A method for determining optimal shooting parameters of target board surface laser speckle based on MFFIseq

Abstract

The present application relates to the technical field of laser speckle monitoring, and specifically discloses a method for determining optimal shooting parameters of laser speckle on a target plate surface based on MFFIseq, comprising the following steps: simulating the service environment of a fusion reactor blanket target plate based on a high heat flow experiment platform, shooting multiple groups of laser speckle image sequences under different acquisition parameters, calculating four sequence evaluation indexes of each group of sequences, i.e., gray unevenness, gray mean square deviation, speckle particle area standard deviation and speckle pixel proportion, fusing to obtain a multi-factor fusion index MFFIseq, and determining the acquisition parameters corresponding to the sequence with the minimum MFFIseq value as the optimal parameters. The method for determining optimal shooting parameters of laser speckle on a target plate surface based on MFFIseq is adopted, multi-dimensional sequence index fusion is used to realize objective quantitative evaluation of the quality of laser speckle images, the optimal parameters suitable for dynamic monitoring of the target plate can be accurately screened, the quality of laser speckle images is improved, and high-precision monitoring of the deformation of the fusion reactor blanket target plate surface and subsequent heat flow inversion are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of laser speckle monitoring, in particular to a method for determining optimal shooting parameters of laser speckle on a target plate surface based on MFFIseq. BACKGROUND

[0002] With the continuous advancement of controllable nuclear fusion technology, the divertor, as a key component for handling impurities and heat load in the tokamak device, its working state directly affects the operation efficiency and plasma confinement performance of the whole device. The target plate, as the end structure of the divertor, often bears high heat flux density and particle bombardment, and is prone to material damage, surface topography change and other phenomena. Therefore, it is of great significance to diagnose the surface state of the target plate in real time with high resolution and non-contact.

[0003] Laser speckle imaging has the advantages of high sensitivity, strong anti-electromagnetic interference ability, and remote non-contact measurement, and is an effective means for diagnosing the small changes in the surface topography of materials, especially suitable for online monitoring of the divertor target plate in the nuclear fusion environment. However, due to the complex material properties of the target plate, the different surface roughness, and the existence of strong background noise and radiation interference in the fusion reactor, the quality of the laser speckle image is easily affected by various parameters, such as laser power, illumination angle, camera aperture, camera exposure time, etc. Therefore, a scientific and systematic method is needed to determine the optimal image acquisition parameters to ensure that high-contrast, high-stability, and high-repeatability speckle images are obtained, providing a reliable data basis for subsequent image processing and physical parameter inversion. SUMMARY

[0004] The purpose of the present application is to provide a method for determining the optimal shooting parameters of laser speckle on the target plate surface based on MFFIseq, by constructing multi-dimensional sequence evaluation indicators and fusing them into a single quantitative indicator, realizing the objective evaluation of the quality of the laser speckle image sequence, and then accurately selecting the optimal acquisition parameters, providing a reliable data basis for high-precision dynamic monitoring of the target plate surface of the fusion reactor divertor.

[0005] To achieve the above purpose, the present application provides a method for determining the optimal shooting parameters of laser speckle on the target plate surface based on MFFIseq, comprising the following steps:

[0006] S1, shooting the divertor target plate surface under different acquisition parameters to obtain multiple groups of laser speckle image sequences;

[0007] S2, for each group of laser speckle image sequences, calculating four sequence evaluation indicators, namely sequence gray non-uniformity, sequence gray mean square error, sequence speckle particle area standard deviation, and sequence speckle pixel ratio;

[0008] S3, calculating the multi-factor fusion indicator of each sequence according to the four sequence evaluation indicators obtained in S2 ;

[0009] S4. Compare the multi-factor fusion index corresponding to each group of laser speckle image sequences. Value, will The acquisition parameters corresponding to the sequence with the smallest value are determined as the optimal acquisition parameters for laser speckle on the target plate of the fusion reactor divertor.

[0010] Preferably, S1 specifically involves: simulating the service environment of a fusion reactor divertor target panel based on a high heat flux experimental platform. The high heat flux experimental platform includes an electron gun and a laser speckle effect testing system. The electron gun is used to apply a thermal load to the divertor target panel, and the laser speckle effect testing system is used to capture images of the target panel under different acquisition parameters to obtain multiple sets of laser speckle image sequences.

