method for extracting a laser damage feature region from the optimized image low-frequency information, and calculating a diameter of the laser damage feature region comprises:

[0021] extracting a laser damage feature region from the optimized image low-frequency information by using Hough transform;

[0022] performing pixel point radius statistics on the laser damage feature region, and calculating a diameter of the laser damage feature region.

[0023] Optionally, the method for extracting a laser damage feature region from the optimized image low-frequency information, and calculating a diameter of the laser damage feature region comprises:

[0024] The edge detection algorithm is used to extract the laser damage feature area from the optimized image low-frequency information; the laser damage feature area is the edge of the closed area in the image;

[0025] The morphological closing operation is used to fill the discontinuous edge points of the laser damage feature area, and the area of the laser damage feature area is calculated;

[0026] According to the area of the laser damage feature area, the diameter of the laser damage feature area is calculated.

[0027] Optionally, the method for calculating the laser damage threshold according to the diameter of the laser damage feature area is:

[0028] According to the diameter of the laser damage feature area, the square of the diameter of the laser damage feature area is obtained;

[0029] The square of the diameter of the laser damage feature area is linearly fitted with the logarithmic value of the average power of the laser beam to obtain the slope and the X-axis intercept of the linear fitting;

[0030] According to the slope and the X-axis intercept of the linear fitting, the laser damage threshold is calculated.

[0031] Optionally, the method for calculating the laser damage threshold according to the slope and the X-axis intercept of the linear fitting is:

[0032]

[0033] wherein, is the laser damage threshold, is the slope of the linear fitting, is the X-axis intercept, is the laser repetition frequency.

[0034] The present application also provides a material laser damage threshold measurement system, comprising:

[0035] An image acquisition module is used to acquire the optical microscopic image of the femtosecond laser irradiation area;

[0036] An image gray processing module is used to perform gray processing on the optical microscopic image of the femtosecond laser irradiation area;

[0037] An image low-frequency information extraction module is used to extract the image low-frequency information from the gray-processed optical microscopic image, and to optimize the image low-frequency information to obtain the optimized image low-frequency information; wherein the image low-frequency information includes the contour information in the central area and the related periodic information;

[0038] The diameter calculation module is used for extracting a laser damage feature area from the optimized low-frequency information of the image and calculating the diameter of the laser damage feature area; wherein the laser damage feature area is a circular laser damage feature area or an edge closed area.

[0039] The laser damage threshold calculation module is used for calculating the laser damage threshold according to the diameter of the laser damage feature area.

[0040] A terminal device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the above method when executing the computer program.

[0041] A computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the above method.

[0042] Compared with the prior art, the present application has the following beneficial effects:

[0043] The present application provides a kind of material laser damage threshold measurement method, which is obtained by femtosecond laser irradiation area optical microscopic image and gray processing, gray processing can remove color information in image, retain key morphology and texture features, simplify image data of femtosecond laser irradiation area optical microscopic image, facilitate subsequent image processing;Low-frequency information extraction is carried out on the image after gray processing, to remove noise and detail interference, retain the main structure and features of the image is the key to analyze laser damage, in the optimized low-frequency image, laser damage feature area is identified and extracted, and the diameter of laser damage feature area is calculated to realize the calculation of laser damage threshold.Compared with the traditional experimental method, the present application combines image processing technology to identify laser damage area and calculate average damage area, can complete the automatic identification and area calculation of ablation area in a short time, greatly improves the measurement efficiency, and no longer depends on tedious manual operation, avoids the uncertainty caused by subjective factors and local defects of measurement personnel, thereby significantly improves the measurement accuracy and reliability, significantly reduces the measurement cost.The method can be widely applied to the measurement of laser damage threshold of different kinds and different structures of materials by more accurately and efficiently measuring the laser damage threshold of materials, and provides strong support for its practical application in the fields of material science, laser technology and optical engineering.

[0044] The structure and morphology of the femtosecond laser irradiation area are characterized and observed by using a high-power microscope objective with a magnification of 5X or more, and the optical microscopic images of the femtosecond laser irradiation area are collected by using a CCD. The high-power microscope objective with a magnification of 5X or more can significantly magnify the observation object, so that the microstructure and morphology of the femtosecond laser irradiation area can be clearly displayed. As a high-sensitivity image sensor, the CCD can convert the image under the microscope into a high-quality digital signal. Compared with the traditional image collection method, the CCD has higher resolution and clarity, and can more truly restore the morphological characteristics of the femtosecond laser irradiation area.

