Volumetric particle image velocity measurement method and device

Abstract

The present disclosure proposes a stereoscopic particle image velocity measurement method, including: obtaining the coordinate transformation relationship between the left and right camera coordinate systems and the actual space coordinate system; according to the coordinate transformation relationship, respectively back-projecting the tracer particle images taken by the left and right cameras at the same time onto two reference planes and performing two-dimensional interpolation to obtain projection images; determining multiple position points on the laser plane according to the projection images, and fitting the laser plane according to the multiple position points; reconstructing the three-dimensional velocity components on the laser plane based on the laser plane. The present disclosure calculates the three-dimensional velocity components on the laser plane through the particle images taken by the left and right cameras, and can correct the rotation and translation in any direction between the laser plane and the calibration plate.

Description

Technical Field

[0001] The present disclosure relates to the field of particle image technology, and in particular to a volumetric particle image velocity measurement method and device. Background Art

[0002] Stereoscopic Particle Image Velocimetry (SPIV) uses two cameras to simultaneously record the motion of tracer particles in the same area from two different perspectives, and then reconstructs the three-dimensional velocity components on the laser plane. For SPIV, a very important step is to invert the images taken by the two cameras to the same area in space. Therefore, during calibration, a calibration plate is placed on the laser plane, and two cameras are used to capture images of the calibration plate. The coordinate transformation relationship between the camera coordinate system and the actual space coordinate system, that is, the calibration parameters, is determined based on the projection relationship of the cameras.

[0003] At present, the commonly used calibration methods are straight-line linear calibration method, Tsai calibration method and Zhang plane calibration method. These calibration methods can be used to find the conversion relationship between pixel points and actual spatial positions. If the laser plane completely coincides with the plane where the calibration plate is located, the calibration parameters can be used to directly invert the image onto the laser plane. However, in actual experiments, it cannot be guaranteed that the two planes completely coincide. Directly using the calibration algorithm to invert the image is on the calibration plate plane, not the laser plane. If no correction is made, the calculated three-dimensional velocity field is wrong.

[0004] To correct the problem of misalignment between the calibration plane and the laser plane, the parallax vector method is currently proposed. However, the parallax vector method only considers the displacement and rotation of the calibration plane relative to the laser plane in one direction. In actual experiments, displacement and rotation in the other two directions also exist, and the current parallax vector method cannot correct the errors in the other two directions. Summary of the invention

[0005] The present disclosure proposes a method for measuring particle velocity using a volumetric image, which relates to a method for laser plane correction. The method comprises:

[0006] Obtaining a coordinate transformation relationship between the left and right camera coordinate systems and the actual space coordinate system, wherein the coordinate transformation relationship between the left and right cameras is obtained from images of the calibration plate taken by the left and right cameras respectively;

[0007] According to the coordinate transformation relationship, the tracer particle images taken by the left and right cameras at the same time are respectively back-projected onto two reference planes and two-dimensionally interpolated to obtain projection images, wherein the two reference planes are located within a predetermined range of the laser plane and are parallel to each other;

[0008] Determine a plurality of position points on a laser plane according to the projection image, and fit the laser plane according to the plurality of position points;

[0009] The three-dimensional velocity components on the laser plane are reconstructed based on the laser plane.

[0010] Optionally, the step of back-projecting the tracer particle images captured by the left and right cameras at the same time onto two reference planes respectively according to the coordinate transformation relationship and performing two-dimensional interpolation to obtain projection images includes:

[0011] According to the coordinate transformation relationship, based on the central projection method, all pixel points in the tracer particle images taken by the left and right cameras are back-projected onto the two reference planes respectively to obtain the projection point of each pixel point on the tracer particle image;

[0012] The grayscale values ​​of the projection points on the two reference planes are interpolated respectively by using a bilinear interpolation method to obtain projection images corresponding to the tracer particle images taken by the left and right cameras on the two reference planes.

[0013] Optionally, determining the position point of the laser plane according to the projection image includes:

[0014] Acquire a first grid point on the first reference plane and a second grid point on the second reference plane corresponding to the first grid point according to the coordinate transformation relationship;

[0015] Determine, according to the first grid points and the second grid points, a first position difference and a second position difference of grid points of the tracer particle images captured by the left and right cameras on the two reference planes respectively;

[0016] According to the geometric relationship, a geometric calculation is performed on the first position difference, the second position difference, the first grid point, and the second grid point to determine a position point on the laser plane.

[0017] Optionally, acquiring a first grid point on the first reference plane and a second grid point on the second reference plane corresponding to the first grid point according to the coordinate transformation relationship includes:

[0018] Selecting a reference plane from the two reference planes as a first reference plane;

[0019] Generating first grid points on the first reference plane according to a predetermined pixel area and a predetermined overlap parameter;

[0020] A second grid point corresponding to the first grid point on the second reference plane is determined according to an intersection point between a line connecting a center point of the left camera or the right camera and the first grid point and the second reference plane.