[0011] Preferably, in S1, the laser speckle effect testing system includes a camera and a laser positioned on both sides of the electron gun, and the acquired parameters include the camera aperture, the number of hot-loading points, the hot-loading frequency, and the hot-loading rate; wherein, the number of hot-loading points, the hot-loading frequency, and the hot-loading rate are controlled by the electron gun, specifically:

[0012] The number of heat loading points is the number of heat load points applied to the target plate surface by the electron gun in a single loading cycle;

[0013] The heat loading frequency is the number of loading cycles per second that the electron gun applies to the target plate surface;

[0014] The hot loading rate is used to control how quickly the loading current rises from zero to the target current.

[0015] Preferably, in S2, for a single image in each group of laser speckle images, the grayscale non-uniformity... IGD The calculation formula is as follows:

[0016] ;

[0017] in, Indicates the grayscale value of an image pixel. The number of pixels, W , H These represent the length and height of the computational region in the laser speckle image, respectively. L Represents the pixel level of an image;

[0018] Then, for each group of laser speckle image sequences, the sequence gray-level non-uniformity is calculated. The calculation formula is as follows:

[0019] ;

[0020] in, For this set of image sequences IGD average value, is the standard deviation of the group of sequence pictures IGD, is the maximum value of the absolute difference between two adjacent pictures in the group of sequence pictures IGD .

[0021] In S2, preferably, for each picture in the group of laser speckle images, the gray level variance MSDG is calculated as follows:

[0022] .

[0023] wherein, is the gray level of the image pixel, is the probability that the gray level of the image pixel is , and the mean gray level .

[0024] Then, for each group of sequence of laser speckle images, the sequence gray level variance is calculated as follows:

[0025] .

[0026] wherein, is the mean of the group of sequence pictures MSDG, is the standard deviation of the group of sequence pictures MSDG , is the maximum value of the absolute difference between two adjacent pictures in the group of sequence pictures MSDG .

[0027] In S2, preferably, for each picture in the group of laser speckle images, the OTSU method is used to binarize the picture, and then the speckle particle area standard deviation SDSPS is calculated according to the following formula:

[0028] .

[0029] wherein, T is the total number of speckle particles, is the area of the th block of speckle particles, is the mean area of the speckle particles;

[0030] Then, for each group of sequence of laser speckle images, the sequence speckle particle area standard deviation is calculated as follows:

[0031] .

[0032] wherein, is the mean of the group of sequence pictures SDSPS ​the average value of the group of sequence pictures, the standard deviation of the group of sequence pictures, SDSPS the maximum value of the absolute difference between two adjacent pictures in the group of sequence pictures. the maximum value of the absolute difference between two adjacent pictures in the group of sequence pictures. SDSPS the maximum value of the absolute difference between two adjacent pictures in the group of sequence pictures.

[0033] Preferably, in S2, for each picture in a group of laser speckle images, the OTSU method is used to binarize the picture, and then the speckle pixel ratio is calculated according to the following formula SPP :

[0034] ;

[0035] wherein, the number of pixels with a binarized pixel value of 1;

[0036] then the sequence speckle pixel is calculated for each group of laser speckle image sequences , and the calculation formula is as follows:

[0037] ;

[0038] wherein, the average value of the group of sequence pictures, SDSPS the standard deviation of the group of sequence pictures, the standard deviation of the group of sequence pictures, SPP the maximum value of the absolute difference between two adjacent pictures in the group of sequence pictures. the maximum value of the absolute difference between two adjacent pictures in the group of sequence pictures. SPP the maximum value of the absolute difference between two adjacent pictures in the group of sequence pictures.

[0039] Preferably, in S3, the multi-factor fusion index of each group of laser speckle image sequences is calculated by the following formula :

[0040] ;

[0041] wherein, the linear amplification coefficient.

[0042] Therefore, the present application adopts the above-mentioned method for determining the optimal shooting parameters of the target plate surface laser speckle based on MFFIseq, and has the following beneficial effects:

[0043] (1) The present application avoids the limitations of traditional experience judgment or single indicators by fusing four sequence evaluation indicators, and realizes objective quantitative evaluation of the quality of the speckle image sequence.

