A fluorescent microfilament dynamic flow spectrum separation and adhesion flow quantitative interpretation method

Abstract

The application discloses a fluorescent microfilament dynamic flow spectrum separation and attached flow quantitative interpretation method, and aims to solve the problem that in the fluorescent microfilament dynamic flow spectrum display method, the subjective experience and qualitative observation of an operator are mainly relied on at present, leading to low interpretation accuracy and poor result repeatability. The method comprises the following steps: S01, pre-processing of the fluorescent microfilament image collected in an experiment; S02, calculation of position coordinates; S03, calculation of a deflection angle of the fluorescent microfilament, and generation of an angle value set; S04, judgment of a flow state existing in the fluorescent microfilament number image; S05, division of a separation and attached flow boundary in the fluorescent microfilament number image; and S06, recording and saving of the judgment of the flow state and the boundary division process. The application utilizes the physical and mathematical meanings of a double-peak coefficient to propose quantitative criteria of the attached flow and the separation flow, realizes dynamic tracking of an evolution process by distinguishing transient flow structures, and is helpful to solve the problem that a non-steady flow field structure is difficult to identify.

Description

Technical Field

[0001] This application relates to the field of aerodynamic flow visualization and identification, specifically a method for dynamic flow spectrum separation and quantitative interpretation of attached flow from fluorescent microfilaments. Background Technology

[0002] Fluorescent microfilament dynamic flow spectrum display technology refers to the visualization of flow structures by arranging an array of fluorescent microfilaments on the surface of an aircraft model and using high-speed photography to record the motion of the fluorescent microfilaments under the influence of airflow. This method is an important tool in the field of aircraft surface flow visualization and is widely used due to its advantages such as ease of operation, fast response, and ability to display transient flows in real time.

[0003] Accurate interpretation of the flow state revealed by the dynamic flow spectrum of fluorescent microfilaments, especially the precise identification of the boundaries between flow separation and adhesion regions, is crucial for determining the safe flight envelope of an aircraft and verifying the accuracy of computational fluid dynamics (CFD) numerical simulation results. It is a key link in improving the reliability of aerodynamic characteristic analysis.

[0004] However, the core problem currently facing this technology is that the interpretation of separated and attached flows in fluorescent microfilament flow spectra mainly relies on the operator's subjective experience and qualitative observation. This subjective judgment-based method has significant limitations, including low interpretation accuracy and poor repeatability. Specifically, it easily misses key information characterizing flow state transitions (such as subtle separation bubbles and reattachment points), leading to unclear flow field details; and it is difficult to objectively and quantitatively define the boundaries between the separation and attachment zones. These problems directly weaken the reliability and engineering practical value of the dynamic flow spectrum visualization results of fluorescent microfilaments, which not only hinders aerodynamic shape optimization design based on flow field details but also affects the accuracy of determining the safe flight envelope.

[0005] Therefore, a new method is urgently needed to solve the above problems. Summary of the Invention

[0006] The purpose of this invention is to provide a method for separating and quantitatively interpreting the dynamic flow spectrum of fluorescent microfilaments, which addresses the current problem that the dynamic flow spectrum display method mainly relies on the operator's subjective experience and qualitative observation, resulting in low interpretation accuracy and poor repeatability.

[0007] To achieve the above objectives, this application adopts the following technical solution.

[0008] A method for dynamic flow spectrum separation and quantitative interpretation of attached flow of fluorescent microfilaments includes the following steps:

[0009] S01. Preprocess the fluorescent microfilament images acquired in the experiment and save the preprocessed fluorescent microfilament images.

[0010] S02. Divide and number each fluorescent microfilament in the preprocessed image of fluorescent microfilaments, and calculate its position coordinates to obtain a numbered image of fluorescent microfilaments.

[0011] S03. Based on the position coordinates and number of each fluorescent microfilament in the numbered image, calculate the deflection angle of the fluorescent microfilament and generate a set of angle values; the set of angle values ​​includes the number, position coordinates and specific deflection angle value of each fluorescent microfilament.