[0021] Optionally, determining the first position difference and the second position difference of the tracer particle images captured by the left and right cameras projected on the two reference planes respectively according to the first grid points and the second grid points includes:

[0022] Using a cross-correlation algorithm, a cross-correlation calculation is performed on an analysis window of a limited area around the images of the left and right cameras near the first grid point to obtain a first position difference between the projections of the tracer particle images taken by the left and right cameras on the first reference plane;

[0023] A cross-correlation algorithm is used to perform cross-correlation calculation on an analysis window of a limited area around the images of the left and right cameras near the second grid point to obtain a second position difference of the tracer particle images taken by the left and right cameras projected on the second reference plane.

[0024] Optionally, reconstructing the three-dimensional velocity component on the laser plane based on the laser plane includes:

[0025] Back-projecting the tracer particle images captured by the left and right cameras onto the laser plane;

[0026] Cross-correlate the projection images of the left and right cameras on the laser plane at the current moment with the projection images of the left and right cameras on the laser plane at the next moment to obtain the velocity field of the real velocity field under the viewing angle of the left and right cameras projected on the laser plane in the direction of the camera normal;

[0027] The three-dimensional velocity component on the laser plane is reconstructed according to the velocity field calculation of the real velocity field under the viewing angles of the left and right cameras projected on the laser plane in the direction of the camera normal.

[0028] Optionally, reconstructing the three-dimensional velocity component on the laser plane according to the velocity field calculation projected on the laser plane in the direction of the camera normal line according to the real velocity field under the viewing angles of the left and right cameras includes:

[0029] The real velocity field under the left and right camera perspectives calculated by the standard cross-correlation algorithm is the velocity field projected on the laser plane with the camera normal direction vector;

[0030] Calculate the three-dimensional velocity vector through the velocity field projected by the left and right cameras and the coordinate transformation relationship;

[0031] The rationality of the calculated velocity field is verified by the consistency of the velocity component in the plane normal direction perpendicular to the left and right camera axes.

[0032] According to a second aspect of the present disclosure, a volumetric particle image velocimetry device is provided, comprising:

[0033] A calibration unit, used to obtain a coordinate transformation relationship between a left and right camera coordinate system and an actual space coordinate system, wherein the left and right camera coordinate transformation relationship is obtained from images of a calibration plate taken by the left and right cameras respectively;

[0034] A back-projection unit, used for back-projecting the tracer particle images taken by the left and right cameras at the same time onto two reference planes according to the transformation relationship and performing two-dimensional interpolation to obtain projection images, wherein the two reference planes are located within a predetermined range of the laser plane and are parallel to each other;

[0035] A determination unit, configured to determine a plurality of position points on a laser plane according to the projection image;

[0036] A fitting unit, used for fitting a laser plane according to the multiple position points;

[0037] A reconstruction unit is used to reconstruct a three-dimensional velocity component on the laser plane based on the laser plane.

[0038] According to a third aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method of the first aspect or the second aspect mentioned above.

[0039] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable a computer to execute the method of the aforementioned first aspect or second aspect.

[0040] According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the computer program implements the method of the first aspect or the second aspect.

[0041] According to an embodiment of the present disclosure, two mutually parallel reference planes are selected within a predetermined range of the laser plane, and the tracer particle images taken by the left and right cameras at the same time are respectively back-projected onto the two reference planes according to the transformation relationship to obtain projection images, and the position of the laser plane is determined according to the projection image, and the laser plane is fitted, and the three-dimensional velocity components on the laser plane are reconstructed based on the laser plane. The determination of the laser plane in the present disclosure can correct the rotation and translation of the laser plane and the calibration plane in any direction. And the determination of the laser plane can be determined by the tracer particle images taken by the left and right cameras, without adding additional experimental data, so that the experimental efficiency is higher.

[0042] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0044] Figure 1 A flow chart of a volumetric particle image velocimetry method provided in an embodiment of the present disclosure;

[0045] Figure 2 A schematic flow chart of a method for back-projecting the tracer particle images taken by the left and right cameras at the same time onto two reference planes to obtain projection images according to the transformation relationship provided in an embodiment of the present disclosure;

[0046] Figure 3 A schematic diagram of a SPIV laser plane self-calibration method provided in an embodiment of the present disclosure;

[0047] Figure 4 A schematic flow chart of a method for determining the position of a laser plane according to the projection image provided in an embodiment of the present disclosure;

[0048] Figure 5 A schematic flow chart of a method for reconstructing three-dimensional velocity components on the laser plane based on the laser plane provided in an embodiment of the present disclosure;

[0049] Figure 6 A schematic diagram of reconstructing three-dimensional velocity provided by an embodiment of the present disclosure;

[0050] Figure 7 A schematic structural diagram of a volumetric particle image velocimetry device provided in an embodiment of the present disclosure;

[0051] Figure 8 A schematic block diagram of an exemplary electronic device provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0052] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0053] The volumetric particle image velocimetry method and device according to the embodiments of the present disclosure will be described below with reference to the accompanying drawings.