[0045] The method extracts the contour information and its related periodic information in the central region by performing two-dimensional Fourier transform on the gray-scale processed optical microscopic image, obtains low-frequency information, and removes noise information to the contour information by performing low-pass filtering processing on the low-frequency information using a circular mask with a radius R. The low-frequency information after low-pass filtering processing is sequentially subjected to inverse Fourier transform, Gaussian blur processing and binaryzation processing to obtain optimized image low-frequency information. Among them, by two-dimensional Fourier transform, the gray-scale processed optical microscopic image is converted from spatial domain to frequency domain, so that the low-frequency information containing the main structure and characteristics in the image and the high-frequency information containing the details and noise are separated, the contour information and its related periodic information in the central region are extracted, and the main structure and characteristics in the image can be accurately captured, providing a basis for subsequent low-pass filtering processing; the low-frequency information is subjected to low-pass filtering processing using a circular mask with a radius R, which can further remove noise information to the contour information and improve the purity and accuracy of the low-frequency information; the low-frequency information after low-pass filtering processing is converted from frequency domain to spatial domain by inverse Fourier transform, and the optimized low-frequency image is obtained. This step makes the main structure and characteristics of the image remain, while removing high-frequency noise and detail interference, improving the clarity and readability of the image; the low-frequency image after inverse Fourier transform is subjected to Gaussian blur processing, which can further smooth the image and reduce the interference of noise and details to the main structure and characteristics; Gaussian blur processing can enhance the overall contrast of the image, making the main structure and characteristics more prominent; the low-frequency image after Gaussian blur processing is subjected to binaryzation processing, which converts the image to black and white, further simplifies the image data, highlights the main structure and characteristics, and the image after binaryzation processing is more intuitive and clear, facilitating subsequent feature extraction and image analysis.

[0046] The method extracts the laser damage feature area from the optimized image low-frequency information by using the Hough transform; the radius of the laser damage feature area is counted, and the diameter of the laser damage feature area is calculated. The Hough transform is an effective feature extraction algorithm, and is particularly suitable for extracting geometric shapes such as straight lines and circles from complex images. In the method, the Hough transform is used to extract the laser damage feature area from the optimized image low-frequency information, which can accurately capture the outline and shape of the damage area, thereby laying a reliable foundation for calculating the diameter of the laser damage feature area.

[0047] The method extracts the laser damage feature area from the optimized image low-frequency information by using the edge detection algorithm; the laser damage feature area is the edge of the closed region in the image; the morphological closing operation is used to fill the discontinuous edge points of the laser damage feature area, and the diameter of the laser damage feature area is calculated. Edge detection is an important research direction in the field of machine vision and image processing, which can accurately identify the points with obvious brightness change in the digital image, thereby greatly reducing the redundant information in the image and retaining the part with structural information in the image. The edge detection algorithm is used to extract the laser damage feature area from the optimized image low-frequency information, which can accurately capture the edge outline of the damage area. The morphological closing operation is an operation in image morphology, which can eliminate small holes in the image, fill small breaks, smooth the boundaries of objects and connect narrow gaps. It is used to fill the discontinuous edge points of the laser damage feature area, enhances the integrity of the feature area, makes the edge of the laser damage feature area smoother and more continuous, and reduces the edge breakage and irregularity caused by noise and detail interference.

[0048] The application provides a material laser damage threshold measurement system, which comprises an image acquisition module, an image gray processing module, an image low-frequency information extraction module, a diameter calculation module and a laser damage threshold calculation module. The image acquisition module is responsible for acquiring optical microscopic images of a femtosecond laser irradiation area. The image gray processing module is responsible for performing gray processing on the acquired optical microscopic images, and converting color images into gray images, so as to perform subsequent image processing and analysis. The image low-frequency information extraction module is responsible for extracting low-frequency information from the gray-processed images, and performing optimization processing, so as to obtain clearer and more accurate image low-frequency information. The diameter calculation module is responsible for extracting laser damage feature areas from the optimized image low-frequency information, and calculating the diameters of the feature areas. The laser damage threshold calculation module is responsible for measuring the laser damage threshold of the material. The system realizes automatic and accurate evaluation of image recognition, processing and damage degree of the femtosecond laser irradiation area, has the advantages of high automation degree, high measurement accuracy and strong applicability, and can be widely applied to laser damage threshold measurement in the fields of material science and optical engineering.

