Wind tunnel flow field display inversion calculation method and device and readable storage medium

Abstract

The invention discloses a wind tunnel flow field display inversion calculation method and device and a readable storage medium, and relates to the technical field of wind tunnel measurement, and the wind tunnel flow field display inversion calculation method comprises the steps: obtaining a fluorescence image, and generating a streamline isogram according to the fluorescence image; configuring the plurality of streamline isograms at different moments at corresponding positions of a time axis respectively to obtain a plurality of time sequence diagrams; marking points are selected, different marking lines are drawn at the positions of the marking points of the multiple time sequence diagrams along the time axis according to the change relation between the yaw angles of the marking points and time, and multiple three-dimensional images are obtained; and sequentially displaying the plurality of three-dimensional images along a time sequence, and synthesizing the three-dimensional images into a three-dimensional video. A streamline time inversion dynamic demonstration effect can be realized through a three-dimensional video, so that the change process of a yaw angle, the change rule of a flow field and the like can be clearly observed. The marking line is drawn along the time axis, the change condition of the surface flow field of the marking point can be emphatically shown, and the flow field condition of the position area where the marking point is located can be clearer.

Description

Technical Field

[0001] The present invention relates to the technical field of wind tunnel measurement, and particularly to a wind tunnel flow field display inversion calculation method, device, and readable storage medium. Background Art

[0002] The wind tunnel flow field display experiment simulates fluid flow in a wind tunnel, combines visualization technology to observe and analyze the flow field structure, so as to study the airflow characteristics, verify the design effect, and optimize the shape design of aircraft, automobiles, etc. It can convert the invisible flow field characteristics into visible images to assist engineers in understanding complex flow phenomena.

[0003] In the wind tunnel flow field display experiment, in order to qualitatively observe the separation morphology on the model surface, the fluorescent silk thread flow display technology is adopted. In previous wind tunnel experiments, the fluorescent silk thread technology was to take pictures of the silk thread states at different positions and postures of the model by a camera, and then roughly judge the flow path situation in the area where the silk thread is located by the naked eye. This has low efficiency, low accuracy, is prone to judgment errors, and cannot display the changes in the fluid on the object surface, which is not convenient for engineers to understand and analyze. Summary of the Invention

[0004] In order to solve the above problems, the present invention adopts the following technical solutions: The first aspect of the present invention provides a wind tunnel flow field display inversion calculation method.

[0005] The wind tunnel flow field display inversion calculation method of the present invention includes the following steps: Obtain a fluorescent image, and generate a streamline contour map according to the fluorescent image; Configure the streamline contour maps at different times at corresponding positions on the time axis respectively to obtain a plurality of time series diagrams; Select a marking point, and draw different marking lines along the time axis at the marking point positions of the plurality of time series diagrams according to the variation relationship between the yaw angle of the marking point and time to obtain a plurality of three-dimensional images; Show the plurality of three-dimensional images in sequence along the time order and synthesize them into a three-dimensional video.

[0006] The second aspect of the present invention provides a wind tunnel flow field display inversion calculation device.

[0007] The wind tunnel flow field display inversion calculation device of the present invention is used to implement the wind tunnel flow field display inversion calculation method of any one of the technical solutions in the present invention. The wind tunnel flow field display inversion calculation device includes: A generation module, configured to obtain a fluorescent image and generate a streamline contour map according to the fluorescent image; A time series module, configured to configure the streamline contour maps at different times at corresponding positions on the time axis respectively to obtain a plurality of time series diagrams; A drawing module, configured to select marked points, and draw different marked lines along the time axis at the positions of the marked points in multiple time series diagrams according to the variation relationship between the yaw angle of the marked points and time, so as to obtain multiple three-dimensional images; and A synthesis module, configured to sequentially show multiple three-dimensional images in time sequence and synthesize them into a three-dimensional video.

[0008] The third aspect of the present invention provides a readable storage medium.

[0009] In the readable storage medium of the present invention, a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the wind tunnel flow field display inversion calculation method according to any one of the technical solutions in the present invention are implemented.

[0010] The technical solution adopted by the present invention can achieve the following beneficial effects: streamline contour maps are generated from fluorescence images, and the streamline contour maps record information such as the path, direction, and yaw angle of the airflow. By configuring the streamline contour maps at corresponding positions on the time axis, multiple time series diagrams are obtained, which is conducive to understanding and analyzing the variation of the surface flow field over time. The three-dimensional video can adjust the playback order, adjust the viewing angle, scale ratio, or select a specific streamline area. The three-dimensional video can achieve the dynamic demonstration effect of streamline time inversion, which can clearly observe the variation process of the yaw angle and the variation law of the flow field, etc. In addition, in the three-dimensional video, marked lines are drawn along the time axis, which can highlight the variation of the surface flow field of the marked points, can more clearly mark the flow field situation in the area where the marked points are located, with high accuracy, and avoid situations such as misjudgment. Description of the Drawings