[0054] Particle Image Velocimetry (PIV) is a method of optical imaging of fluid display. Its main idea is to use laser to illuminate the tracer particles in the flow field, use high-speed camera to record their movement, and combine image processing technology to achieve full-field real-time, transient quantitative measurement, and can simultaneously measure the velocity vectors at multiple spatial points in the flow field. According to whether PIV measures the velocity of a plane fluid on the plane, or the spatial three-dimensional velocity of a fluid in a plane, or the three-dimensional velocity of a fluid in a three-dimensional space, it can be divided into planar PIV (PlanarPIV, 2D2C), stereo PIV (Stereo-PIV, 2D3C) or holographic PIV (Tomo-PIV, 3D3C). The traditional planar PIV technology uses a laser sheet light source with a thickness of about 1 mm to illuminate the tracer particles in the fluid that can follow the movement of the fluid, and uses a single camera to record the positions of two tracer particles separated by a certain time, to achieve two-dimensional velocity measurement on the two-dimensional plane illuminated by the laser (usually expressed as 2D2C).

[0055] Stereoscopic Particle Image Velocimetry (SPIV) uses two cameras to simultaneously record the movement of particles in the same area from two different perspectives, and then reconstructs the 3D velocity components on the laser plane (usually expressed as 2D3C). This includes the velocity component perpendicular to the plane, which is a velocity component that cannot be measured by traditional PIV technology. This 2D3C measurement method can obtain the true three-dimensional velocity of the flow field, so it has broad application prospects in more complex flows.

[0056] For SPIV, a very important step is to invert the images taken by the two cameras to the same area in space. Therefore, during calibration, the calibration plate is placed on the laser plane, and two cameras are used to simultaneously take pictures of the calibration plate. The calibration parameters are determined based on the projection relationship of the cameras. The more commonly used calibration methods are the straight-line linear calibration method, the Tsai calibration method, and the Zhang plane calibration method. These calibration methods can be used to determine the coordinate transformation relationship between the pixel point and the actual spatial position. If the laser plane completely coincides with the plane where the calibration plate is located, the calibration parameters can be used to directly invert the image to the spatial position. However, in actual experiments, it cannot be guaranteed that the two planes completely coincide. The image is directly inverted using the calibration algorithm on the calibration plate plane, not the laser plane. If no correction is made, the calculated three-dimensional velocity field is wrong. Therefore, accurately determining the actual position of the laser plane is of great significance for correcting the error caused by the misalignment of the calibration plate plane and the laser plane during SPIV calibration.

[0057] In order to correct the problem of misalignment between the calibration plane and the laser plane, a disparity vector scheme has been proposed. This method maps the original images taken by the two cameras at the same time onto the calibration plane, and then uses the deviation vector calculated by the cross-correlation algorithm to calculate the position of the laser plane in the three-dimensional space coordinate system. However, the disparity vector scheme only considers the displacement and rotation of the calibration plane in one direction relative to the laser plane. In actual experiments, rotations in the other two directions also exist, so the disparity vector scheme will no longer be applicable.

[0058] In order to solve the above technical problems, the inventors have proposed a method and device for measuring the velocity of volumetric particle images after long-term research. Two parallel reference planes are selected within the predetermined range of the laser plane. According to the transformation relationship, the tracer particle images taken by the left and right cameras at the same time are respectively back-projected onto the two reference planes to obtain projection images. The position of the laser plane is determined according to the projection image, and the laser plane is fitted. The three-dimensional velocity component on the laser plane is reconstructed based on the laser plane, and rotation and translation in any direction can be corrected. In addition, the determination of the laser plane can be determined by the tracer particle images taken by the left and right cameras, without the need to add additional experimental data, making the experimental efficiency higher.

[0059] The volumetric particle image velocimetry method and system proposed in the present disclosure are described in detail below in conjunction with the accompanying drawings.

[0060] Figure 1 The figure is a flow chart of a volumetric particle image velocimetry method provided in an embodiment of the present disclosure. Figure 1 As shown, the method comprises the following steps:

[0061] 101. Obtain a coordinate transformation relationship between a left and right camera coordinate system and an actual space coordinate system, wherein the coordinate transformation relationship between the left and right cameras is obtained from images of a calibration plate taken by the left and right cameras, respectively.

[0062] Before taking images of the calibration plate and tracer particles using the left and right cameras, the laser light source and camera viewing angle need to be adjusted.

[0063] The calibration plate is used to determine the spatial coordinate positions of all cameras. Specifically, the calibration plate is placed so that the plane where the calibration plate is located coincides with the laser plane as much as possible, and the image of the calibration plate is captured by two cameras at the same time. The rotation matrix and translation vector of the two cameras and the actual spatial coordinate space as well as the intrinsic parameters of the camera are calculated using the Tsai method and the captured calibration plate image to determine the coordinate transformation relationship between the images captured by the left and right cameras and the actual spatial position.

[0064] 102. According to the coordinate transformation relationship, the tracer particle images captured by the left and right cameras at the same time are respectively back-projected onto two reference planes and two-dimensionally interpolated to obtain projection images. The two reference planes are located within a predetermined range of the laser plane and are parallel to each other.

[0065] Two reference planes are selected in space, and the tracer particle images taken by the two cameras at the same time are mapped onto the two selected reference planes, and the two reference planes are defined by the origin and the normal direction. The two reference planes are located within the predetermined range of the laser plane as much as possible, and the reference plane and the laser plane generally do not completely overlap.