[0049] The application further provides a terminal device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0050] A computer readable storage medium stores a computer program, wherein the computer program is executed by a processor to implement the steps of the above method. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 A flowchart of a material laser damage threshold measurement method of the application.

[0052] Figure 2 A process diagram from femtosecond laser processing and characterization to material laser damage threshold measurement in an embodiment of the application.

[0053] Figure 3 An optical microscope image collected by a CCD after ultrasonic cleaning after MCD irradiation in an embodiment of the application.

[0054] Figure 4 A gray-scale image after gray-scale processing of an original microscope image in an embodiment of the application.

[0055] Figure 5 An image after two-dimensional Fourier transform of the gray-scale image in an embodiment of the application.

[0056] Figure 6 An image after low-pass filtering of the image after two-dimensional Fourier transform in an embodiment of the application.

[0057] Figure 7 An image after inverse Fourier transform of the image after low-pass filtering in an embodiment of the application.

[0058] Figure 8 An image after Gaussian blur processing of the image after inverse Fourier transform in an embodiment of the application.

[0059] Figure 9 An image after binarization processing of the image after Gaussian blur processing in an embodiment of the application.

[0060] Figure 10 An image after Hough transform detection of the image after binarization processing in an embodiment of the application, wherein a damage area with a circular feature in the image is detected, and a proportion of imaging pixels is converted into an actual radius and displayed on the image.

[0061] Figure 11 The total result graph after the femtosecond laser irradiation on the MCD at different powers is recognized by the automatic recognition algorithm in the embodiment of the application.

[0062] Figure 12 It is a structural schematic diagram of a material laser damage threshold measurement system of the application. DETAILED DESCRIPTION

[0063] In order for those skilled in the art to better understand the application scheme, the technical scheme in the embodiment of the application will be described clearly and completely in the following with reference to the drawings in the embodiment of the application. Obviously, the described embodiment is only a part of the embodiment of the application, not all. Based on the embodiment in the application, all other embodiments obtained by those skilled in the art without creative labor should belong to the protection scope of the application.

[0064] It should be noted that the terms "first", "second" and the like in the specification and claims of the application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0065] The application will be further described in detail below with reference to specific embodiments, which are an explanation of the application rather than a limitation.

[0066] Referring to Figure 1 The application discloses a material laser damage threshold measurement method, comprising

[0067] S1: obtaining an optical microscopic image of the femtosecond laser irradiation area, specifically:

[0068] A high-power microscope objective lens with a magnification of 5X or more is used to characterize and observe the structure and morphology of the femtosecond laser irradiation area, and a charge-coupled device (CCD) is used to collect the optical microscopic image of the femtosecond laser irradiation area.

[0069] S2: performing gray scale processing on the optical microscopic image of the femtosecond laser irradiation area, specifically:

[0070] The obtained optical microscopic image of the femtosecond laser irradiation area is input into matlab software for gray scale processing.

[0071] S3: image low-frequency information extraction is performed on the gray scale processed optical microscopic image, and optimization is performed to obtain optimized image low-frequency information; wherein the image low-frequency information includes contour information in the central region and related periodic information, specifically:

[0072] The gray scale processed optical microscopic image is subjected to two-dimensional Fourier transform, and the contour information in the central region and the related periodic information are extracted to obtain low-frequency information.

[0073] A circular mask with a radius R is used to perform low-pass filtering processing on the low-frequency information to remove noise information of the contour information; preferably, the radius R of the circular mask is 100-150 Pixel;

[0074] The low-pass filtered low-frequency information is subjected to inverse Fourier transform, Gaussian blur processing and binarization processing in sequence to obtain optimized image low-frequency information.

[0075] S4: laser damage feature region extraction is performed on the optimized image low-frequency information, and the diameter of the laser damage feature region is calculated; wherein the laser damage feature region is a circular laser damage feature region or an edge closed region, specifically:

[0076] The optimized image low-frequency information is subjected to laser damage feature region extraction by using Hough transform;

[0077] The pixel radius of the laser damage feature region is counted and directly converted into actual radius to calculate the diameter of the laser damage feature region.