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0012] Figure 1 is a flowchart of the wind tunnel flow field display inversion calculation method shown in an exemplary embodiment of the present application; Figure 2 is a schematic diagram of a fluorescence image shown in an exemplary embodiment of the present application; Figure 3 is Figure 2 an enlarged view of part a in Figure 4 is a schematic diagram of a streamline contour map shown in an exemplary embodiment of the present application; Figure 5 is a schematic diagram of a time series diagram shown in an exemplary embodiment of the present application; Figure 6 It is a schematic diagram of another timing diagram shown in an exemplary embodiment of the present application; Figure 7 It is a schematic diagram of a timing diagram at another moment shown in an exemplary embodiment of the present application; Figure 8 It is a processing flow chart of a fluorescence image shown in an exemplary embodiment of the present application; Figure 9 It is a schematic diagram of a streamline diagram shown in an exemplary embodiment of the present application; Figure 10 It is a schematic diagram of an isogram shown in an exemplary embodiment of the present application; Figure 11 It is a schematic structural diagram of an inversion calculation device for wind tunnel flow field display shown in an exemplary embodiment of the present application; Figure 12 It is a schematic structural diagram of an electronic device shown in an exemplary embodiment of the present application.

[0013] In the figure: 500, inversion calculation device for wind tunnel flow field display; 510, generation module; 520, timing module; 530, drawing module; 540, synthesis module; 600, electronic device; 610, processor; 620, memory. Detailed implementation manners

[0014] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be described in detail below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation manners obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0015] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such used data may be interchanged under appropriate circumstances so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. generally belong to the same category, and do not limit the number of objects. For example, the first object may be one or multiple. In addition, "and / or" in the specification and claims means at least one of the connected objects, and the character " / ", generally represents an "or" relationship between the associated objects before and after.

[0016] In the wind tunnel flow field display test, in order to qualitatively observe the separation pattern on the model surface, the fluorescent wire flow display technology is adopted. Specifically, by treating thin and flexible fibers (such as nylon wires) with fluorescent dyes and then pasting them on the surface or grid of the object to be detected, these fluorescent wires will emit bright fluorescence under the irradiation of ultraviolet light. Since the wires are very thin and have little influence on fluid flow, they can accurately reflect the fluid flow situation. The fluorescent wire flow display technology can directly observe the fluid flow around the current object to be detected, but it is difficult to directly know the subsequent fluid changes, let alone quantify and visually present them, resulting in the limited application range of the fluorescent wire flow display technology, making it difficult for engineers to make accurate judgments in a timely manner and reducing the use effect of the wind tunnel flow field display test.

[0017] The first aspect of this embodiment will elaborate on the inverse calculation method for wind tunnel flow field display.

[0018] Figure 1 The flowchart of the inverse calculation method for wind tunnel flow field display in this embodiment is shown. As Figure 1 shown, the inverse calculation method for wind tunnel flow field display in this embodiment includes the following steps: Step S100: Obtain a fluorescent image and generate a streamline contour map based on the fluorescent image.

[0019] Obtain a fluorescent image. The acquisition methods include but are not limited to direct transmission by a camera device or transmission after preprocessing. The information recorded in the fluorescent image includes but is not limited to the structure of the object to be detected, the distribution map of multiple fluorescent wires on the surface of the object to be detected, and the pose of specific fluorescent wires, etc., which are not limited here. As Figure 2 and Figure 3 shown, Figure 2 shows the fluorescent image, Figure 2 and Figure 3 the blue objects in it are fluorescent wires. Figure 3 is Figure 2 the enlarged view at point a in Figure 3 and the values on each fluorescent wire in

[0020] are the corresponding yaw angle values of the fluorescent wires. Among them, the object to be detected includes but is not limited to aircraft, automobiles or their model structures, etc., which are not limited here. Figure 4 Generate a streamline contour map based on the fluorescent image. Figure 4 shows the streamline contour map, Figure 4 the x-axis and y-axis in Figure 4The surrounding fluid and flow field of the object to be detected are recorded in the fluorescence image. The distribution and posture of multiple fluorescent filaments are recorded in the fluorescence image, and a streamline contour map can be generated based on the distribution and posture of multiple fluorescent filaments. The streamline contour map is about the yaw angle of the object to be detected, where the yaw angle refers to the direction in which the flow direction of the fluid at that location deviates from the ground or a specified direction.

[0021] Streamline contour maps record the flow path of the fluid around the object to be detected in the flow field, which can help engineers intuitively understand the overall structure and dynamic changes of the flow field. In addition, streamline contour maps also record the yaw angle distribution of the fluid around the object to be detected at the same time. The yaw angle distribution of the fluid around the object to be detected can reflect the impact of the airflow on it during flight, thereby helping engineers optimize the design of the object to be detected, reduce resistance during driving, and improve driving efficiency and stability.

[0022] Step S200: arranging a plurality of streamline contour diagrams at different times at corresponding positions on the time axis to obtain a plurality of timing diagrams.

[0023] The streamline contour maps at multiple different moments are obtained by converting the fluorescent images at multiple different moments through the above method. Therefore, the streamline contour maps represent the flow field around the object to be detected and the yaw angle distribution of the fluid at the corresponding moment.