[0012] S04. Based on the set of angle values, determine the flow state present in the fluorescent microfilament numbering image; the flow state includes attached flow, separated flow, and mixed flow, and the mixed flow refers to the simultaneous presence of attached flow and separated flow.

[0013] S05. Based on the angular polar coordinate distribution diagram and the magnitude of the bimodal coefficient, delineate the separation and attachment flow boundaries in the fluorescent microfilament numbering image;

[0014] S06. Record and save the process of determining the flow state and boundary delineation.

[0015] In step S01, the fluorescent microfilament images acquired in the experiment are sequentially processed by grayscale conversion, binarization, and noise reduction, and the preprocessed fluorescent microfilament images are saved.

[0016] In step S01, the grayscale processing is performed as follows: Based on the RGB three channels of each pixel in the fluorescent microfilament image obtained from the experiment, the R value, G value, and B value are obtained respectively. The grayscale value Gray of the corresponding pixel is calculated using the formula Gray = 0.299R + 0.587G + 0.114B.

[0017] The binarization process is as follows: binarization is performed using the local adaptive threshold mean method;

[0018] The noise reduction process is as follows: After binarization, the direction of the fluorescent microfilament is detected using the eigenvectors of the Hessian matrix. The grayscale value changes are kept smooth along the direction of the fluorescent microfilament from the fixed end to the free end, while the grayscale value changes are kept sharp perpendicular to the direction of the fluorescent microfilament. This completes the noise reduction process, and the pre-processed image of the fluorescent microfilament is saved.

[0019] In step S01, the binarization process is as follows: After the grayscale processing is completed, the average grayscale value of all pixels in the neighborhood of each pixel is calculated as mean(x,y). Then, the local threshold of the pixel is T(x,y) = mean(x,y) - C. The grayscale value of the pixel, Gray(x,y), is compared with T(x,y). If Gray(x,y) ≥ T(x,y), then the grayscale value of the pixel is Gray(x,y) = 255; if Gray(x,y) < T(x,y), then the grayscale value of the pixel is Gray(x,y) = 0.

[0020] Where x is the x-coordinate of the pixel, y is the y-coordinate of the pixel, mean(x,y) is the average gray value of all pixels in the neighborhood of a single pixel, T(x,y) is the local threshold of the pixel, and C is a constant.

[0021] mean(x, y) is the average grayscale value of all pixels in the neighborhood surrounding a single pixel; all pixels in the neighborhood refer to adjacent pixels. For example, in a 9-pixel grid, the neighborhood surrounding the center point consists of the other eight pixels. C is a constant ranging from 0 to 255.

[0022] In step S01, the greater the noise, the larger the C value; the larger the neighborhood range, the smaller the C value.

[0023] In step S02, the coordinates of the fixed end (x1, y1) and the coordinates of the free end (x2, y2) of each fluorescent microfilament are obtained based on its position coordinates. The direction vector v of the fluorescent microfilament is calculated using the formula v=(Δx / Δy)=(x2-x1) / (y2-y1). The angle value θ is calculated using the four-quadrant arctan2(Δy, Δx), with an output range of [-180°, 180°]. Finally, the angle is normalized to a range of 0°~360°.

[0024] In step S04, the specific operation for determining the flow state present in the fluorescent microfilament numbering image is as follows:

[0025] Based on the deflection angle of each fluorescent microfilament, an angular polar histogram corresponding to that microfilament is plotted. Then, using the standard bimodal coefficient formula, the magnitude of the bimodal coefficient of the angular polar histogram is calculated to identify the mixed flow state where separation and attached flow coexist. b Here, n is the standard bimodal coefficient, and n is the sample size. g For sample skewness, k For sample kurtosis, The mean of the sample;

[0026] Standard bimodal coefficient b The calculation formula is:

[0027] ;

[0028] Sample skewness g The calculation formula is:

[0029] ;

[0030] Sample kurtosis k The calculation formula is:

[0031] ;

[0032] Sample mean The calculation formula is:

[0033] .

