A wind tunnel flow field display inversion calculation method, device and readable storage medium

Abstract

The present invention discloses a method, device and readable storage medium for inverse calculation of wind tunnel flow field display, which relates to the technical field of wind tunnel measurement. The method for inverse calculation of wind tunnel flow field display includes obtaining a fluorescence image and generating a streamline contour map based on the fluorescence image; arranging the streamline contour maps at different times at corresponding positions on the time axis respectively to obtain a plurality of time series diagrams; selecting a marked point, and drawing different marked lines along the time axis at the position of the marked point in a plurality of time series diagrams according to the variation relationship between the yaw angle of the marked point and time to obtain a plurality of three-dimensional images; showing the plurality of three-dimensional images in sequence along the time order and synthesizing them into a three-dimensional video. The three-dimensional 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. Marked lines are drawn along the time axis, which can highlight the change of the surface flow field of the marked point and can more clearly indicate the flow field situation in the position area where the marked point is located.

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 of the model surface, the fluorescent wire flow display technology is adopted. In the past, in wind tunnel experiments, the fluorescent wire technology was to take pictures of the wire 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 wire is located by the naked eye. This is inefficient, inaccurate, prone to misjudgment, and unable to display the change of the fluid on the surface of the object, 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:

[0005] The first aspect of the present invention provides a wind tunnel flow field display inversion calculation method.

[0006] The wind tunnel flow field display inversion calculation method of the present invention includes the following steps:

[0007] Obtain a fluorescent image, and generate a streamline contour map according to the fluorescent image;

[0008] Configure the streamline contour maps at different times at corresponding positions on the time axis respectively to obtain a plurality of time series diagrams;

[0009] 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 change relationship between the yaw angle of the marking point and time to obtain a plurality of three-dimensional images;

[0010] Show the plurality of three-dimensional images in sequence along the time order and synthesize them into a three-dimensional video.

[0011] The second aspect of the present invention provides a wind tunnel flow field display inversion calculation device.

[0012] 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:

[0013] A generation module, configured to obtain a fluorescence image and generate a streamline isogram based on the fluorescence image;

[0014] A timing module, configured to respectively configure streamline isograms at different times at corresponding positions on the time axis to obtain a plurality of timing diagrams;

[0015] 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 a plurality of timing diagrams according to the variation relationship between the yaw angle of the marked points and time to obtain a plurality of three-dimensional images; and

[0016] A synthesis module, configured to sequentially show a plurality of three-dimensional images in chronological order and synthesize them into a three-dimensional video.

[0017] The third aspect of the present invention provides a readable storage medium.

[0018] 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 of any one of the technical solutions in the present invention are implemented.

[0019] The technical solution adopted by the present invention can achieve the following beneficial effects: A streamline isogram is generated through a fluorescence image, and the streamline isogram records information such as the path, direction, and yaw angle of the airflow. By configuring the streamline isogram at the corresponding position on the time axis, a plurality of timing diagrams are obtained, which is beneficial to understanding and analyzing the change of the surface flow field over time. The three-dimensional video can adjust the playback order, adjust the viewing angle, zoom ratio, or select a specific streamline area, and the three-dimensional 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 three-dimensional video, marked lines are drawn along the time axis, which can highlight the change 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, has high accuracy, and avoids situations such as misjudgment. Description of the Drawings

[0020] 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.

[0021] Figure 1 is a flowchart of the wind tunnel flow field display inversion calculation method shown in an exemplary embodiment of the present application;

[0022] Figure 2 is a schematic diagram of the fluorescence image shown in an exemplary embodiment of the present application;

[0023] Figure 3 For Figure 2 the enlarged view at position a in

[0024] Figure 4 It is a schematic diagram of a streamline isogram shown in an exemplary embodiment of the present application;

[0025] Figure 5 It is a schematic diagram of a timing diagram shown in an exemplary embodiment of the present application;

[0026] Figure 6 It is a schematic diagram of another timing diagram shown in an exemplary embodiment of the present application;