[0024] Multiple streamline contour diagrams at different times are placed at corresponding positions on the time axis to obtain multiple time series diagrams. Figure 5 , which means that the streamline contour diagram is configured at the corresponding position of the time axis. Figure 5 The z-axis and y-axis represent the spatial coordinates of the data points of the streamline contour map, in millimeters (mm). Figure 5 The x-axis (i.e., time axis) in the figure represents the corresponding time of the streamline contour diagram, in milliseconds (ms). Figure 5 The different colors in represent different yaw angles, in degrees (°). Figure 5 As shown in FIG. 1 , taking the initial time as the timing point, a streamline contour diagram records the flow field around the object to be detected and the yaw angle distribution of the fluid at 400ms. Therefore, if the streamline contour diagram is arranged at 400ms on the time axis, the corresponding timing diagram will be obtained.

[0025] It is understandable that the intervals between multiple fluorescent images at different times are the same or different, which will make the streamline contour maps at multiple times arranged evenly or unevenly on the time axis, which is not limited here. In a certain time period, the yaw angle of the fluid may change greatly, and the flow field changes too drastically, so the number of fluorescent images in this time period is set to be more, so as to observe the changes in the fluid and process.

[0026] Convert the streamline contour maps at multiple different times into multiple time series diagrams, which makes the streamline contour maps correspond to the time sequence. This can facilitate engineers to understand and analyze the changes of fluids and processes over time, improving observability.

[0027] It is understandable that the time series diagram can be an axonometric view, which can clearly observe the situation of each part of the streamline contour map in the time series diagram and also know the corresponding position of the streamline contour map on the time axis, that is, clearly know the specific time situation of the streamline contour map. Moreover, engineers can also observe the overall evolution process of the flow field flow state, and can freely rotate, zoom in and out, and pan the time series diagram to observe the flow field state at different times from different angles.

[0028] In some other cases, such as Figure 6 shown, Figure 6 the z-axis and y-axis represent the spatial coordinate positions of the data points of the streamline contour map, with the unit of millimeters (mm), Figure 6 and the x-axis (i.e., the time axis) in [] represents the corresponding times of multiple streamline contour maps, with the unit of milliseconds (ms). It is also possible to synthesize the streamline contour maps at multiple different times into the same time series diagram, and multiple of them are arranged in order on the time axis in the same time series diagram. This can show the change trend and evolution process of the flow over time.

[0029] Step S300: Select marking points, and draw different marking lines along the time axis at the positions of the marking points in multiple time series diagrams according to the variation relationship between the yaw angle of the marking points and time, to obtain multiple three-dimensional images.

[0030] Select marking points. The marking points can be selected by the tester through presetting or manual input, etc., without limitation. Moreover, the selection of the marking points can be affected by the specific object to be detected and wind speed, etc., to ensure that more critical positions can be selected, such as areas where the flow field changes more significantly, the area of this improvement, or the area where there was a fault in the previous test, etc.

[0031] According to the variation relationship between the yaw angle of the marking points and time, draw different marking lines along the time axis at the positions of the marking points in multiple time series diagrams, to obtain multiple three-dimensional images. At the same marking point, the flow field near the marking point may change over time. According to the variation relationship between the yaw angle and time, draw different marking lines along the time axis. Marking lines can be drawn at multiple marking points in each time series diagram, and multiple marking lines such as Figure 5As shown by multiple straight lines with arrows in different colors. Its marking line changes according to the specific parameters of the yaw angle, such as its thickness, color, arrow, or a combination of multiple ones. This can highlight the change of the surface flow field at the marked point, and can more clearly show the flow field situation in the position area where the marked point is located, with high accuracy and avoiding situations such as misjudgment.

[0032] Step S400: Show multiple three-dimensional images in chronological order and synthesize them into a three-dimensional video.

[0033] The three-dimensional images are shown in chronological order and synthesized into a three-dimensional video. For example, as Figure 5 and Figure 7 shown, the three-dimensional video can show the three-dimensional images in sequence. Further, align the time axes of multiple three-dimensional images so that the positions of the time axes are relatively fixed. In the three-dimensional video, the part that changes each time is the streamline isogram in the three-dimensional image, and the positions of multiple sequentially shown streamline isograms will also change with the time axis, that is, gradually move farther or closer. Exemplarily, the multiple three-dimensional images are three-dimensional images at 0, 500 ms, and 1000 ms respectively. In chronological order, the three-dimensional image at 0 moment, the three-dimensional image at 500 ms moment, and the three-dimensional image at 1000 ms moment are shown in sequence. This can clearly observe the change process of the yaw angle of the streamline isogram and the flow field change law, etc.

[0034] In addition, the three-dimensional video can be paused or started, the playback order can be adjusted (in the forward or reverse chronological order), the viewing angle, the zoom ratio can be adjusted, or a specific streamline area can be selected, so as to obtain more detailed flow field information, which provides a powerful analysis and diagnosis function for engineers.

[0035] Preferably, when the three-dimensional video shows one of the streamline isograms at multiple different moments, the three-dimensional video correspondingly shows the wind speed, the pose of the object to be detected, and the time information at the same moment. The three-dimensional video also shows the pose of the object to be detected in real time, including its position, direction, and attitude, etc. This is of great significance for studying the motion law and force condition of the object to be detected in the flow field. And through the time information, engineers can easily track the changes of the flow field and the object state over time, which is crucial for dynamic flow field analysis and object motion prediction.