[0066] 103. Determine a plurality of position points on a laser plane according to the projection image, and fit the laser plane according to the plurality of position points.

[0067] The particles projected by the two cameras onto the same plane have a displacement, and the displacement vectors on the two planes are parallel. The position of the actual tracer particles can be calculated based on the displacement vectors on the two planes, and the laser plane can be fitted using the positions of these tracer particles. Among them, multiple points on the laser plane can be determined based on the projected image, and then the laser plane is fitted using a random sampling consensus algorithm to obtain the position and normal direction of the laser plane.

[0068] 104. Reconstruct three-dimensional velocity components on the laser plane based on the laser plane.

[0069] The tracer particle image taken by the camera is projected onto a regular grid on the laser plane, and then the PIV method is used to calculate the velocity vector at each camera perspective, and finally the three-dimensional velocity field on the laser plane is reconstructed.

[0070] Therefore, according to an embodiment of the present disclosure, two mutually parallel reference planes are selected within a predetermined range of the laser plane, and the tracer particle images taken by the left and right cameras at the same time are respectively back-projected onto the two reference planes according to the coordinate transformation relationship to obtain projection images, and the position of the laser plane is determined according to the projection image, and the laser plane is fitted, and the three-dimensional velocity components on the laser plane are reconstructed based on the laser plane. The determination of the laser plane in the present disclosure can correct the rotation and translation of the laser plane and the calibration plane in any direction. And the determination of the laser plane can be determined by the tracer particle images taken by the left and right cameras, without adding additional experimental data, so that the experimental efficiency is higher.

[0071] Further, in the embodiment of the present disclosure, when the tracer particle images captured by the left and right cameras at the same time are respectively back-projected onto two reference planes according to the coordinate transformation relationship to obtain projection images, the following method may be adopted but is not limited to it: Figure 2 As shown, the method includes:

[0072] 201. According to the coordinate transformation relationship, based on the central projection method, all pixel points in the tracer particle images taken by the left and right cameras are projected onto the two reference planes respectively to obtain the projection point of each pixel point on the tracer particle image.

[0073] Specifically, Figure 3 As shown, Figure 3 Schematic diagram of the PIV laser plane self-calibration method, which includes reference plane 1, reference plane 2, the laser sheet light source (the gray part in the figure), and the left and right cameras. The center points of the left and right cameras are O l ,O r The reference plane 1 and the reference plane 2 are defined by the origin and the normal direction (O1, n1), (O2, n2). When the present disclosure performs projection, the central projection method is used. Figure 3 As shown in the figure, in the measurement area, the tracer particles are illuminated by the laser sheet light source (the gray plane part in the figure). Assuming that Q and P are two tracer particles, they are imaged on the image planes of the left and right cameras through the left and right cameras. The imaging points of point Q in the tracer particle images taken by the left and right cameras are respectively The same is true for point P. l ,* r Denote the variables corresponding to the left and right cameras respectively, and the subscripts *1 and *2 denote the variables corresponding to reference planes 1 and 2 respectively. Mapping onto reference plane 1 is equivalent to finding a straight line The intersection point with reference plane 1. Specifically, the coordinates of the intersection point are obtained through the following projection relationship. The calculation of the coordinates can be achieved by, but not limited to, the following methods, including:

[0074]

[0075] in, yes The coordinates mapped to reference plane 1, is the optical center O of the left camera l The actual space coordinate, X O,1 is the coordinate of the origin O1 of reference plane 1, is the pixel coordinate of the projection of point Q on the left camera. According to the above formula, if the optical center position of the camera is known, any pixel point on the tracer particle image taken by the camera can be projected onto any plane.

[0076] 202. Using a bilinear interpolation method, interpolate the grayscale values ​​of the projection points on the two reference planes to obtain projection images corresponding to the tracer particle images captured by the left and right cameras on the two reference planes.

[0077] Generally speaking, for SPIV, the projection points back-projected from the pixels in the tracer particle image captured by the camera to a certain plane are not regular grid points. Therefore, after the pixels in the tracer particle image captured by the camera are back-projected to a certain reference plane to form projection points, it is necessary to use the bilinear interpolation method to perform bilinear interpolation processing on the projection points on the reference plane to obtain the grayscale values ​​on the regular grid points. This method can be used to project the tracer particle images captured by the left and right cameras onto reference plane 1 and reference plane 2 respectively.

[0078] Furthermore, when determining the multiple position points of the laser plane according to the projection image, the embodiments of the present disclosure may be implemented by, but not limited to, the following methods: Figure 4 As shown, the method includes:

[0079] 301. Acquire a first grid point on a first reference plane and a second grid point on a second reference plane corresponding to the first grid point according to the coordinate transformation relationship.

[0080] 302. Determine, according to the first grid points and the second grid points, a first position difference and a second position difference of grid points of the tracer particle images captured by the left and right cameras on the two reference planes, respectively.

[0081] Since the reference plane and the laser plane do not completely coincide, the projection of the tracer particle images taken by the two cameras at the same time onto the same reference plane has a displacement, and the displacement vectors on the two reference planes are parallel. The actual position of the tracer particles can be calculated based on the displacement on the two reference planes, and the laser plane can be fitted using the positions of these tracer particles.