[0027] Figure 7 It is a schematic diagram of a timing diagram at another moment shown in an exemplary embodiment of the present application;

[0028] Figure 8 It is a processing flow chart of a fluorescence image shown in an exemplary embodiment of the present application;

[0029] Figure 9 It is a schematic diagram of a streamline shown in an exemplary embodiment of the present application;

[0030] Figure 10 It is a schematic diagram of an isogram shown in an exemplary embodiment of the present application;

[0031] Figure 11 It is a schematic structural diagram of a wind tunnel flow field display inversion calculation device shown in an exemplary embodiment of the present application;

[0032] Figure 12 It is a schematic structural diagram of an electronic device shown in an exemplary embodiment of the present application.

[0033] In the figure: 500, wind tunnel flow field display inversion calculation device; 510, generation module; 520, timing module; 530, drawing module; 540, synthesis module; 600, electronic device; 610, processor; 620, memory. Detailed implementation manners

[0034] 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 of the embodiments. All other implementation manners obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope protected by the present invention.

[0035] The terms "first", "second", etc. in the description and claims of this application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such data used can be interchanged under appropriate circumstances, so that the embodiments of this application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same category, and the number of objects is not limited. For example, the first object can be one or multiple. In addition, "and / or" in the description 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.

[0036] 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. Specifically, by treating thin and soft fibers (such as nylon filaments) with fluorescent dyes and then pasting them on the surface or grid of the object to be detected to be observed, these fluorescent silk threads will emit bright fluorescence under the irradiation of ultraviolet light. Since the silk threads are very thin and have little influence on the fluid flow, they can accurately reflect the fluid flow situation. The fluorescent silk thread flow display technology can visually observe the fluid flow situation around the current object to be detected, but it is difficult to intuitively know the subsequent fluid changes, and it is even more impossible to quantify and visually present them, resulting in the adaptation range of the fluorescent silk thread flow display technology being too limited, 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 experiment.

[0037] The first aspect of this embodiment will elaborate on the wind tunnel flow field display inversion calculation method in detail.

[0038] Figure 1 The flowchart of the wind tunnel flow field display inversion calculation method of this embodiment is shown. As Figure 1 shown, the wind tunnel flow field display inversion calculation method of this embodiment includes the following steps:

[0039] Step S100: Obtain a fluorescent image and generate a streamline contour map according to the fluorescent image.

[0040] 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 silk threads on the surface of the object to be detected, and the pose of specific fluorescent silk threads, 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 are the fluorescent silk threads. Figure 3 is Figure 2 the enlarged view at a in, Figure 3The value on each fluorescent filament represents the corresponding yaw angle value of the fluorescent filament. Among them, the object to be detected includes, but is not limited to, aircraft, automobiles, or their model structures, etc., and is not restricted here.

[0041] Generate a streamline contour map based on the fluorescent image. Figure 4 The streamline contour map is shown, Figure 4 The x-axis and y-axis of which represent the spatial horizontal and vertical coordinates of the data points of the streamline contour map, with the unit of millimeter (mm), Figure 4 The different colors in it represent the angles of different yaw angles, with the unit of degree (°). Figure 4 It records the surrounding fluid and flow field conditions of the object to be detected. The fluorescent image records the distribution and pose of multiple fluorescent filaments, etc., and based on the distribution and pose of multiple fluorescent filaments, etc., a streamline contour map can be generated. The streamline contour map is about the yaw angle condition of the object to be detected, where the yaw angle refers to the direction in which the flow direction of the fluid at that place deviates from the ground or a specified direction.

[0042] The streamline contour map records 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. Moreover, the streamline contour map also records 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 influence of the airflow during its flight, thereby helping engineers optimize the design of the object to be detected, reduce the resistance during driving, and improve the driving efficiency and stability.

[0043] Step S200: Arrange the streamline contour maps at different times at the corresponding positions on the time axis to obtain multiple time series diagrams.

[0044] The streamline contour maps at multiple different times are converted from the fluorescent images at multiple different times through the above method. Therefore, the streamline contour map represents the surrounding flow field conditions of the object to be detected and the yaw angle distribution of the fluid at the corresponding time.