[0036] The wind tunnel flow field display inversion calculation method of the preferred technical solution of this embodiment generates streamline contour maps through fluorescence images. The streamline contour maps record information such as the path, direction, and yaw angle of the airflow. By configuring the streamline contour maps at corresponding positions on the time axis, multiple time series diagrams are obtained, which is conducive to understanding and analyzing the change of the surface flow field of the object to be detected over time. The 3D video can adjust the playback order, adjust the viewing angle, zoom ratio, or select a specific streamline area. The 3D video can achieve the dynamic demonstration effect of streamline time inversion, which can clearly observe the change process of the yaw angle and the change law of the flow field, etc. In addition, in the 3D video, a marking line is drawn along the time axis, which can highlight the change of the surface flow field of the marked point, and can more clearly mark the flow field situation in the area where the marked point is located, with high accuracy and avoiding misjudgment and other situations.

[0037] According to an optional implementation manner, step S100: Obtain a fluorescence image and convert it into a streamline contour map according to the fluorescence image, including at least the following steps: Step S110: Obtain a fluorescence image and select a reference direction.

[0038] Obtain a fluorescence image. The acquisition methods include but are not limited to direct transmission by a camera device or transmission after preprocessing. The information recorded in the fluorescence image includes but is not limited to the structure of the object to be detected, the distribution map of multiple fluorescent filaments on the surface of the object to be detected, and the pose of specific fluorescent filaments, etc., which are not limited here.

[0039] Select a reference direction. Coding points are respectively pasted at two ends of the object to be detected that are far away from each other. Further, the object to be detected has a first end and a second end that are far away from each other. After detecting the coding points, the center of the coding point at the first end of the object to be detected is used as the starting point, and the center of the coding point at the second end is used as the ending point. The vector connecting the two points is used as the reference direction.

[0040] Exemplarily, the object to be detected can be an aircraft model. The first end can be the head end of the aircraft model, and the second end can be the tail end of the aircraft model. The connection line between the head end and the tail end can be used as the reference direction and used as the basis for subsequent comparison and detection.

[0041] Step S120: Compare multiple fluorescent filaments in the fluorescence image with the reference direction to obtain multiple yaw angles.

[0042] Under the influence of the fluid, multiple fluorescent filaments in the fluorescence image will present different postures, that is, the fluorescent filaments will deflect in different directions. Its deflection direction is affected by the fluid. Conversely, its deflection direction can also show the flow situation of the fluid, the state of the flow field, etc.

[0043] Compare multiple fluorescent filaments in the fluorescence image with the reference direction to obtain multiple yaw angles. Further, this step at least includes: according to the image information of the multiple fluorescent filaments, compare the image information with the reference direction to obtain the yaw angles of the multiple fluorescent filaments. Compare the multiple fluorescent filaments after deflection in the fluorescence image, which is compared with the reference direction, and the included angle between the fluorescent filament and the reference direction is the yaw angle.

[0044] Step S130: Generate a streamline contour map according to the fluorescence image and the yaw angle.

[0045] Generate a streamline contour map according to the fluorescence image and the yaw angle. Generate a streamline contour map according to the specific positions of the fluorescent filaments in the fluorescence image and the corresponding yaw angles. Exemplarily, not every location in the fluorescence image is provided with fluorescent filaments. The areas without fluorescent filaments can be deduced and analogized through the yaw angles of the surrounding fluorescent filaments and the flow field state, and then a streamline contour map is generated by fitting. The streamline contour map has the relevant content of a streamline map and an isogram, that is, it shows the flow paths in the flow field of the area where the fluorescent lines are located. In the streamline contour map, different isograms represent different yaw angle values, and the density and direction of the isograms reflect the changes in the velocity and direction of fluid flow.

[0046] According to an optional embodiment, before step S120: Compare multiple fluorescent filaments in the fluorescence image with the reference direction, at least the following steps are included: Step S141: Obtain a fluorescence video and decompose the fluorescence video into multiple single-frame fluorescence images; Obtain a fluorescence video, and the fluorescence video can be directly obtained by a camera module. The fluorescence video can be in a video format with multiple frames per second. According to specific accuracy requirements and application scenarios, etc., select the shooting parameters and specifications of the camera module, and then change the specifications and parameters of the fluorescence video, such as the number of frames, resolution, etc.

[0047] Decompose the fluorescence video into multiple single-frame fluorescence images. Select the fluorescence filament image to be processed and read the image. Process the collected fluorescence video, decompose the fluorescence video into single-frame images, and select one or more frames of images to be processed for subsequent processing.

[0048] Step S142: Perform grayscale processing, Gaussian filtering processing, adaptive binarization processing, connected region detection, and region extraction on the fluorescence image in sequence to obtain the image information of the fluorescent filaments.

[0049] Perform grayscale processing, Gaussian filtering processing, adaptive binarization processing, connected region detection, and region extraction on the fluorescence image in sequence to obtain the image information of the fluorescent filaments, as Figure 8 shown, Figure 8 shows the processing flow chart of the fluorescence image.

[0050] Gray-scale the fluorescence image. Convert the RGB color image in the fluorescence image to a grayscale image. Exemplarily, the acquired fluorescence image captured by the camera module is an RGB color image. First, gray-scale the color fluorescent filaments in the fluorescence image, and gray-scale the R, G, and B channel images into a single-channel image to remove redundant image information, reduce the occupation of computing resources, and improve processing efficiency.