[0034] In the formula, For the first i The deflection angle of the fluorescent microfilament at the same location in each image.

[0035] In step S05, the location range of the mixed flow state is determined based on the bimodal coefficient of the polar coordinate histogram of each fluorescent microfilament, thereby confirming the location range of the transition from the attached flow to the separated flow, and finally determining the boundary between the two flow states.

[0036] In step S06, the process of determining the flow state and boundary delineation is recorded and saved; among which, the polar coordinate histogram of the deflection angle of each fluorescent microfilament and the flow state are saved.

[0037] To address the aforementioned problems, this application provides a method for dynamic flow spectrum separation and quantitative interpretation of attached flow from fluorescent microfilaments. In a specific example, it includes the following steps.

[0038] S01. Batch preprocessing of fluorescent microfilament images acquired during the experiment under different operating conditions, including temperature, angle of attack, Mach number, Reynolds number, and pressure, was performed. Batch preprocessing included grayscale conversion, binarization, and noise reduction. The preprocessed images of the fluorescent microfilaments under different operating conditions were saved, with filenames including the image name and image format. The image name was determined by the corresponding operating conditions, and the image format was determined by the batch preprocessing results. Specifically, the batch preprocessing set the image format for saving the processed images to facilitate saving and viewing; it only helps to differentiate the images during data analysis and does not involve specific technical processing.

[0039] After acquiring images of fluorescent microfilaments under different operating conditions, the images were preprocessed in the order of grayscale conversion, binarization, and noise reduction. The grayscale conversion process was as follows: a weighted average grayscale method was used. Based on the human eye's sensitivity to different wavelengths of light, different weights were assigned to the RGB channels of each pixel in the acquired fluorescent microfilament images under different operating conditions, and then the grayscale value of the corresponding pixel was obtained by summing the weights. The weighted average formula is Gray = 0.299R + 0.587G + 0.114B; where R, G, and B correspond to the RGB channel values ​​of each pixel, and 0.299, 0.587, and 0.114 are the weighting coefficients, which are derived from the ITU-R BT.709 standard. Green (G) contributes the most to the human eye's perception of brightness, followed by red (R), and blue (B) contributes the least.

[0040] The binarization process is as follows: Using a local adaptive threshold mean method, based on the grayscale result, the average grayscale value mean(x, y) of all pixels in the neighborhood surrounding each pixel is calculated. Then, the local threshold T(x, y) for that pixel is calculated as mean(x, y) - C. The grayscale value Gray(x, y) of the pixel is compared with T(x, y): if Gray(x, y) ≥ T(x, y), then the grayscale value Gray(x, y) = 255; otherwise, Gray(x, y) = 0. The range of the pixel's neighborhood is determined by the resolution of the fluorescent microfilament image acquired in the experiment. In the local threshold calculation formula, C is a constant determined by the noise level of the fluorescent microfilament image and the range of the pixel's neighborhood. Specifically, the greater the noise, the larger the value of C; the larger the neighborhood, the smaller the value of C.

[0041] After binarization is completed, noise reduction is performed. The specific operation is as follows: noise reduction is performed using line segment set features. The main principle is to use the directional adjustable Gaussian derivative kernel, i.e., the Hessian matrix feature vector, to detect the direction of the fluorescent microfilament. Along the main direction, the gray value changes are kept smooth, while the gray value changes are kept sharp perpendicular to the direction of the fluorescent microfilament.

[0042] S02. Based on the preprocessed image of the fluorescent microfilament under the corresponding working condition saved in S01, each fluorescent microfilament in the preprocessed image is divided into blocks and numbered, and its position coordinates are calculated to obtain the numbered image of the fluorescent microfilament.