[0082] In the embodiment of the present disclosure, when determining the first position difference and the second position difference of the tracer particle images captured by the left and right cameras projected on the two reference planes respectively according to the projection image, the method can be implemented in but not limited to the following manner, which includes the following steps:

[0083] 1. Select a reference plane from the two reference planes as the first reference plane.

[0084] In the embodiment of the present disclosure, any reference plane can be selected from the reference planes. Figure 3 As shown, the present disclosure can select reference plane 1 as the first reference plane, without specific limitation, and can also select reference plane 2 as the first reference plane.

[0085] 2. Generate first grid points on the first reference plane according to a predetermined pixel ratio and a predetermined overlap parameter.

[0086] In the embodiments of the present disclosure, the position difference is calculated using a cross-correlation algorithm. When using the cross-correlation algorithm, it is necessary to select an area of ​​a certain size near the grid point as the analysis window. In the embodiments of the present disclosure, when the projection points on the first reference plane are meshed, it can be done at a predetermined pixel ratio, which is consistent with the ratio of the analysis window, such as 128x128. There is no specific limitation, and it can also be other pixel ratios. The overlap parameter here can be consistent with the overlap parameter of the PIV grid division of 0.95, and the specific embodiments of the present disclosure are not limited to this. When implementing the embodiments of the present disclosure, the first position difference can be calculated by back-projecting the images taken by the left and right cameras near the grid points on the first reference plane onto the images of the first reference plane. Figure 3 As shown, the grid point Q is selected through the image point captured by the left camera Its coordinates are Projected coordinates on the first reference plane in is the coordinate of the first grid point, that is, the starting coordinate of the first position difference. The first position difference is calculated by the cross-correlation algorithm.

[0087] 3. Determine a second grid point on the second reference plane corresponding to the first grid point according to an intersection point between a line connecting the center point of the left camera or the right camera and the first grid point and the second reference plane.

[0088] In the embodiment of the present disclosure, the second grid point on the reference plane 2 corresponding to the first grid point is determined by using the line connecting the center of the left camera or the right camera and the first grid point on the reference plane 1. The present disclosure takes the left camera as an example. Figure 3 As shown, the left camera center O l , the projection grid points of the left camera on reference plane 1 Connect the lines and get the rays Intersection point with reference plane 2 The coordinates of the point is the coordinate of the second grid point, that is, the starting coordinate of the second position difference, and the second position difference is calculated by the cross-correlation algorithm

[0089] 4. A cross-correlation algorithm is used to perform cross-correlation calculations on analysis windows of a limited area around the images of the left and right cameras near the first grid point to obtain a first position difference between the tracer particle images taken by the left and right cameras on the first reference plane; and a cross-correlation algorithm is used to perform cross-correlation calculations on analysis windows of a limited area around the images of the left and right cameras near the second grid point to obtain a second position difference between the tracer particle images taken by the left and right cameras on the second reference plane.

[0090] When the cross-correlation algorithm is used, the first position difference of the first grid point in a certain range on the reference plane 1 and the second position difference of the second grid point on the reference plane 2 are calculated with the grid point as the center. The first position difference is: The second position difference is:

[0091] 303. Perform geometric calculation on the first position difference, the second position difference, the first grid point, and the second grid point according to the geometric relationship to determine a position point on the laser plane.

[0092] In the embodiment of the present disclosure, since the two reference planes are selected to be parallel to each other, it is easy to prove that the two intersecting rays and The intersection lines Δ1 and Δ2 with the two reference planes are also parallel. Figure 3 The triangle Q in With triangle Q, are similar triangles, if we know and position difference Two intersecting rays are calculated based on the geometric relationship and The intersection coordinates X Q The coordinate calculation method can be implemented by but not limited to the following method, which includes:

[0093]

[0094] Among them, α is the proportionality coefficient

[0095]

[0096] Represents the vector of the projection point of point Q on reference plane 1 and the projection point on reference plane 2.

[0097] In the embodiments of the present disclosure, the above method can be used to determine multiple position points on the laser plane, and the specific execution steps of other points will not be repeated in the embodiments of the present disclosure.

[0098] Further, in the embodiment of the present disclosure, when reconstructing the three-dimensional velocity component on the laser plane based on the laser plane, as follows Figure 5 As shown, the following method may be used but is not limited to implement the method, which includes:

[0099] 401. Back-project the tracer particle images captured by the left and right cameras onto the laser plane.

[0100] In the embodiment of the present disclosure, the tracer particle images of the left and right cameras are projected onto the laser plane by, but not limited to, Figure 2 The specific method described in steps 201-202 will not be repeated here in the embodiment of the present disclosure.

[0101] 402. Cross-correlate the projection images of the left and right cameras on the laser plane at the current moment with the projection images of the left and right cameras on the laser plane at the next moment to obtain the velocity field of the real velocity field under the viewing angle of the left and right cameras projected on the laser plane in the direction of the camera normal.