[0044] (2) The present application is aimed at the dynamic characteristics of the target plate during the heat loading process, and through the analysis of sequence continuity and stability, it ensures that the selected parameters are applicable to the dynamic monitoring scene.

[0045] (3) The present application can accurately determine the optimal parameter combination through multiple experimental verifications, significantly improve the contrast, stability and information integrity of the speckle image, and provide high-quality data for subsequent deformation calculation.

[0046] The technical solutions of the present application are further described below through the drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 is the overall flowchart of a method embodiment of the present application for determining optimal shooting parameters of target plate surface laser speckle based on MFFIseq;

[0048] Figure 2 is a high heat flow experimental platform structure diagram of a method embodiment of the present application for determining optimal shooting parameters of target plate surface laser speckle based on MFFIseq;

[0049] Figure 3 is a heat loading point number schematic diagram of a method embodiment of the present application for determining optimal shooting parameters of target plate surface laser speckle based on MFFIseq;

[0050] Figure 4 is a strain curve diagram of a deflector target plate surface under 10mw / m 2 heat flow loading.

[0051] REFERENCE NUMERALS

[0052] 1, camera; 2, observation window; 3, electron gun; 4, laser; 5, deflector target plate surface. DETAILED DESCRIPTION

[0053] The technical solutions of the present application are further described below through the drawings and examples.

[0054] Unless otherwise defined, the technical terms or scientific terms used in the present application shall be understood as the usual meanings understood by persons having ordinary skills in the art to which the present application belongs. The terms "first", "second" and the like used in the present application do not represent any order, number or importance, but are only used to distinguish different components. The terms "include" or "contain" and the like mean that the elements or objects before the terms cover the elements or objects listed after the terms and their equivalents, and do not exclude other elements or objects. The terms "connect" or "connected" and the like are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "up", "down", "left", "right" and the like are only used to represent relative positional relationships, and when the absolute positions of the described objects change, the relative positional relationships may also change accordingly.

[0055] As shown in Figure 1 A method for determining optimal shooting parameters of target plate laser speckle based on sequence multi-factor fusion index MFFIseq(Sequence multi-factor fusion index) includes the following steps:

[0056] S1, the present application is based on high heat flow experimental platform simulates the service environment of the target plate of the divertor of the fusion reactor, as shown in Figure 2 The high heat flow experimental platform includes an electron gun 3 and a laser speckle effect test system. The electron gun 3 is used to apply thermal load to the divertor target plate 5, and the laser speckle effect test system includes a camera 1 and a laser 4 arranged on both sides of the electron gun 3. The laser 4 precisely irradiates the divertor target plate 5 through the observation window 2 on one side, and the camera 1 captures the interference image formed by the laser speckle through the observation window 2 on the other side.

[0057] The divertor target plate 5 under different acquisition parameters is shot by the laser speckle effect test system, and a plurality of groups of laser speckle image sequences are obtained. The acquisition parameters include the aperture of the camera 1, the number of thermal loading points, the thermal loading frequency and the thermal loading rate; wherein the number of thermal loading points, the thermal loading frequency and the thermal loading rate are controlled by the electron gun 3, specifically:

[0058] As shown in Figure 3 The number of thermal loading points is the number of thermal load points loaded by the electron gun 3 on the divertor target plate 5 in a single loading cycle. By increasing the number of loading points of the electron gun 3, the thermal load applied to the divertor target plate 5 can be more uniform. Figure 3 ① in the figure is the divertor target plate 5, and ② is a single loading point of the electron gun 3.

[0059] The thermal loading frequency is the number of loading cycles per second of the electron gun on the target plate. Since the electron gun can only load a single point at a time, the thermal load on the entire loading surface is realized by shifting the loading surface x 、 y direction, that is, the thermal loading frequency refers to the surface frequency of the loading surface, and 5Hz means that the loading surface is scanned and loaded 5 times per second.

[0060] The loading voltage of the electron gun system is 80kv, which is a fixed value. The present application controls the thermal load value of the loading of the divertor target plate by adjusting the size of the loading current. However, the loading current does not reach the set value instantaneously, and the thermal loading rate is used to control the speed of the loading current rising from zero to the target current; for example, if the thermal loading rate is 1ms, it means that the loading current rises by 1mA in 0.01s, 2ms means that the loading current rises by 1mA in 0.02s, and 5ms means that the loading current rises by 1mA in 0.05s.