[0043] This method is based on ordered mesh pasting of fluorescent microfilaments and coordinate transformation. Each fluorescent microfilament corresponds to a block, and the blocks are adaptively divided according to the number of microfilaments, numbered from 1 in a top-down, left-to-right order. Using index transformation, the one-dimensional block number is converted into two-dimensional mesh coordinates, and the coordinate offset is calculated. The offset principle is that the offset of each block is determined by the position of its upper-left corner in the global image. The calculation formula is: Offset = [(Column Index - 1) × Block Width, (Row Index - 1) × Block Height]. Finally, the local coordinates are converted into global coordinates to determine the position coordinates of the fluorescent microfilaments.

[0044] S03. Based on the position coordinates and number of each fluorescent microfilament in the numbered image, calculate the deflection angle of the fluorescent microfilament and generate a set of angle values; the set of angle values ​​includes the number, position coordinates and specific deflection angle value of each fluorescent microfilament.

[0045] Specifically, based on the position coordinates of each fluorescent microfilament, the coordinates of the fixed end (x1, y1) and the coordinates of the free end (x2, y2) can be obtained. The direction vector v of the fluorescent microfilament is calculated using the formula v=(Δx / Δy)=(x2-x1) / (y2-y1). The angle value θ is calculated using the four-quadrant arctan2(Δy, Δx), with an output range of [-180°, 180°]. Finally, the angle is normalized to be converted to the range of 0°~360°.

[0046] S04. Based on the set of angle values, determine the flow state present in the fluorescent microfilament images under different working conditions, and determine the flow state present in the fluorescent microfilament numbered images; the flow state includes attached flow, separated flow, and mixed flow in which both flows exist.

[0047] Specifically, an angular polar histogram is plotted based on the deflection angle of each fluorescent microfilament, and the bimodal coefficient of the angular polar histogram is calculated using the standard bimodal coefficient formula to identify the mixed flow state in which separation and attached flow coexist.

[0048] The standard bimodal coefficients are given below ( b ), sample skewness ( g ), sample kurtosis ( k ) and sample mean The formula for calculating is as follows: where n is the sample size.

[0049] Standard bimodal coefficient b The calculation formula is:

[0050] ;

[0051] Sample skewness g The calculation formula is:

[0052] ;

[0053] Sample kurtosis k The calculation formula is:

[0054] ;

[0055] Sample mean The calculation formula is:

[0056] .

[0057] S05. Based on the angular polar coordinate distribution diagram and the magnitude of the bimodal coefficient, delineate the boundary between the separation and attachment flows in the fluorescent microfilament numbering image.

[0058] In step S05, the location range of the mixed flow state is determined based on the bimodal coefficient of the polar coordinate histogram of each fluorescent microfilament, thereby confirming the location range of the transition from the attached flow to the separated flow, and finally determining the boundary between the two flow states.

[0059] S06. Record and save the process of determining the flow state and boundary delineation.

[0060] The process of determining the flow state and boundary delineation is recorded and saved; specifically, the polar coordinate histogram of the deflection angle of each fluorescent microfilament and the flow state are saved. The image names are determined by the different flow states and operating conditions, and the image format is determined by the batch preprocessing results, serving only to facilitate differentiation during data analysis and not involving specific technical processing.

[0061] Compared with existing technologies, this invention has at least the following advantages: It realizes the visualization of complex flow structures on the near-wall surface of a simple model by using fluorescent microfilaments and image processing technology, and has the characteristics of high sensitivity and high contrast; It proposes quantitative criteria for attached flow and separated flow by utilizing the physical and mathematical meaning of the bimodal coefficient, and realizes dynamic tracking of the evolution process by distinguishing transient flow structures, which helps to solve the problem of difficulty in identifying unsteady flow field structures. Attached Figure Description

[0062] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0063] The present invention will be described by way of example and with reference to the accompanying drawings, wherein:

[0064] Figure 1This is a flowchart of Example 1;

[0065] Figure 2 This is a schematic diagram of the preprocessing results of the fluorescent microfilament image in Example 1;

[0066] Figure 3 This is a schematic diagram of the fluorescent microfilaments in Example 1;

[0067] Figure 4 This is a polar histogram of the deflection angle of the fluorescent microfilaments in Example 1;

[0068] Figure 5 This is a schematic diagram of the boundary division of different flow structures in Example 1. Detailed Implementation

[0069] All features disclosed in this specification, or all steps in all disclosed methods or processes, may be combined in any way, except for mutually exclusive features and / or steps.