[0051] Furthermore, perform Gaussian filtering on the fluorescence image. The camera module may generate Gaussian noise due to uneven light intensity in the shooting field of view and interference from other sensors. After the fluorescence image of the present application is gray-scaled, perform Gaussian filtering on the gray-scaled image. The equation of the two-dimensional Gaussian function is shown as follows: Where: is the specific position coordinate value based on the center point of the fluorescence image for Gaussian filtering processing; is the standard deviation, which is used to control the width of the Gaussian function; a Gaussian convolution kernel matrix can be generated through the Gaussian function for convolution filtering operations. The specific implementation method of the Gaussian filtering algorithm is to perform a convolution operation between the Gaussian filter kernel and the image, which is used to reduce the noise and details in the fluorescence image, make the fluorescence image smoother, and reduce the interference of image noise on subsequent processing.

[0052] Furthermore, perform adaptive binarization on the fluorescence image. Use the adaptive binarization algorithm to further process the gray-scale fluorescence image after Gaussian filtering. The binarization algorithm is used to separate the foreground and background in the fluorescence image, and can distinguish the fluorescent filaments in the fluorescence image from the objects to be detected and other interfering backgrounds, and retain the required fluorescent filaments and their details from the fluorescence image to obtain a binarized image.

[0053] Perform connected component detection on the fluorescence image. Perform connected component detection on the obtained binarized image to identify all independent edge regions, providing a basis for subsequent extraction and linear fitting of fluorescent filaments.

[0054] Perform region extraction on the fluorescence image. Since multiple fluorescent filaments have the same length, when the camera module and the object to be detected are certain, the number of pixels occupied by the fluorescent filaments in the same image has little difference, and the sizes of the connected regions corresponding to different filaments are all within a certain similar range; after multiple tests, find the range value that can contain all the connected regions of the fluorescent filaments, and accordingly extract the specific parameters of the fluorescent filaments from the detected connected regions.

[0055] Finally, the fluorescent thread area of ​​the fluorescent image is linearly fitted. Although the rigidity of the fluorescent thread is very low, the fluorescent thread is not a standard straight line in the fluorescent image; and after the fluorescent thread is excited by the ultraviolet light, the edge of the fluorescent thread will occupy more pixels in the image. The present application can fit the extracted fluorescent thread area into a straight line to accurately calculate the yaw angle of the fluorescent thread and draw a streamline diagram.

[0056] This application uses singular value decomposition (SVD) to perform straight line fitting for each fluorescent thread area. SVD has good resistance to noise and outliers in the data, and can stably capture the main trends of the data; and SVD determines the best fitting line by minimizing the sum of the squares of the vertical distances from the point to the line, without biasing towards any coordinate axis, and can be used to fit fluorescent thread areas with arbitrary directions, and can obtain the best straight line fitting effect. The specific principles of SVD are as follows: Assume that the two-dimensional data point set in the fluorescent thread area to be fitted is: (N is greater than or equal to 1) The straight line to be fitted is .in, is the linear parameter vector formed by the fluorescent silk line region fitting, , a, b, c are the line parameter vectors The elements in a and b satisfy , T represents transpose; Represents the homogeneous coordinates of two-dimensional data points, where x and y are the horizontal and vertical coordinates of each two-dimensional data point. Represent the data point set in homogeneous coordinate form and construct the design matrix As shown below: To solve for the line parameter vector Make the data point set as satisfy as possible , p is the parameter vector of the line, which can be converted to minimize the error Time Solution , Received =1 constraint.

[0057] Decomposition of matrix A by SVD: Where: U is An orthogonal matrix whose column vectors are called left singular vectors; ∑ is The diagonal matrix of , the elements on the diagonal are non-negative real numbers, called singular values, and are arranged in order from large to small; V is an orthogonal matrix, and its column vectors are called right singular vectors.

[0058] Substitute into the optimization problem and the following process can be obtained: by Since U is an orthogonal matrix, its norm remains unchanged.

[0059] To minimize , and = 1, select such that corresponds to the smallest singular value of ∑.

[0060] Therefore, the optimal solution is the last column of V, that is, the right singular vector corresponding to the smallest singular value.

[0061] After obtaining the optimal solution , the best straight line fitted to the fluorescent silk thread region can be obtained .

[0062] Using SVD to solve the best fitting straight line for each fluorescent silk thread region and marking each fitted straight line in the region where the original fluorescent silk thread is located can reduce the influence of other factors and ensure the accuracy of the specific parameters of the fluorescent silk thread, such as its position, attitude, etc., thereby improving the calculation accuracy of subsequent yaw angles and the like.

[0063] According to an optional implementation manner, step S130: Generate a streamline contour map based on the fluorescence image and the yaw angle, including: Step S131: Generate a streamline map based on the image information of multiple fluorescent silk threads.