[0061] S2, for each set of laser speckle image sequence, respectively, the sequence of gray inhomogeneity, sequence gray mean square error, sequence speckle particle area standard deviation and sequence speckle pixel ratio of four sequence evaluation index.

[0062] For each picture in each set of laser speckle image sequence, the calculation formula of gray inhomogeneity IGD (Inhomogeneity of Gray Distribution) is as follows:

[0063] ;

[0064] wherein, represents the number of pixels with gray value , W , H respectively represents the length and height of the laser speckle image calculation area.

[0065] Define the image , wherein respectively represents the row and column of the image, and the pixel level of the image is set to L , then the of eight bit gray scale image.

[0066] The inhomogeneity of gray distribution reflects the breadth of the distribution of image gray value. The more uniform the image gray distribution is, the wider the gray scale covered is, and the higher the quality of speckle pattern is. On the contrary, if the image gray distribution is concentrated on some gray scale, the quality of speckle pattern is low. IGD The greater the inhomogeneity of gray distribution is, the more concentrated the gray value is, and the single the image gray level is; IGD The smaller the inhomogeneity of gray distribution is, the more uniform the distribution of gray value is, and the more rich the image level is, and the more texture information is.

[0067] For each picture in each set of laser speckle image sequence, the calculation formula of gray mean square error MSDG is as follows:

[0068] ;

[0069] wherein, is the gray value of image pixel, represents the probability of image pixel gray value , and the gray mean value .

[0070] The gray variance reflects the dispersion degree of image pixel gray value relative to the mean value, that is, the contrast of the image, MSDG The greater the gray variance is: the wider the gray distribution is, the stronger the contrast of the image is, and the more rich the texture is; MSDG The smaller the gray variance is: the gray distribution is concentrated, the image is dark or flat, and the feature is not obvious.

[0071] For each picture in the laser speckle image sequence, the OTSU method is used for binaryzation of the image, and then the speckle particle area standard deviation is calculated according to the following formula SDSPS :

[0072] ;

[0073] Wherein, T is the total number of speckle particles, is the area of the speckle particle in the first block, is the area of the speckle particle in the last block, is the average area of the speckle particle. SDSPS The smaller: the speckle particle size tends to be consistent, and the image contrast is poor. SDSPS The larger: the speckle size difference in the image is obvious, and the image quality is good.

[0074] For each picture in the laser speckle image sequence, the OTSU method is used for binaryzation of the image, and then the speckle pixel ratio is calculated according to the following formula SPP :

[0075] ;

[0076] Wherein, is the number of pixels with a pixel value of 1 after binaryzation.

[0077] After binaryzation, in addition to the size difference between the speckle particles affecting the image quality, the proportion of the speckle particles also affects the image quality, but the speckle pixel ratio SPP is not the larger the better, when SPP exceeds 0.5, multiple speckle particles will be fused together, reducing the number of speckles and the difference between the speckle particles, and theoretically the speckle pixel ratio SPP is closer to 0.5 the better, so SPP is converted into another form , at this time is the smaller the better.

[0078] The above four evaluation criteria are limited to the evaluation of single laser speckle quality, and since the target plate laser speckle changes dramatically during the heat flow loading process, the quality of the single laser speckle image cannot determine the quality of the entire image sequence, therefore, the above four formulas are improved and optimized:

[0079] The present application further calculates the sequence gray scale non-uniformity for each laser speckle image sequence, and the calculation formula is as follows:

[0080] ;

[0081] wherein, is the average value of the group of sequence pictures, IGD is the standard deviation of the group of sequence pictures, IGD is the maximum value of the absolute value of the difference between two adjacent pictures in the group of sequence pictures. IGD

[0082] For a single picture, IGD the smaller the better, and the same for the fluctuation of the collected sequence picture, IGD the smaller the better, that is, the smaller the better, if the change between two adjacent pictures in the sequence picture group is severe, that is, the value is large, which will cause the de-correlation of subsequent sequence picture calculation and analysis, therefore, the goal of the present application is the smaller the better.