[0045] Arrange the streamline contour maps at different times at the corresponding positions on the time axis to obtain multiple time series diagrams. Please refer to Figure 5 This means arranging the streamline contour map at the corresponding position on the time axis. Figure 5 The z-axis and y-axis of which represent the spatial coordinate positions of the data points of the streamline contour map, with the unit of millimeter (mm), Figure 5 The x-axis (i.e., the time axis) in it represents the corresponding time of the streamline contour map, with the unit of millisecond (ms), Figure 5 The different colors in it represent the angles of different yaw angles, with the unit of degree (°). For example, as Figure 5As shown, taking the initial moment as the timing point, a streamline contour map records the flow field situation around the object to be detected at 400 ms and the yaw angle distribution of the fluid. Therefore, by configuring this streamline contour map at the 400 ms position on the time axis, the corresponding time series diagram can be obtained.

[0046] It can be understood that the intervals between fluorescence images at multiple different times can be the same or different, which will cause the streamline contour maps at multiple different times to be arranged evenly or unevenly on the time axis, and no restrictions are imposed here. During a certain period of time, the yaw angle of the fluid may change greatly and the change of the flow field is too drastic. Therefore, more fluorescence images are set in this period of time to facilitate the observation of the changes of the fluid and the flow process.

[0047] Converting the streamline contour maps at multiple different times into multiple time series diagrams will make the streamline contour maps correspond to the time sequence, which can facilitate engineers to understand and analyze the changes of the fluid and the flow process over time and improve the observability.

[0048] It can be understood 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 achieve the observation of the flow field state at different times from different angles.

[0049] In some other cases, such as Figure 6 shown, Figure 6 the z-axis and y-axis of [] represent the spatial coordinate positions of the data points of the streamline contour map, with the unit of millimeter (mm), Figure 6 the x-axis (i.e., the time axis) in [] represents the corresponding times of multiple streamline contour maps, with the unit of millisecond (ms). Multiple streamline contour maps at different times can also be synthesized 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.

[0050] Step S300: 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 change relationship between the yaw angle of the marked points and time to obtain multiple three-dimensional images.

[0051] Select marked points. The marked points can be selected by the tester through presetting or manual input, etc., without restrictions. Moreover, the selection of the marked points can be affected by the specific object to be detected and the wind speed, etc., to ensure that more critical positions can be selected, such as areas with more obvious flow field changes, areas of this improvement, or areas with faults in the previous test, etc.

[0052] According to the relationship between the yaw angle of the marked points and time, different marked lines are drawn along the time axis at the positions of the marked points in multiple time sequence diagrams, obtaining multiple three-dimensional images. At the same marked point, the flow field near the marked point may change with time. According to the relationship between the yaw angle and time, different marked lines are drawn along the time axis. Multiple marked lines can be drawn at the multiple marked points of each time sequence diagram, and the multiple marked lines are as shown by the multiple straight lines with arrows of different colors in Figure 5 The marked lines change according to the specific parameters of the yaw angle, such as their thickness, color, arrow, or a combination of multiple ones. This can highlight the change of the surface flow field of the marked points, and it can more clearly show the flow field situation in the area where the marked points are located, with high accuracy and avoid situations such as misjudgment.

[0053] Step S400: Show the multiple three-dimensional images in sequence along the time order and synthesize them into a three-dimensional video.

[0054] The three-dimensional images are shown in sequence along the time order and synthesized into a three-dimensional video. For example, as shown by Figure 5 and Figure 7 The three-dimensional video can show the three-dimensional images in sequence. Further, the time axes of the multiple three-dimensional images are aligned 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 contour map in the three-dimensional image, and the positions of the multiple sequentially shown streamline contour maps also change with the time axis, that is, gradually move farther or closer. Exemplarily, the multiple three-dimensional images are the three-dimensional images at 0, 500 ms, and 1000 ms respectively. According to the time 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 contour map and the flow field change law, etc.