[0064] Specifically, as Figure 9 shown, Figure 9 the x-axis and y-axis of

[0065] represent the spatial horizontal and vertical coordinates of the data points of the streamline map, with the unit of millimeters (mm). Convert the straight line where the fluorescent silk thread is located into a vector, and this vector represents the flow field direction at the position where the corresponding fluorescent silk thread is located. Moreover, use the streamslice function in MATLAB to draw the streamline map to display the flow pattern and direction change of the flow field at the position where the fluorescent silk thread is located. Among them, x and y are two-dimensional grid coordinate matrices generated based on the fluorescent filaments in the fluorescence image, which define the coordinate positions of each point within the streamline plot area. Among them, these matrices are generated through the meshgrid function and cover the entire area of the image. The two two-dimensional arrays u_combined and v_combined respectively represent the x-component and y-component of the vector fitted according to the fluorescent filaments at each grid point (x, y). Specifically, u_combined represents the horizontal component, and v_combined represents the vertical component.

[0066] Furthermore, the streamslice function selects some sample points on the given grid (x, y). These sample points perform vector sampling according to the nearest fluorescent filament at their locations. The sampling points determine the starting positions of the streamline segments to ensure that the streamlines start from the key areas of the flow field.

[0067] Moreover, according to the vector direction fitted by the nearby fluorescent filaments, the streamslice function advances a certain distance along these vectors through numerical integration to generate at least part of the streamline. This process is repeated until the sampling points exceed the calculation area or reach the preset number of integration steps. Furthermore, the streamslice function connects the sampling points obtained through integration to generate smooth streamlines.

[0068] Since the vector data fitted by the fluorescent filaments is often sparse and cannot be directly used to draw a continuous streamline plot, this application uses the griddata function for interpolation to convert the sparse fluorescent filament vector data into a dense vector field. However, during the interpolation process, due to insufficient data points around certain positions, the griddata function cannot calculate an effective interpolation result and thus returns NaN. At this time, these NaN values are set to 0 to ensure that a continuous streamline plot can be drawn.

[0069] Step S132: Generate a contour map based on the yaw angles of multiple fluorescent filaments.

[0070] As Figure 10 shown, Figure 10 the x-axis and y-axis of Figure 10 represent the spatial horizontal and vertical coordinates of the data points of the contour map, with the unit of millimeters (mm). The contourf function will find a series of contour lines within a specified area according to the yaw angles of the vectors represented by each fluorescent filament. These contour lines connect points with the same deviation angle.

[0071] The contourf function will fill the colors between adjacent contour lines to generate a contour map. Different regions within the contour map have different colors, which can intuitively show the angular distribution between the fluorescent filaments and the flow field direction.

[0072] Among them, it is represented using the current colormap according to the yaw angle of the fluorescent filament. The colormap defines a color gradient sequence from the minimum yaw angle value to the maximum yaw angle value. Exemplarily, the yaw angle of a certain area is 0, and the color of this area is cyan. Based on the yaw angle of 0, as the yaw angle gradually increases, the color of the area gradually changes to dark red. Based on the yaw angle of 0, as the yaw angle gradually decreases, the color of the area gradually changes to dark blue.

[0073] Step S133: Fit the streamline map and the contour map at the same moment to form a streamline contour map.

[0074] As Figure 4 shown, set the streamline map and the contour map correspondingly. The streamline map is fitted on the contour map to form a streamline contour map. Exemplarily, keep the streamlines of the streamline map and increase the transparency of the rest. When fitting the processed streamline map to the contour map, where the layer of the streamline map is on the layer of the contour map so that the streamline map can be clearly obtained. This can obtain a clearer streamline contour map.

[0075] According to an optional embodiment, step S300: Select marked points. According to the change relationship between the yaw angle of the marked points and time, draw different marked lines along the time axis at the positions of the marked points in multiple time series diagrams, including: Step S310: Select the positions where at least part of the fluorescent filaments are located as marked points.

[0076] Select the positions where at least part of the fluorescent filaments are located as marked points. The number of fluorescent filaments is multiple. Select part or all of the fluorescent filaments as marked points. The change state and the change law of the yaw angle of the fluorescent filaments are both known. To improve the visualization degree of its change law, select them as marked points.

[0077] It can be understood that before calculating the yaw angle, the positions of multiple fluorescent filaments have been obtained, which is also convenient for automatically selecting marked points later to improve the degree of automation. Or, the tester can also manually input or select the specific positions of the marked fluorescent filaments.

[0078] In some other cases, the marked points can be manually selected by the tester and are not the positions where the fluorescent filaments are located. The specific selection requirements for the marked points will be affected by debugging requirements and the like.

[0079] Step S320: Obtain the yaw angles of the marked points in multiple time series diagrams.

[0080] Obtain the yaw angles of the marked points in multiple time series diagrams. According to the positions of the marked points, confirm the yaw angle parameters at the corresponding positions. It can be understood that the yaw angle can be obtained from the corresponding area of the contour map, that is, by detecting the color at the corresponding position of the contour map for detection and judgment. However, when the marked point is selected as the position where the fluorescent filament is located, the yaw angle of the fluorescent filament has been recorded, and only the corresponding yaw angle of the corresponding fluorescent filament needs to be obtained, which can simplify the acquisition steps and improve the detection efficiency.

[0081] Step S330: Draw marked lines along the time axis at the positions of the marked points in multiple time series diagrams according to the change relationship between the yaw angle of the marked points and time.