[0078] Or

[0079] The optimized image low-frequency information is subjected to laser damage feature region extraction by using edge detection algorithm; the laser damage feature region is the edge of the closed region in the image;

[0080] The discontinuous edge points of the laser damage feature region are filled by using morphological closing operation, and the area of the laser damage feature region is calculated.

[0081] The diameter of the laser damage feature region is calculated according to the area of the laser damage feature region.

[0082] S5: the laser damage threshold is calculated according to the diameter of the laser damage feature region, specifically:

[0083] The square of the diameter of the laser damage feature region is obtained according to the diameter of the laser damage feature region.

[0084] Linearly fitting the square of the diameter of the laser damage characteristic region and the logarithmic value of the average power of the laser beam, to obtain the slope of the linear fitting and the intercept of the X axis;

[0085] According to the slope of the linear fitting and the intercept of the X axis, the laser damage threshold is calculated:

[0086]

[0087] Wherein, is the laser damage threshold, is the slope of the linear fitting, is the intercept of the X axis, is the laser repetition frequency;

[0088] Principle:

[0089] For the single pulse energy of the femtosecond laser with Gaussian distribution, the relationship between the laser energy density and the beam cross section radius can be described by the following formula:

[0090]

[0091] Wherein, is the peak energy density of the laser beam; is the beam cross section radius; is the laser spot radius.

[0092] From formula (2), the single pulse energy of the laser can be deduced as:

[0093]

[0094] The central energy density of the laser is calculated as:

[0095]

[0096] Wherein, is the single pulse energy of the laser; is the laser repetition frequency, is the average power of the laser beam;

[0097] Therefore, the relationship between the damage diameter of the laser and the laser energy density is deduced as:

[0098]

[0099] Wherein, is the damage point diameter generated by the laser, is the LDT when the laser interacts with the material.

[0100] ​The LDT of a material is the fluence of the laser when the laser-induced damage spot has a diameter of zero. By measuring the size of the damage spot at different laser powers, a line with a slope of and is obtained. The X-intercept of the line, i.e. the value of when , is taken as the critical average power , and is brought back into the equation to obtain , i.e. the LDT of the interaction of femtosecond laser with the material, as shown in equation (1). The following takes a certain raw material as an example to further illustrate and verify the method: Raw material: Microcrystalline Diamond (MCD) with a thickness of 550 nm and a boron doping concentration of 500 ppm is grown on a (100) oriented single crystal silicon wafer with a thickness of 500 μm by hot wire CVD technology.

[0101] Referring to , a horizontal polarization femtosecond Gaussian laser (laser pulse frequency of 1 kHz, initial polarization state of horizontal linear polarization

[0102] , pulse width of 50 fs, output energy of 3.5 mJ) with a central wavelength of 800 nm is generated by a titanium sapphire amplification laser (Libra-USP-HE). The femtosecond laser beam is focused to the surface of the sample through a Nikon 5X objective lens (NA=0.15), and the MCD surface is etched at a rate of 8 mm / s. The diamond film modified and etched by femtosecond laser is ultrasonically cleaned.

[0103] The structure and morphology of the femtosecond laser irradiation area are characterized and observed by using a 5X high-power microscope objective, and the optical microscopic images of the femtosecond laser irradiation area are collected by a CCD, as shown in Figure 2 . The optical microscopic images of the femtosecond laser irradiation area are imported into matlab software for grayscale processing, as shown in

[0104] ; and the optical microscopic images after grayscale processing are subjected to two-dimensional Fourier transform to extract the contour information and related periodic information in the central region, and obtain low-frequency information, as shown in Figure 3 .

[0105] The optical microscopic images of the femtosecond laser irradiation area are imported into matlab software for grayscale processing, as shown in Figure 4 ; and the optical microscopic images after grayscale processing are subjected to two-dimensional Fourier transform to extract the contour information and related periodic information in the central region, and obtain low-frequency information, as shown in Figure 5 .

[0106] ​A circular mask with a radius of R = 100 pixels is used to perform low-pass filtering on the low-frequency information, removing some high-frequency noise information that is harmful to contour recognition while retaining the contour information. Figure 6 .