[0070] Any feature disclosed in this specification, unless otherwise stated, may be replaced by other equivalent or similar features. That is, unless otherwise stated, each feature is merely one example of a series of equivalent or similar features.

[0071] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0072] Example 1

[0073] This embodiment provides a method for dynamic flow spectrum separation and quantitative interpretation of attached flow of fluorescent microfilaments. The method is applied to a simple airfoil model and includes the following steps.

[0074] S01. Under certain wind tunnel experimental conditions (including Mach number, Reynolds number, temperature, pressure, angle, etc.), the fluorescent microfilament image is preprocessed by grayscale conversion, binarization, and noise reduction to obtain the following result: Figure 2 The results are shown in the figure.

[0075] In this study, a weighted average grayscale method was used. Based on the sensitivity of the human eye to different wavelengths of light, different weights were assigned to the RGB channels of each pixel in the fluorescent microfilament images acquired under different working conditions. The grayscale values ​​of the corresponding pixels were then summed. The weighted average formula was Gray = 0.299R + 0.587G + 0.114B. The weighting coefficients came from the ITU-R BT.709 standard. Green (G) contributed the most to the human eye's perception of brightness, followed by red (R), and blue (B) contributed the least.

[0076] After grayscale conversion, binarization is performed using a local adaptive thresholding method. The binarization process is as follows: After grayscale conversion, the average grayscale value of all pixels in the neighborhood of each pixel is calculated as mean(x, y). The local threshold for that pixel is then T(x, y) = mean(x, y) - C. The grayscale value of the pixel, Gray(x, y), is compared with T(x, y). If Gray(x, y) ≥ T(x, y), the grayscale value of the pixel is Gray(x, y) = 255; if Gray(x, y) < T(x, y), the grayscale value of the pixel is Gray(x, y) = 0. Here, x is the x-coordinate of the pixel, y is the y-coordinate of the pixel, mean(x, y) is the average grayscale value of all pixels in the neighborhood of a single pixel, T(x, y) is the local threshold of the pixel, and C is a constant. The range of the pixel neighborhood is determined by the resolution of the fluorescent microfilament image acquired in the experiment. In the local threshold calculation formula, C is a constant, which is determined by the image noise level and the range of the pixel neighborhood; where, the greater the noise, the larger the value of C; and the larger the neighborhood range, the smaller the value of C.

[0077] After binarization is completed, noise reduction is performed. The specific operation is as follows: noise reduction is performed using line segment set features. The main principle is to use the directional adjustable Gaussian derivative kernel, i.e., the Hessian matrix feature vector, to detect the direction of the fluorescent microfilament. Along the main direction, the gray value changes are kept smooth, while the gray value changes are kept sharp perpendicular to the direction of the fluorescent microfilament.

[0078] S02. Divide and number each fluorescent microfilament in the preprocessed image of the fluorescent microfilament, and calculate its position coordinates to obtain a numbered image of the fluorescent microfilament. The specific operation is as follows.

[0079] Figure 3 A schematic diagram of the fluorescent microfilament numbering and block division results is provided. This is achieved through ordered mesh pasting and coordinate transformation of the fluorescent microfilaments. Each fluorescent microfilament corresponds to one block, and the blocks are adaptively divided according to the number of fluorescent microfilaments, numbered from 1 in a top-down, left-to-right order. Index transformation is used to convert the one-dimensional block number into two-dimensional grid coordinates, and the coordinate offset is calculated. The offset principle is that the offset of each block is determined by the position of its upper-left corner in the global image. The calculation formula is: offset = [(column index - 1) × block width, (row index - 1) × block height]. Finally, the local coordinates are converted into global coordinates to determine the position coordinates of the fluorescent microfilaments.