[0082] Draw different marked lines along the time axis at the positions of the marked points in multiple time series diagrams according to the change relationship between the yaw angle of the marked points and time. As Figure 5 shown, at the same marked point, the flow field near the marked point may change with time. Draw different marked lines along the time axis according to the change relationship between the yaw angle and time. Marked lines can be drawn at multiple marked points in each time series diagram, and the marked lines change according to the specific parameters of the yaw angle, such as its thickness, color, arrow, or a combination of multiple ones. This can highlight the change of the surface flow spectrum of the marked points, and it can more clearly indicate the flow spectrum situation in the area where the marked points are located, with high accuracy and avoiding situations such as misjudgment.

[0083] Step S340: Configure the marked information of the marked line as the yaw angle of the corresponding marked point in the streamline contour map of the previous moment.

[0084] Configure the marked information of the marked line as the yaw angle of the corresponding marked point in the streamline contour map of the previous moment. When the marked line is drawn, the information carried by the marked line drawn at a certain moment is the yaw angle situation of the corresponding marked point in the streamline contour map of the previous moment. The purpose of doing this is to clearly present the change trend and continuity of the yaw angle in the time series. This helps researchers analyze the influence of the airflow on the object at different times and the change of the object's attitude in the airflow. Among them, the marked information is intuitively shown by the marked line, and the marked information can be intuitively obtained by users such as engineers. The marked line can be configured so that the marked information of the marked line can include the line color.

[0085] Among them, the color of the marking line shows the corresponding yaw angle information, and the color of the streamline contour map shows the corresponding yaw angle information. The color of the marking line can be set corresponding to the color of the contour map area, which can reduce color errors and interference and facilitate the user's understanding and observation.

[0086] In some other cases, the color of the marking line can also be configured as a gradient color, that is, the color of the marking line changes from a first color (representing the color of the yaw angle of the corresponding marking point of the streamline contour map at the previous moment) to a second color (representing the color of the yaw angle of the corresponding marking point of the streamline contour map at the next moment), which can show the changing rule.

[0087] The second aspect of this embodiment will be described in detail for the wind tunnel flow field display inversion calculation device 500. Figure 11 The module diagram of the wind tunnel flow field display inversion calculation device 500 of this embodiment is shown.

[0088] As Figure 11 shown, the wind tunnel flow field display inversion calculation device 500 of this embodiment is used to implement the aforementioned wind tunnel flow field display inversion calculation method. The wind tunnel flow field display inversion calculation device 500 may include a generation module 510, a timing module 520, a drawing module 530, and a synthesis module 540. Further, the generation module 510, the timing module 520, the drawing module 530, and the synthesis module 540 may be electrically connected to each other.

[0089] The generation module 510 is used to obtain a fluorescence image and generate a streamline contour map according to the fluorescence image. The timing module 520 is used to respectively configure the streamline contour maps at different times at corresponding positions on the time axis to obtain a plurality of timing diagrams. The drawing module 530 is used to select marking points and draw different marking lines along the time axis at the positions of the marking points in the plurality of timing diagrams according to the change relationship between the yaw angle of the marking points and time to obtain a plurality of three-dimensional images. The synthesis module 540 is used to sequentially show the plurality of three-dimensional images in time sequence and synthesize them into a three-dimensional video.

[0090] The third aspect of this embodiment will be described in detail for the readable storage medium.

[0091] The readable storage medium of this embodiment stores a program or instructions. When the program or instructions are executed by a processor, the steps of the wind tunnel flow field display inversion calculation method of any one of the technical solutions in this embodiment are implemented. For the implementation of each of the above operations, reference can be made to the foregoing method embodiments, which will not be elaborated herein.

[0092] A readable storage medium can be an electronic memory such as a flash memory, an electrically erasable programmable read only memory (EEPROM), an erasable programmable read only memory (EPROM), a hard disk, or a ROM. Optionally, the readable storage medium may include a non-transitory computer-readable storage medium. The computer-readable storage medium has a storage space for program codes for performing any of the method steps in the above methods. These computer program codes can be read from or written into one or more computer program products. The computer program codes can be compressed in a suitable form, for example.

[0093] In some other cases, the present embodiment can also provide an electronic device 600, as Figure 12 shown. The electronic device 600 includes a memory 620 and a processor 610, and the memory 620 is connected to the processor 610. The memory 620 stores a program or instructions that can run on the processor 610. When the program or instructions are executed by the processor 610, the steps of the wind tunnel flow field display inversion calculation method of any of the technical solutions in the present embodiment are implemented. The memory 620 can exist independently or be integrated with the processor 610.

[0094] The memory 620 can include a random access memory 620 (RAM), and can also include a read-only memory 620 (ROM). The memory 620 can be used to store instructions, programs, codes, code sets, or instruction sets. The memory 620 can include a program storage area and a data storage area. Among them, the program storage area can store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above various method embodiments, etc. The data storage area can also store data created during the use of the electronic device 600 (such as audio and video data, chat record data), etc.

[0095] The processor 610 may include one or more processing cores. The processor 610 can be connected to various parts within the entire electronic device 600 through various interfaces and circuits. It can execute various functions of the electronic device 600 and process data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 620, and by calling the data stored in the memory 620. Optionally, the processor 610 can be implemented in at least one hardware form of digital signal processing (DSP), field programmable gate array (FPGA), or programmable logic array (PLA). The processor 610 can integrate a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for the rendering and drawing of display content; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 610 and can be implemented separately through a communication chip.