[0107] The low-frequency information after low-pass filtering is subjected to inverse Fourier transform, Gaussian blur processing and binarization processing in sequence to obtain optimized image low-frequency information. Figures 7 to 9 It can be seen that after a series of image processing, the optimized image low-frequency information is obtained, and the contour shape is clear, which lays a reliable foundation for the subsequent identification of the laser damaged area.

[0108] Hough Transform is used to detect the damaged area with circular features in the optimized low-frequency information of the image, that is, the laser damage feature area; all possible pixel radii of the damaged area are traversed. , determine all possible circle centers The position of the accumulator array corresponds to the point with the most votes in the Hough space. The parameters of the approximate circle of the detected damage area are converted into the actual radius according to the ratio of imaging pixels, and the diameter of the laser damage characteristic area is obtained, see Figure 10 .

[0109] Based on the automatic identification of the damaged structure area irradiated by different laser powers, the and the logarithmic value of power Perform a linear fit and get the slope and the X-intercept . The slope will be and the X-intercept Substitute into formula (1) and measure the LDT. The measurement results are shown in Figure 11 .

[0110] Traditional direct measurement methods, such as single-pulse test method and multi-pulse test method, although simple operation and can quickly obtain data, but due to the local defects or non-uniformity of the material, often lead to the existence of greater uncertainty in the measurement results. In addition, the manual measurement of ablation area (especially in non-standard circular symmetry structure) also has a large error; the traditional LDT measurement method often relies on a large number of manual experiments and measurements, especially the extrapolation method needs a large number of experimental data for statistical analysis, and the manual measurement of the ablation area has a high time cost. Compared with the traditional measurement method, the method can quickly and accurately identify the laser damage characteristic area and automatically measure the laser damage characteristic area, so that the measurement process is standardized and the controllability is greatly enhanced, avoiding the uncertainty caused by manual error and local defects, thereby significantly improving the measurement accuracy and reliability, reducing the volatility of the measurement results, improving the consistency and repeatability of the experimental results, high efficiency and good accuracy.

[0111] Referring to Figure 12 The application provides a material laser damage threshold measurement system, comprising:

[0112] An image acquisition module is configured to acquire an optical microscopic image of a femtosecond laser irradiation region.

[0113] An image gray scale processing module is configured to perform gray scale processing on the optical microscopic image of the femtosecond laser irradiation region.

[0114] An image low-frequency information extraction module is configured to extract image low-frequency information from the gray scale processed optical microscopic image and optimize the image low-frequency information to obtain optimized image low-frequency information; wherein the image low-frequency information includes contour information in a central region and related periodic information.

[0115] A diameter calculation module is configured to extract a laser damage characteristic region from the optimized image low-frequency information and calculate a diameter of the laser damage characteristic region; wherein the laser damage characteristic region is a circular laser damage characteristic region or an edge closed region.

[0116] A laser damage threshold calculation module is configured to calculate a laser damage threshold according to the diameter of the laser damage characteristic region.

[0117] The application provides a terminal device comprising a processor, a memory, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the steps in each of the above method embodiments. Alternatively, the processor executes the computer program to implement the functions of each module / unit in each of the above device embodiments.

[0118] The computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present application.

[0119] The terminal device can be a desktop computer, a notebook computer, a palm computer, a cloud server, and the like. The terminal device can include, but is not limited to, a processor, a memory.

[0120] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, etc.

[0121] The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the terminal device by running or executing the computer program and / or modules stored in the memory, and calling data stored in the memory.

[0122] The modules / units integrated in the terminal device, if realized in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. The computer program can realize the steps of the above-mentioned various method embodiments when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier wave signal, telecommunication signal, and software distribution medium, etc. It should be noted that the computer readable medium can include or exclude contents according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electric carrier wave signal and telecommunication signal.

[0123] In summary, the present application provides a material laser damage threshold measurement method, system, device and storage medium, which is an automatic femtosecond laser ablation threshold measurement based on image recognition algorithm, breaking through some limitations in traditional methods and solving the challenges in precision, efficiency, cost and other aspects. By automatically identifying and analyzing the morphological characteristics of the ablation area, combined with the laser processing conditions, the LDT of the material can be accurately and efficiently obtained, significantly improving the accuracy and consistency of the measurement results. Not only can it be applied to LDT measurement under single condition, but also can adapt to material ablation area analysis under different laser power, pulse width, repetition frequency and other laser processing conditions. The scalability and flexibility of this technical solution enable it to meet the femtosecond laser ablation threshold measurement requirements under different laser processing conditions, and have a wider application scenario.