[0055] In addition, the three-dimensional video can be paused or started, the playing order can be adjusted (in the forward or reverse order along the time), 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.

[0056] Preferably, 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 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 movement 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.

[0057] The wind tunnel flow field display inversion calculation method of the preferred technical solution of this embodiment generates streamline contour maps through fluorescent 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, 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 flow field change law, 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 marking point, and can more clearly mark the flow field situation of the position area where the marking point is located, with high accuracy and avoiding misjudgment and other situations.

[0058] According to an optional embodiment, step S100: Obtain a fluorescent image and convert it into a streamline contour map according to the fluorescent image, which at least includes the following steps:

[0059] Step S110: Obtain a fluorescent image and select a reference direction.

[0060] 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 filaments on the surface of the object to be detected, and the pose of specific fluorescent filaments, etc., which are not limited here.

[0061] 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.

[0062] 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.

[0063] Step S120: Compare multiple fluorescent filaments in the fluorescent image with the reference direction to obtain multiple yaw angles.

[0064] Under the influence of the fluid, multiple fluorescent filaments in the fluorescent 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.

[0065] 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 multiple fluorescent filaments, compare the image information with the reference direction to obtain the yaw angles of 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.

[0066] Step S130: Generate a streamline contour map according to the fluorescence image and the yaw angle.

[0067] 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 area 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 the streamline map and the contour map, that is, it shows the flow path in the flow field of the area where the fluorescent line is located. In the streamline contour map, different contour lines represent different yaw angle values, and the density and direction of the contour lines reflect the changes in the velocity and direction of fluid flow.

[0068] 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:

[0069] Step S141: Obtain a fluorescence video and decompose the fluorescence video into multiple single-frame fluorescence images;

[0070] Obtain a fluorescence video, which 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.

[0071] 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.

[0072] 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.

[0073] 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 8The processing flow chart of the fluorescence image is shown.

[0074] The fluorescence image is grayscale processed. By converting the RGB color image in the fluorescence image into a grayscale image. Exemplarily, the acquired fluorescence image captured by the camera module is an RGB color image. First, the color fluorescent filaments in the fluorescence image are grayscale processed, and the R, G, and B channel images are grayscale processed into a single-channel image to remove redundant information in the image, reduce the occupation of computing resources, and improve the processing efficiency.

[0075] Furthermore, the fluorescence image is Gaussian filtered. 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 grayscale processed, the grayscale processed image is Gaussian filtered. The equation of the two-dimensional Gaussian function is shown as follows:

[0076]

[0077] 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 functions 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 achieved by performing 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.

[0078] Furthermore, the fluorescence image is adaptively binarized. The adaptively binarized algorithm is used to further process the grayscale 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.

[0079] Connected region detection is performed on the fluorescence image. Connected region detection is performed on the obtained binarized image to identify all independent edge regions, providing a basis for subsequent extraction and linear fitting of fluorescent filaments.

[0080] Region extraction is performed 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, the range value that can include all the connected regions of the fluorescent filaments is found, and the specific parameters of the fluorescent filaments are extracted from the detected connected regions accordingly.

[0081] 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.

[0082] 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:

[0083] Assume that the two-dimensional data point set in the fluorescent thread area to be fitted is:

[0084] (N is greater than or equal to 1)

[0085] 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:

[0086]

[0087] 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.

[0088] Decomposition of matrix A by SVD:

[0089]

[0090] Where: U is The orthogonal matrix, whose column vectors are called left singular vectors;

[0091] ∑ is a diagonal matrix, the elements on the diagonal are non - negative real numbers, called singular values, and arranged in descending order;

[0092] V is an orthogonal matrix, whose column vectors are called right singular vectors.

[0093] Substitute denoted as q into the optimization problem, and the following process can be obtained:

[0094]

[0095] Since U is an orthogonal matrix, the norm remains unchanged.

[0096] To minimize , and = 1, select such that corresponds to the minimum singular value of ∑.

[0097] Therefore, the optimal solution is the last column of V, that is, the right singular vector corresponding to the minimum singular value.