[0083] For each group of laser speckle image sequence, further calculate the sequence gray mean square deviation , the calculation formula is as follows:

[0084] ;

[0085] wherein, is the average value of the group of sequence pictures, the larger the better; MSDG is the standard deviation of the group of sequence pictures, the smaller the better; is the maximum value of the absolute value of the difference between two adjacent pictures in the group of sequence pictures, the smaller the better, therefore, the goal of the present application is MSDG the larger the better. MSDG For each group of laser speckle image sequence, further calculate the sequence speckle particle area standard deviation , the calculation formula is as follows:

[0086]

[0087] ;

[0088] wherein, is the average value of the group of sequence pictures, the larger the better; SDSPS is the standard deviation of the group of sequence pictures, the smaller the better; is the maximum value of the absolute value of the difference between two adjacent pictures in the group of sequence pictures, the smaller the better, therefore, the goal of the present application is SDSPS the larger the better. SDSPS

[0089] ​​​​​​​​​Further calculate the sequence speckle pixel proportion for each group of laser speckle image sequences , the calculation formula is as follows:

[0090] ;

[0091] Wherein, is the average value of the group of sequence pictures SDSPS , the larger the value is, the better; is the standard deviation of the group of sequence pictures SPP , the smaller the value is, the better; is the maximum value of the absolute value of the difference between adjacent two pictures in the group of sequence pictures SPP , the smaller the value is, the better, therefore the purpose of the present application is the larger the value is, the better.

[0092] S3, four sequence evaluation indexes obtained according to S2, the multi-factor fusion index of each group of sequences is calculated by the following formula :

[0093] ;

[0094] Wherein, is a linear amplification coefficient, the smaller the value is, the higher the quality of the group of sequence pictures is.

[0095] S4, compare the multi-factor fusion index values of each group of laser speckle image sequences , determine the acquisition parameters corresponding to the group of sequences with the minimum value as the optimal acquisition parameters of the laser speckle of the target plate surface of the fusion reactor divertor.

[0096] Based on the high heat flow experimental platform and the sequence multi-factor fusion index , the camera aperture, the number of heat loading points, the heat loading frequency, the heat loading rate and other four factors are tested for the imaging quality of the laser speckle of the target plate surface of the divertor.

[0097] Example one

[0098] Camera aperture parameter determination

[0099] The experimental loading working condition is set as: heat flow 10mw / m 2 , camera acquisition frame rate 30fps, heat loading point number 600 points, heat loading frequency 5Hz, heat loading rate 5ms, and the tested aperture parameters are F5.6, F8, F11, F16 and F22 in turn, and the sequence multi-factor fusion index values obtained are shown in Tables 1-5:

[0100] Table 1 sequence IGD calculation value under different apertures

[0101] ;

[0102] Table 2 Sequence MSDG calculation values under different apertures

[0103] ;

[0104] Table 3 Sequence SDSPS calculation values under different apertures

[0105] ;

[0106] Table 4 Sequence SPP calculation values under different apertures

[0107] ;

[0108] Table 5 Sequence MFFIseq calculation values under different apertures

[0109] ;

[0110] From the table, when the camera aperture is F11, the corresponding MFFIseq value is 7.56, which is the smallest among all the test aperture parameters. In combination with the sequence evaluation indicators: the sequence gray uniformity score is 121.0305, which is significantly lower than F5.6 128.5529, F22 137.1063 and other parameters, indicating that the gray distribution is more uniform and the sequence stability is better; the sequence gray mean square error score is 25.83387, which is at a higher level, indicating that the image contrast is moderate and the fluctuation is small; the sequence speckle particle area standard deviation score is 19.51107, which is lower than F22 23.72151, but the standard deviation 1.550883 and the maximum absolute value of adjacent difference 3.804007 of F22 are significantly higher, reflecting that the speckle particle size stability is poorer, while the speckle particle morphology diversity and sequence consistency of F11 are better; the sequence speckle pixel ratio score is 0.185288, close to the ideal range, and the fluctuation is small. In summary, the image sequence taken under F11 aperture performs best in terms of gray distribution uniformity, contrast stability, speckle morphology rationality and sequence dynamic consistency, etc. Therefore, F11 is determined as the optimal camera aperture parameter.