[0124] The above is only the preferred embodiment of the present application, and is not intended to limit the technical solutions of the present application in any way. Those skilled in the art should understand that without departing from the spirit and principles of the present application, the technical solutions can also be modified and replaced in several simple ways, and these modifications and replacements also belong to the protection scope covered by the claims.

Claims

1. A method for measuring the laser damage threshold of a material, characterized in that: include: Acquire optical microscopic images of the femtosecond laser irradiated area; Grayscale processing of the optical microscopic image of the femtosecond laser irradiated area; Extracting and optimizing low-frequency information of the grayscale-processed optical microscopic image to obtain optimized low-frequency information of the image; wherein the low-frequency information of the image includes contour information of the central region and its related periodic information; Extracting the laser damage characteristic region from the optimized low-frequency information of the image and calculating the diameter of the laser damage characteristic region; wherein the laser damage characteristic region is a circular laser damage characteristic region or other closed edge region; According to the diameter of the laser damage characteristic area, obtaining the square of the diameter of the laser damage characteristic area; Perform a linear fit between the square of the diameter of the laser damage characteristic area and the logarithm of the average power of the laser beam to obtain the slope of the linear fit and the intercept of the X-axis; According to the slope of the linear fit and the intercept of the X-axis, the laser damage threshold is calculated: in, is the laser damage threshold, is the slope of the linear fit, is the intercept of the X axis, is the laser repetition frequency.

2. The material laser damage threshold measurement method according to claim 1, characterized in that: The method for obtaining an optical microscopic image of the femtosecond laser irradiated area is: A high-magnification microscope objective lens of 5X or above was used to characterize and observe the structural morphology of the femtosecond laser irradiated area, and a CCD was used to collect optical microscopic images of the femtosecond laser irradiated area.

3. The material laser damage threshold measurement method according to claim 1, characterized in that: The method for extracting low-frequency information of the grayscale-processed optical microscopic image and optimizing it to obtain optimized low-frequency information of the image is as follows: Perform two-dimensional Fourier transform on the grayscale processed optical microscopic image to extract the contour information of the central area and its related periodic information to obtain low-frequency information; A circular mask with a radius of R is used to perform low-pass filtering on the low-frequency information to remove noise information on the contour information; The low-frequency information after low-pass filtering is subjected to inverse Fourier transform, Gaussian blur and binarization in sequence to obtain optimized image low-frequency information.

4. The material laser damage threshold measurement method according to claim 1, characterized in that: The method for extracting the laser damage characteristic area from the optimized image low-frequency information and calculating the diameter of the laser damage characteristic area is: Hough transform is used to extract the laser damage feature area from the optimized image low-frequency information; The pixel radius of the laser damage characteristic area is counted, and the diameter of the laser damage characteristic area is calculated.

5. The material laser damage threshold measurement method according to claim 1, characterized in that: The method for extracting the laser damage characteristic area from the optimized image low-frequency information and calculating the diameter of the laser damage characteristic area is: The edge detection algorithm is used to extract the laser damage feature area from the optimized image low-frequency information; Using morphological closing operation, the discontinuous edge points of the laser damage characteristic area are filled and the area of ​​the laser damage characteristic area is calculated; The diameter of the laser damage characteristic region is calculated based on the area of ​​the laser damage characteristic region.

6. A material laser damage threshold measurement system for implementing the material laser damage threshold measurement method according to any one of claims 1 to 5, characterized in that: include: Image acquisition module: used to obtain optical microscopic images of the femtosecond laser irradiated area; Image grayscale processing module: used to perform grayscale processing on the optical microscopic image of the femtosecond laser irradiated area; Image low-frequency information extraction module: used to extract and optimize the image low-frequency information of the optical microscopic image after grayscale processing to obtain optimized image low-frequency information; wherein the image low-frequency information includes the contour information located in the central area and its related periodic information; Diameter calculation module: used to extract the laser damage characteristic area from the optimized image low-frequency information and calculate the diameter of the laser damage characteristic area; wherein the laser damage characteristic area is a circular laser damage characteristic area or other edge-closed area; Laser damage threshold calculation module: used to calculate the laser damage threshold based on the diameter of the laser damage characteristic area.

7. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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