[0098] After obtaining the optimal solution , the best straight line fitted from the fluorescent silk thread region can be obtained .

[0099] Use SVD to solve the best - fitting straight line for each fluorescent silk thread region, and mark each fitted straight line in the region where the original fluorescent silk thread is located. This can reduce the influence of other factors, etc., ensure the accuracy of the specific parameters of the fluorescent silk thread, such as its position, attitude, etc., and further improve the calculation accuracy of subsequent yaw angles, etc.

[0100] According to an optional implementation manner, step S130: Generate a streamline contour map based on the fluorescence image and the yaw angle, including:

[0101] Step S131: Generate a streamline map according to the image information of multiple fluorescent silk threads.

[0102] Specifically, as Figure 9 shown, Figure 9The x-axis and y-axis represent the spatial horizontal and vertical coordinates of the data points in the streamline plot, with the unit being millimeters (mm). The straight line where the fluorescent filament is located is converted into a vector, and this vector represents the flow field direction at the corresponding position of the fluorescent filament. Moreover, the streamline plot is drawn using the streamslice function in MATLAB to show the flow pattern and direction change of the flow field at the position where the fluorescent filament is located.

[0103] The calling format of the streamslice function is streamslice(x, y, u_combined, v_combined)

[0104] Among them, x and y are two-dimensional grid coordinate matrices generated based on the fluorescent filaments in the fluorescent image, which define the coordinate positions of each point within the streamline plot drawing area. Among them, these matrices are generated by 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 filament at each grid point (x, y). Specifically, u_combined represents the horizontal direction component, and v_combined represents the vertical direction component.

[0105] 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 drawn streamline segments to ensure that the streamlines start to be drawn from the key areas of the flow field.

[0106] 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.

[0107] Since the vector data fitted by the fluorescent filaments is often sparse and cannot be directly used to draw a continuous streamline plot, the griddata function is used in this application 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 some 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.

[0108] Step S132: Generate a contour plot according to the yaw angles of multiple fluorescent filaments.

[0109] As Figure 10 shownFigure 10 The x-axis and y-axis represent the spatial horizontal and vertical coordinates of the data points of the isogram, with the unit of millimeters (mm). Figure 10 The different colors in it represent the angles of different yaw angles, with the unit of degrees (°). Based on the calculated yaw angles of the fluorescent filaments, the contourf function in Matlab is used to draw the contour map. The contourf function is used to create a filled contour map and can be very effectively used to visualize the contour regions of two-dimensional data. The contourf function will perform contour calculation, color filling, and color mapping in sequence.

[0110] The contourf function will find a series of contour lines within the specified area range according to the yaw angles of the vectors represented by each fluorescent filament, and these contour lines connect the points with the same deviation angle.

[0111] 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, and it can intuitively show the angle distribution between the fluorescent filaments and the flow field direction.

[0112] Among them, it is represented using the current color map according to the yaw angle of the fluorescent filament. The color map 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.

[0113] Step S133: Fit the streamline map and the contour map at the same moment to form a streamline contour map.

[0114] As Figure 4 shown, the streamline map and the contour map are correspondingly set. The streamline map is fitted on the contour map to form a streamline contour map. Exemplarily, the streamlines of the streamline map are retained, and the transparency of the remaining part is increased. After fitting the processed streamline map to the contour map, where the layer of the streamline map is located on the layer of the contour map so that the streamline map can be clearly obtained. This can obtain a clearer streamline contour map.

[0115] According to an optional implementation manner, 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 change relationship between the yaw angle of the marking points and time, including:

[0116] Step S310: Select the positions where at least part of the fluorescent filaments are located as the marking points.

[0117] Select the position of at least part of the fluorescent filaments as the marking points. The number of fluorescent filaments is multiple. Select some or all of the fluorescent filaments as the marking points. The change state of the fluorescent filaments and the change law of the yaw angle are both known. To improve the visualization degree of its change law, select them as the marking points.

[0118] 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 the marking points later and improving the automation degree. Or, the tester can also manually input or select the specific positions of the marked fluorescent filaments.