[0111] Example Two

[0112] Thermal loading point number parameter determination

[0113] The experimental loading condition is set as: heat flow 10 mw / m 2, the camera acquisition frame rate 30 fps, camera aperture F11, thermal loading frequency 5 Hz, thermal loading rate 5 ms; the number of test thermal loading points are: 200, 300, 400, 500, 600; the resulting sequence of multi-factor fusion index values are shown in Tables 6-10:

[0114] Table 6. Sequence IGD calculation values under different thermal loading points

[0115] ;

[0116] Table 7. Sequence MSDG calculation values under different thermal loading points

[0117] ;

[0118] Table 8. Sequence SDSPS calculation values under different thermal loading points

[0119] ;

[0120] Table 9. Sequence SPP calculation values under different thermal loading points

[0121] ;

[0122] Table 10. Sequence MFFIseq calculation values under different thermal loading points

[0123] ;

[0124] From the table, when the thermal loading point number is 600 points, the corresponding MFFIseq value is 7.56, which is the smallest among all test points, indicating that the sequence image comprehensive quality is optimal under this parameter. From each sub-index: the sequence gray uniformity score is 121.0305, which is significantly lower than 123.9929 of 200 points and 136.1037 of 500 points, especially in the mean 118.8629 and the maximum absolute value of adjacent difference 1.406124, which performs better, indicating that the gray distribution is more uniform and the sequence fluctuation is smaller; the sequence gray mean square error score is 25.83387, which is higher than all other points, reflecting that the image contrast is stronger and the stability is better; the sequence speckle grain area standard deviation score is 19.51107, which is close to 19.51392 of 500 points, but the standard deviation 0.435592 and the maximum absolute value of adjacent difference 1.602899 of 600 points are smaller, indicating that the consistency of speckle grain size is better; the sequence speckle pixel ratio score is 0.185288, which is much higher than other points, indicating that the speckle ratio is closer to the ideal range. In summary, the thermal loading point number of 600 points can make the target plate face more uniform, and the collected laser speckle image sequence performs best in gray distribution, contrast, speckle morphology and dynamic stability, so 600 points is determined as the optimal thermal loading point number parameter.

[0125] Example Three

[0126] Thermal loading frequency parameter determination

[0127] The experimental loading condition is set as: heat flow 10 mw / m 2 , camera acquisition frame rate 30 fps, camera aperture F11, thermal loading point number 600, thermal loading rate 5 ms; the tested thermal loading frequency is 2 Hz, 3 Hz, 4 Hz and 5 Hz in turn, and the obtained sequence multi-factor fusion index numerical values are shown in Tables 11-15:

[0128] Table 11. Sequence IGD calculation values under different thermal loading point numbers

[0129] ;

[0130] Table 12. Sequence MSDG calculation values under different thermal loading point numbers

[0131] ;

[0132] Table 13. Sequence SPP calculation values under different thermal loading point numbers

[0133] ;

[0134] Table 14. Sequence SDSPS calculation values under different thermal loading point numbers

[0135] ;

[0136] Table 15. Sequence MFFIseq calculation values under different thermal loading point numbers

[0137] ;

[0138] From the table, when the thermal loading frequency is 5Hz, the corresponding MFFIseq value is 7.56, which is the smallest among all test frequencies, indicating that the sequence image collected at this frequency has the optimal comprehensive quality. From the sequence evaluation indicators: the sequence gray scale non-uniformity score is 121.0305, which is lower than 123.8983, 123.8247 and 121.9642 of 2Hz, 3Hz and 4Hz respectively, especially the mean value 118.8629 is the lowest, indicating that the gray scale distribution is the most uniform, and the maximum value of the absolute value of the adjacent difference is slightly higher than that of 2Hz and 3Hz, but the overall sequence stability is still better; the sequence gray scale mean square error score is 25.83387, which is higher than all other frequencies, meaning that the image contrast is the strongest, and the standard deviation and the maximum value of the absolute value of the adjacent difference are in a reasonable range, and the sequence contrast stability is good; the sequence speckle particle area standard deviation score is 19.51107, which is much higher than 17.32925 of 2Hz, 17.76923 of 3Hz and 17.60307 of 4Hz, and its standard deviation 0.435592 and the maximum value of the absolute value of the adjacent difference 1.602899 are the smallest among all frequencies, indicating that the speckle particle size difference is obvious and the sequence consistency is the best; the sequence speckle pixel ratio score is 0.185288, which is the highest among all frequencies, and the speckle ratio is closer to the ideal value with smaller fluctuations. In summary, the thermal loading frequency of 5Hz has the highest matching degree with the camera acquisition frame rate and the dynamic change characteristics of the target plate, and the laser speckle image sequence collected has the best performance in terms of gray scale uniformity, contrast, speckle morphology and dynamic stability, so 5Hz is determined as the optimal thermal loading frequency parameter.