[0102] Specific as Figure 6 As shown, the projection images of the left and right cameras on the laser plane at the current moment and the projection images on the laser plane at the next moment are cross-correlated, and the velocity field of the real velocity field under the perspective of the left and right cameras projected on the laser plane in the direction of the camera normal can be obtained as u cl ,u cr .

[0103] 403. Reconstruct the three-dimensional velocity component on the laser plane according to the velocity field calculation of the real velocity field under the viewing angles of the left and right cameras projected on the laser plane in the direction of the camera normal.

[0104] The embodiment of the present disclosure can be implemented by using but not limited to the following method when calculating and reconstructing the three-dimensional velocity component on the laser plane according to the velocity field projected on the laser plane in the normal direction of the camera according to the real velocity field under the left and right camera viewing angles. The method includes:

[0105] The actual velocity field under the left and right camera perspectives calculated by the standard cross-correlation algorithm is the camera normal direction vector u cl and u cr .

[0106] Specifically, Figure 6 As shown, the velocity field u projected on the laser plane under the left and right camera viewing angles is calculated. cl ,u cr After that, according to the geometric parameters n of the camera obtained by calibration cl , n cr , reconstructing the three-dimensional velocity field. The actual three-dimensional velocity u can be obtained by using the component u of the left and right camera normal directions.l ,u r and its vertical component (u·n l ) l , (u·n r ) r The sum indicates that

[0107] u=u l +(u·n l ) l

[0108] =u r +(u·n r ) r

[0109] The various components are calculated by the following formula:

[0110] u l =u cl +(u cl ·n l ) l

[0111] u r =u cr +(u cr ·n r ) r

[0112]

[0113]

[0114] in

[0115]

[0116]

[0117] In summary, according to the embodiments of the present disclosure, two mutually parallel reference planes are selected within a predetermined range of the laser plane, and the tracer particle images taken by the left and right cameras at the same time are respectively back-projected onto the two reference planes according to the transformation relationship to obtain projection images, and the position of the laser plane is determined according to the projection image, and the laser plane is fitted, and the three-dimensional velocity components on the laser plane are reconstructed based on the laser plane. The determination of the laser plane in the present disclosure can correct the rotation and translation in any direction between the laser plane and the calibration plane. And this method can be determined by the tracer particle images taken by the left and right cameras, without adding additional experimental data, so that the experimental efficiency is higher.

[0118] In the embodiment of the present disclosure, in reconstructing the three-dimensional velocity, the velocity component calculated on each camera image has two degrees of freedom, while the three-dimensional velocity in space has three degrees of freedom. Therefore, one component of the velocity components calculated by the images of the two cameras is repeated. l and n r The components in the direction of the constructed plane should be consistent, and this component can be used to verify the rationality of the calculated velocity field.

[0119] Corresponding to the above-mentioned volumetric particle image velocimetry method, an embodiment of the present disclosure further provides a volumetric particle image velocimetry device. Figure 7 FIG. 5 is a schematic diagram of a volumetric particle image velocity measurement device 500 provided in an embodiment of the present disclosure. Figure 7 As shown, including:

[0120] The calibration unit 501 is used to obtain the coordinate transformation relationship between the left and right camera coordinate systems and the actual space coordinate system. The coordinate transformation relationship of the left and right cameras is obtained from the images of the calibration plate taken by the left and right cameras respectively.

[0121] The back-projection unit 502 is used to back-project the tracer particle images taken by the left and right cameras at the same time onto two reference planes according to the coordinate transformation relationship and perform two-dimensional interpolation to obtain projection images. The two reference planes are located within a predetermined range of the laser plane and are parallel to each other.

[0122] The determination unit 503 is used to determine a plurality of position points on the laser plane according to the projection image.

[0123] The fitting unit 504 is used to fit the laser plane according to the multiple position points.

[0124] The reconstruction unit 505 is used to reconstruct the three-dimensional velocity component on the laser plane based on the laser plane.

[0125] In some embodiments, the back-projection unit 502 is used to back-project the tracer particle images taken by the left and right cameras at the same time onto two reference planes according to the coordinate transformation relationship and perform two-dimensional interpolation to obtain projection images, including:

[0126] According to the coordinate transformation relationship, based on the central projection method, all pixel points in the tracer particle images taken by the left and right cameras are back-projected onto the two reference planes respectively to obtain the projection point of each pixel point on the tracer particle image;

[0127] The grayscale values ​​of the projection points on the two reference planes are interpolated respectively by using a bilinear interpolation method to obtain projection images corresponding to the tracer particle images taken by the left and right cameras on the two reference planes.

[0128] In some embodiments, the determining unit 503 determines the position point of the laser plane according to the projection image, including:

[0129] Acquire a first grid point on a first reference plane and a second grid point on a second reference plane corresponding to the first grid point according to the projection image;

[0130] Determine, according to the first grid points and the second grid points, a first position difference and a second position difference of grid points of the tracer particle images captured by the left and right cameras on the two reference planes respectively;

[0131] According to the geometric relationship, a geometric calculation is performed on the first position difference, the second position difference, the first grid point, and the second grid point to determine a position point on the laser plane.