[0096] When the programs or instructions stored in the memory 620 are executed, the processor 610 can be used to perform various operations in the above method embodiments to implement the steps of the wind tunnel flow field display inversion calculation method of any one of the technical solutions in this embodiment. The specific implementation of these operations can be referred to the previous method embodiments and will not be elaborated here.

[0097] It should be noted that in this article, the term "including", "comprising", or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article, or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such a process, method, article, or device. Without more limitations, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article, or device including that element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the reverse order according to the functions involved. For example, the described methods can be executed in an order different from that described, and various steps can be added, omitted, or combined. Additionally, the features described with reference to certain examples can be combined in other examples.

[0098] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention.

Claims

1. A wind tunnel flow field display inversion calculation method, characterized in that: include: Acquiring a fluorescent image, and generating a streamline contour map based on the fluorescent image; Arrange the streamline contour diagrams at multiple different moments at corresponding positions on the time axis to obtain multiple time sequence diagrams; Selecting a marking point, and drawing different marking lines along the time axis at the positions of the marking points in the plurality of timing diagrams according to the relationship between the yaw angle of the marking point and time, to obtain a plurality of three-dimensional images; The plurality of three-dimensional images are sequentially displayed in time sequence and synthesized into a three-dimensional video.

2. The wind tunnel flow field display inversion calculation method according to claim 1 is characterized in that: The step of acquiring a fluorescent image and converting the fluorescent image into a streamline contour map includes: Acquire a fluorescent image and select a reference direction; Comparing a plurality of fluorescent filaments in the fluorescent image with the reference direction to obtain a plurality of yaw angles; The streamline contour map is generated according to the fluorescent image and the yaw angle.

3. The wind tunnel flow field display inversion calculation method according to claim 2 is characterized in that: Before comparing the plurality of fluorescent threads in the fluorescent image with the reference direction, the method further includes: Acquire a fluorescence video, and decompose the fluorescence video into a plurality of single-frame fluorescence images; The fluorescent image is sequentially subjected to grayscale processing, Gaussian filtering processing, adaptive binarization processing, connected region detection, and region extraction to obtain image information of the fluorescent thread.

4. The wind tunnel flow field display inversion calculation method according to claim 3 is characterized in that: The comparing the multiple fluorescent wires in the fluorescent image with the reference direction to obtain multiple yaw angles includes: According to the image information of the plurality of fluorescent threads, the image information is compared with the reference direction to obtain the yaw angles of the plurality of fluorescent threads.

5. The wind tunnel flow field display inversion calculation method according to claim 3 is characterized in that: The step of generating the streamline contour map according to the fluorescent image and the yaw angle comprises: generating a streamline diagram according to the image information of the plurality of fluorescent threads; generating a contour map according to the yaw angles of the plurality of fluorescent threads; The streamline diagram and the contour diagram at the same time are fitted to each other to form the streamline contour diagram.

6. The wind tunnel flow field display inversion calculation method according to claim 1, characterized in that: The selecting of the marking point, and drawing different marking lines along the time axis at the positions of the marking points of the plurality of timing diagrams according to the relationship between the yaw angle of the marking point and time, comprises: Selecting the positions of at least a portion of the fluorescent threads in the fluorescent image as the marking points; Obtaining the yaw angles of the marked points in the plurality of timing diagrams; According to the relationship between the yaw angle of the marking point and time, a straight line is drawn along the direction of the time axis at the positions of the marking points of the plurality of timing diagrams as a marking line; The marking information of the marking line is configured as the yaw angle of the corresponding marking point of the streamline contour map at the previous moment.

7. The wind tunnel flow field display inversion calculation method according to claim 6 is characterized in that: The marking information of the marking line includes line color.

8. The wind tunnel flow field display inversion calculation method according to claim 1 is characterized in that: When the three-dimensional video shows one of the streamline contour maps at multiple different moments, the three-dimensional video correspondingly shows the wind speed, the position and posture of the object to be detected, and the time information at the same moment.

9. A wind tunnel flow field display inversion calculation device, characterized in that: The method for calculating the inversion of the wind tunnel flow field display according to any one of claims 1 to 8 is used to implement the inversion calculation method of the wind tunnel flow field display according to any one of claims 1 to 8, wherein the wind tunnel flow field display inversion calculation device comprises: A generating module, used for acquiring a fluorescent image and generating a streamline contour map according to the fluorescent image; A timing module, used for respectively configuring the streamline contour diagrams at multiple different moments at corresponding positions on the time axis to obtain multiple timing diagrams; A drawing module, used for selecting a marking point, and drawing different marking lines along the time axis at the positions of the marking points of the plurality of timing diagrams according to the relationship between the yaw angle of the marking point and time, so as to obtain a plurality of three-dimensional images; And a synthesis module is used to display the multiple three-dimensional images in sequence along the time sequence and synthesize them into a three-dimensional video.

10. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by a processor, the wind tunnel flow field display inversion calculation method according to any one of claims 1 to 8 is implemented.

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