[0080] S03. Based on the position coordinates and number of each fluorescent microfilament in the numbered image, calculate the deflection angle of the fluorescent microfilament and generate a set of angle values; the set of angle values ​​includes the number, position coordinates and specific deflection angle value of each fluorescent microfilament.

[0081] Specifically, based on the position coordinates of each fluorescent microfilament, the coordinates of the fixed end (x1, y1) and the coordinates of the free end (x2, y2) can be obtained. The direction vector v of the fluorescent microfilament is calculated using the formula v=(Δx / Δy)=(x2-x1) / (y2-y1). The angle value is calculated using the four-quadrant arctan2(Δy, Δx), with an output range of [-180°, 180°]. Finally, the angle is normalized to be converted to the range of 0°~360°.

[0082] S04. Based on the set of angle values, determine the flow state present in the numbered image of fluorescent microfilaments; the flow state includes attached flow, separated flow, and mixed flow in which both types of flow exist.

[0083] Specifically, Figure 4 This is a polar histogram of the deflection angles of each fluorescent microfilament. Figure 4 The number in the upper left corner indicates the serial number of the fluorescent microfilament, i.e., which fluorescent microfilament is being represented. MATLAB is used to plot the polar histogram corresponding to the deflection angle of each fluorescent microfilament, and the bimodal coefficient of the angular polar histogram is calculated using the standard bimodal coefficient formula to identify the mixed flow state where separation and attached flow coexist.

[0084] The standard bimodal coefficients are given below ( b ), sample skewness ( g ), sample kurtosis ( k ) and sample mean The formula for calculating is as follows: where n is the sample size.

[0085] Standard bimodal coefficient b The calculation formula is:

[0086] .

[0087] Sample skewness g The calculation formula is:

[0088] .

[0089] Sample kurtosis k The calculation formula is:

[0090] .

[0091] Sample mean The calculation formula is:

[0092] .

[0093] S05. Based on the angular polar coordinate distribution diagram and the magnitude of the bimodal coefficient, delineate the separation and attachment flow boundaries in the fluorescent microfilament numbering image.

[0094] Specifically, Figure 5 A schematic diagram of the flow structure boundary of a fluorescent microfilament exhibiting mixed flow is presented. Figure 5 The serial numbers corresponding to the dots in the middle are 35, 96, 106, 133, 140, and 156. Figure 4 The serial numbers of the fluorescent microfilaments correspond one-to-one. Specifically, based on the magnitude of the bimodal coefficient of the polar histogram of each fluorescent microfilament, the location range of the mixed flow state is determined, thereby confirming the location range of the transition from the attached flow to the separated flow, and finally determining the boundary between the two flow states.

[0095] S06. Record and save the process of determining the flow state and boundary delineation.

[0096] In step S06, the process of determining the flow state and boundary delineation is recorded and saved; among which, the polar coordinate histogram of the deflection angle of each fluorescent microfilament and the flow state are saved.

[0097] Through calculation, as Figure 4 The polar coordinate distribution of the angles of the fluorescent microfilaments shown below yields the following results: Figure 5 The flow state changes at each location shown. Figure 5 The boundary between attached flow and separated flow is clearly shown (as shown by the green line in the lower right corner). Above the line is attached flow, and below the line is strong separated flow. The flow near the green line contains both attached flow and separated flow.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for dynamic flow spectrum separation and quantitative interpretation of attached flow of fluorescent microfilaments, characterized in that, Includes the following steps: S01. Preprocess the fluorescent microfilament images acquired in the experiment and save the preprocessed fluorescent microfilament images. S02. Divide and number each fluorescent microfilament in the preprocessed image of fluorescent microfilaments, and calculate its position coordinates to obtain a numbered image of fluorescent microfilaments. S03. Based on the position coordinates and number of each fluorescent microfilament in the numbered image, calculate the deflection angle of the fluorescent microfilament and generate a set of angle values; the set of angle values ​​includes the number, position coordinates and specific deflection angle value of each fluorescent microfilament. S04. Based on the set of angle values, determine the flow state present in the fluorescent microfilament numbering image; the flow state includes attached flow, separated flow, and mixed flow, and the mixed flow refers to the simultaneous presence of attached flow and separated flow. S05. Based on the angular polar coordinate distribution diagram and the magnitude of the bimodal coefficient, delineate the separation and attachment flow boundaries in the fluorescent microfilament numbering image; S06. Record and save the process of determining the flow state and boundary delineation.