[0139] Example Four

[0140] Thermal loading rate parameter determination

[0141] The experimental loading condition is set as: heat flow 10mw / m 2 , camera acquisition frame rate 30fps, camera aperture F11, thermal loading point number 600, thermal loading frequency 5Hz; the tested thermal loading rates are 1ms, 2ms, 3ms, 4ms and 5ms in turn; the sequence multi-factor fusion index values obtained are shown in Tables 16-20:

[0142] Table 16 Sequence IGD calculation values under different thermal loading rates

[0143]

[0144] Table 17 Sequence MSDG calculation values under different thermal loading rates

[0145]

[0146] Table 18 Sequence SDSPS calculation values under different thermal loading rates ​​

[0147] ;

[0148] Table 19 Sequence SPP calculated values under different heat loading rates

[0149] ;

[0150] Table 20 Sequence MFFIseq calculated values under different heat loading rates

[0151] ;

[0152] From the table, when the heat loading rate is 5ms, the corresponding MFFIseq value is 7.56, which is the smallest among all test rates, indicating that the sequence image collected at this rate has the optimal comprehensive quality. From each sequence evaluation index: the sequence gray scale non-uniformity score is 121.0305, which is lower than 127.7659 of 1ms, 127.5588 of 2ms, 121.6871 of 3ms and 121.6185 of 4ms, the standard deviation 0.436429 and the maximum absolute value of adjacent difference 1.406124 are smaller among all rates, indicating that the gray scale distribution is uniform and the sequence stability is better; the sequence gray scale mean square error score is 25.83387, which is slightly lower than 25.87963 of 3ms and 25.85103 of 4ms, but the standard deviation 0.205803 and the maximum absolute value of adjacent difference 0.649009 are at a low level, and the sequence contrast stability is good; the sequence speckle particle area standard deviation score is 19.51107, which is close to 19.58496 of 4ms, and the standard deviation 0.435592 and the maximum absolute value of adjacent difference 1.602899 are reasonable, the speckle particle size difference and sequence consistency are better; the sequence speckle pixel ratio score is 0.185288, which is the highest among all rates, and the speckle ratio is closer to the ideal value with smaller fluctuations. In summary, the heat loading rate of 5ms can make the target plate surface heat loading process more stable, and has the highest compatibility with other parameters, and the collected laser speckle image sequence performs best in terms of gray scale uniformity, contrast stability, speckle morphology and dynamic consistency, so 5ms is determined as the optimal heat loading rate parameter.

[0153] According to the sequence multi-factor fusion index, the optimal shooting parameters of the deflector target plate laser speckle are obtained as follows: camera aperture F11, heat loading point number 600 points, heat loading frequency 5Hz, heat loading rate 5ms. Through the above acquisition parameters, the deflector target plate surface laser speckle image sequence under 10mw / m 2 The strain curve under heat flow loading can effectively reflect the dynamic deformation characteristics of the target plate under 10mw / m 2 heat flow, as shown in Figure 4 .

[0154] Therefore, the application adopts the above method for determining optimal shooting parameters of target plate surface laser speckle based on MFFIseq, realizes multi-dimensional quantitative evaluation of laser speckle image sequence quality of the fusion filter target plate of the fusion reactor by constructing the sequence multi-factor fusion index MFFIseq, significantly improves the gray uniformity, contrast stability, speckle shape rationality and dynamic consistency of the speckle image, provides high-quality data support for target plate surface dynamic monitoring and subsequent deformation calculation, and meanwhile, the method has strong objectivity and universality, and can be popularized to parameter optimization scenes of material surface laser speckle monitoring in other extreme environments.

[0155] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application, but not to limit it, although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that: it can still modify or equivalently replace the technical solutions of the present application, and these modifications or equivalent replacements also cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present application.