[0119] In some other cases, the marking points can be manually selected by the tester and are not the positions of the fluorescent filaments. The specific selection requirements of the marking points will be affected by debugging requirements and the like.

[0120] Step S320: Obtain the yaw angles of the marking points in multiple time series diagrams.

[0121] Obtain the yaw angles of the marking points in multiple time series diagrams. According to the positions of the marking 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 isogram, that is, detect the color at the corresponding position of the isogram for detection and judgment. However, when the marking points are selected as the positions of the fluorescent filaments, the yaw angles of the fluorescent filaments have been recorded, and just obtain the corresponding yaw angles of the corresponding fluorescent filaments, which can simplify the acquisition steps and improve the detection efficiency.

[0122] Step S330: Draw marking lines along the time axis at the positions of the marking points in multiple time series diagrams according to the change relationship between the yaw angle of the marking points and time.

[0123] Draw different marking lines along the time axis at the positions of the marking points in multiple time series diagrams according to the change relationship between the yaw angle of the marking points and time. As Figure 5 shown, at the same marking point, the flow field near the marking point may change with time. Draw different marking lines along the time axis according to the change relationship between the yaw angle and time. Marking lines can be drawn at multiple marking points of each time series diagram, and the marking lines change with 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 marking points, and it can more clearly mark the flow spectrum situation in the area where the marking points are located, with high accuracy and avoiding situations such as misjudgment.

[0124] Step S340: Configure the marking information of the marking lines as the yaw angle of the corresponding marking point of the streamline isogram at the previous moment.

[0125] The marking information of the marking line is configured as the yaw angle of the corresponding marking point of the streamline isoline map at the previous moment. When the marking line is drawn, the information carried by the marking line drawn at a certain moment is the yaw angle situation of the corresponding marking point in the streamline isoline map of the previous moment. The purpose of doing this is to clearly present the changing 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 moments and the change of the object's attitude in the airflow. Among them, the marking information is intuitively shown by the marking line, and the marking information can be intuitively obtained by users such as engineers. The marking line can be configured so that the marking information of the marking line can include the line color.

[0126] Among them, the color of the marking line shows the corresponding yaw angle information, and the color of the streamline isoline map shows the corresponding yaw angle information. The color of the marking line can be set corresponding to the color of the isoline map area, which can reduce color errors and interference and is convenient for users to understand and observe.

[0127] 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 ranges from the first color (the color representing the yaw angle of the corresponding marking point of the streamline isoline map at the previous moment) to the second color (the color representing the yaw angle of the corresponding marking point of the streamline isoline map at the next moment), which can show the changing rule.

[0128] The second aspect of this embodiment will elaborate on the wind tunnel flow field display inversion calculation device 500. Figure 11 The block diagram of the wind tunnel flow field display inversion calculation device 500 of this embodiment is shown.

[0129] 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.

[0130] The generation module 510 is used to obtain a fluorescence image and generate a streamline isoline map according to the fluorescence image. The timing module 520 is used to respectively configure the streamline isoline maps at multiple different moments at corresponding positions on the time axis to obtain multiple 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 multiple timing diagrams according to the change relationship between the yaw angle of the marking points and time to obtain multiple three-dimensional images. The synthesis module 540 is used to sequentially show the multiple three-dimensional images in time order and synthesize them into a three-dimensional video.

[0131] The third aspect of this embodiment will be described in detail for the readable storage medium.

[0132] For the readable storage medium of this embodiment, a program or instruction is stored on the readable storage medium, and when the program or instruction is 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 may be made to the foregoing method embodiments, which will not be elaborated herein.

[0133] The readable storage medium may 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 executing any of the method steps in the above method. These computer program codes may be read from or written into one or more computer program products. The computer program codes may be compressed in a suitable form, for example.

[0134] In some other cases, this embodiment may 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 and the processor 610 are connected. The memory 620 stores a program or instruction that can run on the processor 610, and when the program or instruction is executed by the processor 610, the steps of the wind tunnel flow field display inversion calculation method of any one of the technical solutions in this embodiment are implemented. The memory 620 may exist independently or be integrated with the processor 610.