2. The method according to claim 1, characterized in that, In step S01, the fluorescent microfilament images acquired in the experiment are sequentially processed by grayscale conversion, binarization, and noise reduction, and the preprocessed fluorescent microfilament images are saved.

3. The method according to claim 2, characterized in that, In step S01, the grayscale processing is performed as follows: Based on the RGB three channels of each pixel in the fluorescent microfilament image obtained from the experiment, the R value, G value, and B value are obtained respectively. The grayscale value Gray of the corresponding pixel is calculated using the formula Gray = 0.299R + 0.587G + 0.114B. The binarization process is as follows: binarization is performed using the local adaptive threshold mean method; The noise reduction process is as follows: After binarization, the direction of the fluorescent microfilament is detected using the eigenvectors of the Hessian matrix. The grayscale value changes are kept smooth along the direction of the fluorescent microfilament from the fixed end to the free end, while the grayscale value changes are kept sharp perpendicular to the direction of the fluorescent microfilament. This completes the noise reduction process, and the pre-processed image of the fluorescent microfilament is saved.

4. The method according to claim 3, characterized in that, In step S01, the binarization process is as follows: After the grayscale processing is completed, the average grayscale value of all pixels in the neighborhood of each pixel is calculated as mean(x,y). Then, the local threshold of the pixel is T(x,y) = mean(x,y) - C. The grayscale value of the pixel, Gray(x,y), is compared with T(x,y). If Gray(x,y) ≥ T(x,y), then the grayscale value of the pixel is Gray(x,y) = 255; if Gray(x,y) < T(x,y), then the grayscale value of the pixel is Gray(x,y) = 0. Where x is the x-coordinate of the pixel, y is the y-coordinate of the pixel, mean(x,y) is the average gray value of all pixels in the neighborhood of a single pixel, T(x,y) is the local threshold of the pixel, and C is a constant.

5. The method according to claim 1, characterized in that, In step S02, the coordinates of the fixed end (x1, y1) and the coordinates of the free end (x2, y2) are obtained based on the position coordinates of each fluorescent microfilament. The direction vector v of the fluorescent microfilament is calculated using the formula v=(Δx / Δy)=(x2-x1) / (y2-y1). The angle value is calculated using the four-quadrant arctan2(Δy, Δx), with an output range of [-180°, 180°]. Finally, the angle is normalized to be converted to the range of 0°~360°.

6. The method according to claim 1, characterized in that, In step S04, the specific operation for determining the flow state present in the fluorescent microfilament numbering image is as follows: Based on the deflection angle of each fluorescent microfilament, an angular polar histogram corresponding to that microfilament is plotted. Then, using the standard bimodal coefficient formula, the magnitude of the bimodal coefficient of the angular polar histogram is calculated to identify the mixed flow state where separation and attached flow coexist. b Here, n is the standard bimodal coefficient, and n is the sample size. g For sample skewness, k For sample kurtosis, The mean of the sample; Standard bimodal coefficient b The calculation formula is: ； Sample skewness g The calculation formula is: ； Sample kurtosis k The calculation formula is: ； Sample mean The calculation formula is: 。 7. The method according to claim 1, characterized in that, In step S05, the location range of the mixed flow state is determined based on the bimodal coefficient of the polar coordinate histogram of each fluorescent microfilament, thereby confirming the location range of the transition from the attached flow to the separated flow, and finally determining the boundary between the two flow states.

8. The method according to claim 1, characterized in that, In step S06, the process of determining the flow state and boundary delineation is recorded and saved; among which, the polar coordinate histogram of the deflection angle of each fluorescent microfilament and the flow state are saved.

Images