Claims

1. A method for determining optimal shooting parameters of target board laser speckle based on MFFIseq, characterized in that, The method comprises the following steps: S1, taking pictures of the target plate surface of the filter under different acquisition parameters to obtain a plurality of groups of laser speckle image sequences; S2, for each group of laser speckle image sequences, four sequence evaluation indexes of sequence gray inhomogeneity, sequence gray mean square error, sequence speckle particle area standard deviation and sequence speckle pixel ratio are calculated respectively; S3、According to the four sequence evaluation indexes obtained in S2, calculate the multi-factor fusion index of each group of sequences ; S4. Compare the multi-factor fusion index corresponding to each group of laser speckle image sequences. Value, will The acquisition parameters corresponding to the sequence with the smallest value are determined as the optimal acquisition parameters for laser speckle on the target plate of the fusion reactor divertor. For each sequence of laser speckle images, the sequence gray level non-uniformity is calculated The formula is as follows: ； in, For this set of image sequences average value, For the grayscale unevenness of a single image, For this set of image sequences standard deviation For two adjacent images in this sequence of images The maximum value of the absolute value of the difference; For each sequence of laser speckle images, the sequence gray level mean square deviation is calculated The formula is as follows: ； wherein, is the average value of the group of sequence pictures , is the mean square error of the gray scale of the single picture, is the standard deviation of the group of sequence pictures , is the maximum value of the absolute value of the difference between two adjacent pictures in the group of sequence pictures . For each sequence of laser speckle images, the standard deviation of the sequence speckle grain area is calculated with the following formula: ； wherein is the average value of the group of sequence pictures , is the standard deviation of the group of sequence pictures , is the maximum value of the absolute difference between two consecutive pictures of the group of sequence pictures , . For each sequence of laser speckle images, a sequence of speckle pixels is calculated with the following formula: ； wherein, is the average value of the group of sequence pictures , is the proportion of speckle pixels of a single picture, is the standard deviation of the group of sequence pictures , is the maximum value of the absolute difference between two adjacent pictures of the group of sequence pictures . In S3, a multi-factor fusion index of each group of laser speckle image sequences is calculated by the following formula : ； wherein is a linear amplification factor.

2. The method of claim 1, wherein, S1 is specifically: based on a high heat flow experiment platform to simulate the service environment of the target plate of the fusion reactor filter, the high heat flow experiment platform comprises an electron gun and a laser speckle effect test system, the electron gun is used to apply thermal load to the target plate surface of the filter, and the target plate surface under different acquisition parameters is photographed by the laser speckle effect test system to obtain a plurality of groups of laser speckle image sequences.

3. The method of claim 2, wherein, In S1, the laser speckle effect test system comprises cameras and lasers arranged on both sides of the electron gun, and the acquisition parameters comprise camera aperture, heat loading point number, heat loading frequency and heat loading rate; wherein the heat loading point number, the heat loading frequency and the heat loading rate are controlled by the electron gun, and specifically: The heat loading point number is the number of heat load points loaded on the target plate surface by the electron gun in a single loading cycle; The heat loading frequency is the number of loading cycles loaded on the target plate surface by the electron gun per second; The heat loading rate is used to control the speed of the loading current rising from zero to the target current.

4. The method of claim 3, wherein, In S2, for each single picture in the set of laser speckle images, the calculation formula of the gray scale non-uniformity is as follows: In S2, for each single picture in the set of laser speckle images, the calculation formula of the gray scale non-uniformity is as follows: ； wherein, represents the number of pixels with image pixel gray value respectively represent the length and height of the laser speckle image calculation region, represents the pixel level of the image.​ 5. The method of claim 4, wherein, In S2, for each single picture in the set of laser speckle images, the gray level mean square deviation is calculated according to the following formula: ； wherein, is the image pixel gray value, represents the probability that the image pixel gray value is is the gray mean value, .​ 6. The method of claim 5, wherein, In S2, for each picture in the set of laser speckle images, the OTSU method is used to binarize the picture, and then the standard deviation of the speckle particle area is calculated according to the following formula : ； wherein, is the total number of speckle particles, is the area of the first block of speckle particles, is the average area of the speckle particles.

7. The method of claim 6, wherein, In S2, for each single picture in the set of laser speckle images, the OTSU method is used to binarize the picture, and then the proportion of speckle pixels is calculated according to the following formula : ； wherein, is the number of pixels with a pixel value of 1 after binarization.

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