[0132] In some embodiments, acquiring a first grid point on a first reference plane and a second grid point on a second reference plane corresponding to the first grid point according to the projection image comprises:

[0133] Selecting a reference plane from the two reference planes as a first reference plane;

[0134] Generating first grid points on the first reference plane according to a predetermined pixel area and a predetermined overlap parameter;

[0135] The corresponding second grid point on the second reference plane is determined according to the intersection point of the line connecting the center point of the left camera or the right camera and the first grid point and the second reference plane.

[0136] In some embodiments, determining the first position difference and the second position difference of the tracer particle images captured by the left and right cameras projected on the two reference planes respectively according to the first grid points and the second grid points comprises:

[0137] Using a cross-correlation algorithm, a cross-correlation calculation is performed on an analysis window of a limited area around the images of the left and right cameras near the first grid point to obtain a first position difference between the projections of the tracer particle images taken by the left and right cameras on the first reference plane;

[0138] A cross-correlation algorithm is used to perform cross-correlation calculation on an analysis window of a limited area around the images of the left and right cameras near the second grid point to obtain a second position difference of the tracer particle images taken by the left and right cameras projected on the second reference plane.

[0139] In some embodiments, the reconstruction unit 505 reconstructs the three-dimensional velocity component on the laser plane based on the laser plane, including:

[0140] Back-projecting the tracer particle images captured by the left and right cameras onto the laser plane;

[0141] Cross-correlate the projection images of the left and right cameras on the laser plane at the current moment with the projection images of the left and right cameras on the laser plane at the next moment to obtain the velocity field of the real velocity field under the viewing angle of the left and right cameras projected on the laser plane in the direction of the camera normal;

[0142] The three-dimensional velocity component on the laser plane is reconstructed according to the velocity field calculation of the real velocity field under the viewing angles of the left and right cameras projected on the laser plane in the direction of the camera normal.

[0143] In some embodiments, calculating and reconstructing the three-dimensional velocity component on the laser plane according to the velocity field projected on the laser plane in the direction of the camera normal line according to the real velocity field under the left and right camera viewing angles includes:

[0144] The real velocity field under the left and right camera perspectives calculated by the standard cross-correlation algorithm is the velocity field u projected by the camera normal direction vector in the laser plane cl and u cr .

[0145] Calculate the three-dimensional velocity vector through the velocity field and coordinate transformation relationship of the left and right camera projections;

[0146] The rationality of the calculated velocity field is verified by the consistency of the velocity field component in the plane normal direction perpendicular to the left and right camera axes.

[0147] It should be noted that since the device embodiment of the present disclosure corresponds to the above-mentioned method embodiment, the above-mentioned explanation of the method embodiment is also applicable to the device of the present disclosure, and the principle is the same. For details not disclosed in the device embodiment, reference can be made to the above-mentioned method embodiment, and they will not be repeated in this disclosure.

[0148] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0149] Figure 8 A schematic block diagram of an example electronic device 600 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0150] like Figure 8 As shown, the device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 602 or a computer program loaded from a storage unit 608 to a RAM (Random Access Memory) 603. In the RAM 603, various programs and data required for the operation of the device 600 can also be stored. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An I / O (Input / Output) interface 605 is also connected to the bus 604.

[0151] A number of components in the device 600 are connected to the I / O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0152] The computing unit 601 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as for managing a volumetric particle image velocimetry method. For example, in some embodiments, a method for managing a safety seat may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to execute the aforementioned method for managing volumetric particle image velocimetry in any other appropriate manner (for example, by means of firmware).

[0153] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a dedicated or general-purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0154] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0155] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include electrical connections based on one or more lines, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only-Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0156] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0157] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0158] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0159] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0160] It should be noted that, for the convenience of description, only the parts related to the relevant invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0161] It should be understood that the "system", "device", "unit" and / or "module" used in the present disclosure is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the word can be replaced by other expressions.

[0162] As shown in the present disclosure and claims, unless the context clearly indicates an exception, the words "a", "an", "a kind" and / or "the" do not refer to the singular, but also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of clearly identified steps and elements, and these steps and elements do not constitute an exclusive list, and the method or device may also include other steps or elements. The elements defined by the sentence "includes a..." do not exclude the existence of other identical elements in the process, method, commodity or device that includes the elements.

[0163] In the description of the embodiments of the present disclosure, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present disclosure, "multiple" means two or more than two.

[0164] The terms "first" and "second" used in this disclosure are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0165] Flowcharts are used in this disclosure to illustrate the operations performed by the system according to the embodiments of the present disclosure. It should be understood that the preceding or following operations are not necessarily performed precisely in order. On the contrary, the steps may be processed in reverse order or simultaneously. At the same time, other operations may be added to these processes, or one or more operations may be removed from these processes, and the various forms of processes shown may be used to reorder, add or delete steps. For example, the steps described in this disclosure may be performed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document is not limited here.

[0166] The above description is only an embodiment of the present disclosure and an explanation of the technical principles used, and is not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and variations. The scope of the invention involved in the present disclosure is not limited to the technical solution formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, a technical solution formed by replacing the above-mentioned features with the technical features with similar functions disclosed in the present disclosure (but not limited to).