[0135] The memory 620 may include a random access memory (RAM), and may also include a read-only memory (ROM). The memory 620 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 620 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for implementing at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc. The data storage area may also store data created during the use of the electronic device 600 (such as audio and video data, chat record data), etc.

[0136] The processor 610 may include one or more processing cores. The processor 610 can connect various parts within the entire electronic device 600 through various interfaces and lines. By running or executing instructions, programs, code sets or instruction sets stored in the memory 620, and by calling data stored in the memory 620, the processor 610 can execute various functions of the electronic device 600 and process data. Optionally, the processor 610 can be implemented in at least one hardware form of digital signal processing (DSP), field programmable gate array (FPGA), 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 the displayed 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.

[0137] 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-mentioned 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.

[0138] It should be noted that in this text, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising such 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 a reverse order according to the functions involved. For example, the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0139] As described above, the above are only specific embodiments 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, Including: Obtain a fluorescence image and select a reference direction; Compare multiple fluorescent filaments in the fluorescence image with the reference direction to obtain multiple yaw angles; Generate a streamline diagram according to the image information of multiple fluorescent filaments; Generate an isogram according to the yaw angles of multiple fluorescent filaments; Fit the streamline diagram and the isogram at the same moment to form a streamline isogram; Arrange the streamline isograms at multiple different moments at corresponding positions on the time axis to obtain multiple time series diagrams; 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 angles of the marked points and time to obtain multiple three-dimensional images; Show multiple three-dimensional images in sequence along the time order and synthesize them into a three-dimensional video.

2. The wind tunnel flow field display inversion calculation method according to claim 1, characterized in that Before comparing multiple fluorescent filaments in the fluorescence image with the reference direction, it further includes: Obtain a fluorescence video and decompose the fluorescence video into multiple single-frame fluorescence images; Perform grayscale processing, Gaussian filtering processing, adaptive binary processing, connected region detection, and region extraction on the fluorescence images in sequence to obtain the image information of the fluorescent filaments.

3. The wind tunnel flow field display inversion calculation method according to claim 2, characterized in that Comparing multiple fluorescent filaments in the fluorescence image with the reference direction to obtain multiple yaw angles includes: According to the image information of multiple fluorescent filaments, compare the image information with the reference direction to obtain the yaw angles of multiple fluorescent filaments.

4. The wind tunnel flow field display inversion calculation method according to claim 1, wherein Selecting marked points and drawing 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 angles of the marked points and time includes: Select the positions where the fluorescent filaments are located in at least part of the fluorescence images as the marked points; Obtain the yaw angles of the marked points in multiple time series diagrams; Draw a straight line as a marked line along the direction of the time axis at the positions of the marked points in multiple time series diagrams according to the variation relationship between the yaw angles of the marked points and time; The marking information of the marked line is configured as the yaw angle of the corresponding marked point in the streamline isogram at the previous moment.

5. The wind tunnel flow field display inversion calculation method according to claim 4, characterized in that The marking information of the marked line includes the line color.

6. The wind tunnel flow field display inversion calculation method according to claim 1, wherein, 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.

7. A wind tunnel flow field display inversion calculation device, characterized in that, For implementing the wind tunnel flow field display inversion calculation method described in any one of claims 1-6, the wind tunnel flow field display inversion calculation device includes: A generation module, configured to obtain a fluorescence image and generate a streamline isogram according to the fluorescence image; A time series module, configured to arrange the streamline isograms at multiple different moments at corresponding positions on the time axis to obtain multiple 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 angles of the marked points and time to obtain multiple three-dimensional images; and A synthesis module, configured to show multiple three-dimensional images in sequence along the time order and synthesize them into a three-dimensional video.

8. A readable storage medium, characterized in that, The program or instruction is stored on the readable storage medium, and when the program or instruction is executed by the processor, the wind tunnel flow field display inversion calculation method described in any one of claims 1 to 6 is implemented.

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