Claims

1. A volumetric particle image velocimetry method, characterized in that: include: Obtaining a coordinate transformation relationship between the left and right camera coordinate systems and the actual space coordinate system, wherein the coordinate transformation relationship between the left and right cameras is obtained from images of a calibration plate taken by the left and right cameras, respectively; According to the coordinate transformation relationship, the tracer particle images taken by the left and right cameras at the same time are respectively back-projected onto two reference planes and two-dimensionally interpolated to obtain projection images, wherein the two reference planes are located within a predetermined range of the laser plane and are parallel to each other; Determine a plurality of position points on a laser plane according to the projection image, and fit the laser plane according to the plurality of position points; The three-dimensional velocity components on the laser plane are reconstructed based on the laser plane.

2. The method according to claim 1, characterized in that The step of back-projecting the tracer particle images captured by the left and right cameras at the same time onto two reference planes according to the coordinate transformation relationship and performing two-dimensional interpolation to obtain projection images comprises: According to the coordinate transformation relationship, based on the central projection method, all pixel points in the tracer particle images taken by the left and right cameras are back-projected onto the two reference planes respectively to obtain the projection point of each pixel point on the tracer particle image; The grayscale values ​​of the projection points on the two reference planes are interpolated respectively by using a bilinear interpolation method to obtain projection images corresponding to the tracer particle images taken by the left and right cameras on the two reference planes.

3. The method according to claim 2, characterized in that Determining a position point on the laser plane according to the projection image comprises: Acquire a first grid point on a first reference plane and a second grid point on a second reference plane corresponding to the first grid point according to the coordinate transformation relationship; Determine, according to the first grid points and the second grid points, a first position difference and a second position difference of grid points of the tracer particle images captured by the left and right cameras on the two reference planes respectively; According to the geometric relationship, a geometric calculation is performed on the first position difference, the second position difference, the first grid point, and the second grid point to determine a position point on the laser plane.

4. The method according to claim 3, characterized in that The acquiring, according to the coordinate transformation relationship, a first grid point on the first reference plane and a second grid point on the second reference plane corresponding to the first grid point comprises: Selecting a reference plane from the two reference planes as a first reference plane; Generating first grid points on the first reference plane according to a predetermined pixel area and a predetermined overlap parameter; A second grid point corresponding to the first grid point on the second reference plane is determined according to an intersection point between a line connecting a center point of the left camera or the right camera and the first grid point and the second reference plane.

5. The method according to claim 3, characterized in that: The step of determining the first position difference and the second position difference of the grid points of the tracer particle images captured by the left and right cameras on the two reference planes respectively according to the first grid points and the second grid points comprises: Using a cross-correlation algorithm, a cross-correlation calculation is performed on an analysis window of a limited area around the images of the left and right cameras near the first grid point to obtain a first position difference between the projections of the tracer particle images taken by the left and right cameras on the first reference plane; A cross-correlation algorithm is used to perform cross-correlation calculation on an analysis window of a limited area around the images of the left and right cameras near the second grid point to obtain a second position difference between the projections of the tracer particle images taken by the left and right cameras on the second reference plane.

6. The method according to any one of claims 1 to 5, characterized in that Reconstructing the three-dimensional velocity component on the laser plane based on the laser plane includes: Back-projecting the tracer particle images captured by the left and right cameras onto the laser plane; Cross-correlate the projection images of the left and right cameras on the laser plane at the current moment with the projection images of the left and right cameras on the laser plane at the next moment to obtain the velocity field of the real velocity field under the viewing angle of the left and right cameras projected on the laser plane in the direction of the camera normal; The three-dimensional velocity component on the laser plane is reconstructed according to the velocity field calculation of the real velocity field under the viewing angles of the left and right cameras projected on the laser plane in the direction of the camera normal.

7. The method according to claim 6, characterized in that Calculating and reconstructing the three-dimensional velocity component on the laser plane according to the velocity field projected on the laser plane in the direction of the camera normal according to the real velocity field under the viewing angles of the left and right cameras comprises: The real velocity field from the left and right camera perspectives calculated by the standard cross-correlation algorithm is the velocity field projected on the laser plane with the camera normal direction vector; Calculate the three-dimensional velocity vector through the velocity field projected by the left and right cameras and the coordinate transformation relationship; The rationality of the calculated velocity field is verified by the consistency of the velocity field component in the plane normal direction perpendicular to the left and right camera axes.

8. A volumetric particle image velocimetry device, characterized in that: include: A calibration unit, used to obtain a coordinate transformation relationship between a left and right camera coordinate system and an actual space coordinate system, wherein the coordinate transformation relationship between the left and right cameras is obtained from images of a calibration plate taken by the left and right cameras respectively; A back-projection unit, used for back-projecting the tracer particle images taken by the left and right cameras at the same time onto two reference planes according to the coordinate transformation relationship and performing two-dimensional interpolation to obtain projection images, wherein the two reference planes are located within a predetermined range of the laser plane and are parallel to each other; A determination unit, configured to determine a plurality of position points on a laser plane according to the projection image; A fitting unit, used for fitting a laser plane according to the plurality of position points; A reconstruction unit is used to reconstruct a three-dimensional velocity component on the laser plane based on the laser plane.

9. An electronic device, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

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