Turbine blade leading edge air film cooling effectiveness PSP test image post-processing method

Abstract

The invention provides a turbine blade leading edge air film cooling effectiveness PSP test image post-processing method. The method comprises the following steps: acquiring an image set of a leading edge suction side and a leading edge pressure side of a to-be-tested turbine blade subjected to a PSP test under a test working condition; calculating air film cooling effectiveness distribution nephograms of the front edge suction side and the front edge pressure side through the image set; the method comprises the following steps: pasting a black-and-white grid calibration piece on the front edge of a turbine blade to be measured, collecting calibration pictures of a front edge suction side and a front edge pressure side, and obtaining a coordinate transformation matrix of the front edge suction side and the front edge pressure side; and according to the coordinate transformation matrix, flattening and recombining the air film cooling effectiveness distribution nephograms of the front edge suction side and the front edge pressure side to obtain a blade front edge air film cooling effectiveness distribution nephogram of the turbine blade to be detected. The method provided by the invention can solve the technical problem that the blade leading edge air film cooling efficiency distribution cannot be accurately measured due to high processing difficulty of images obtained through inclination angle and block shooting during a large-curvature turbine blade PSP experiment.

Description

Technical Field

[0001] This invention belongs to the field of gas turbine engine testing and relates to the technology for analyzing the effectiveness of film cooling at the leading edge of turbine blades. Specifically, it relates to a post-processing method for PSP test images of the effectiveness of film cooling at the leading edge of turbine blades, used to obtain the distribution of film cooling efficiency at the large curvature leading edge of turbine blades under tilted angle photography. Background Technology

[0002] A gas turbine engine is a thermal power unit with powerful output and high thermal efficiency, typically operating in extremely harsh environments. During the development of gas turbine engines, to improve thrust and thermal efficiency and thus enhance performance, turbine inlet temperatures are continuously increased. For example, the turbine inlet gas temperature in advanced aero-turbofan engines has reached 1800K–2050K, significantly exceeding the temperature resistance of existing high-temperature alloys. To ensure safe turbine operation and extend turbine blade lifespan, effective cooling technologies must be implemented, and the film cooling efficiency distribution at the turbine blade leading edge must be accurately measured to precisely predict the cooling effect of different cooling structures.

[0003] Among them, the PSP (also known as pressure-sensitive paint technology) experiment is a common measurement method for the effectiveness of air film cooling on the surface of turbine blades. It has the advantages of high experimental efficiency, reliable and stable measurement results, and little influence from temperature. The principle is based on the photoluminescence and oxygen quenching characteristics of pressure-sensitive paint, converting the luminescence intensity of the paint into oxygen partial pressure, and solving the air film cooling effectiveness through the principle of heat transfer and mass transfer analogy.

[0004] However, due to the large curvature and complex flow field of the turbine blade leading edge, the PSP experiment can only be conducted by taking pictures from the upper and lower endwalls. Moreover, a single shot cannot completely capture the cold air outflow trajectory of all the exhaust film holes at the leading edge. During the shooting process, two cameras are usually needed to take pictures from the suction side and the pressure side at the same time, or the suction side and the pressure side of a blade are taken by a single camera in two separate shots. This poses a great challenge to the processing of the images after the experiment, making it difficult to accurately measure the distribution of the film cooling efficiency at the leading edge of the turbine blade. Summary of the Invention

[0005] To address the technical problem of inaccurate measurement of the film cooling efficiency distribution at the leading edge of turbine blades due to the difficulty in image processing obtained from tilted angle and segmented shooting during PSP experiments on turbine blades with large curvature, this invention discloses a post-processing method for PSP experiment images of turbine blade leading edge film cooling effectiveness. The method includes the following steps:

[0006] S101. Collect image sets of the leading-edge suction side and leading-edge pressure side of the turbine blade under test under test conditions for PSP test;

[0007] S102. Calculate the distribution cloud map of the film cooling effectiveness of the leading edge suction side and the leading edge pressure side using the image set respectively;

[0008] S103. A black and white grid calibration piece is attached to the leading edge of the turbine blade to be tested. Calibration images of the leading edge suction side and the leading edge pressure side are collected respectively. Based on the black and white grid calibration piece and the calibration images, the coordinate transformation matrix of the leading edge suction side and the leading edge pressure side is obtained respectively.

[0009] S104. Based on the coordinate transformation matrix, the distribution cloud maps of the effective air film cooling on the leading edge suction side and the leading edge pressure side are flattened to obtain flattened images. The flattened images on the leading edge suction side and the leading edge pressure side are reconstructed to obtain the distribution cloud map of the effective air film cooling on the leading edge of the turbine blade under test.

[0010] Optionally, in step S102, calculating the distribution cloud maps of the film cooling effectiveness on the leading edge suction side and the leading edge pressure side using the image set includes:

[0011] S1021. When conducting a PSP test on the turbine blade under the test conditions, the collected image set includes a dark image, a reference image, an experimental image, and an air image, and the light intensity of each pixel in the dark image, the reference image, the experimental image, and the air image is obtained respectively.

[0012] S1022. Based on the light intensity of each pixel in the dark image and the reference image, calculate the light intensity ratio distribution cloud map of the experimental image and the air image respectively, wherein the light intensity ratio distribution cloud map includes the light intensity ratio of each pixel.

[0013] S1023. Based on the fitting formula between light intensity ratio and oxygen partial pressure ratio, calculate the oxygen partial pressure ratio distribution cloud map of the experimental image and the air image respectively using the light intensity ratio distribution cloud map. The oxygen partial pressure ratio distribution cloud map includes the oxygen partial pressure ratio of each pixel.

[0014] S1024. Based on the conversion formula between oxygen partial pressure ratio and film cooling effectiveness, the first film cooling effectiveness distribution cloud map is calculated for the leading edge suction side and the leading edge pressure side using the oxygen partial pressure ratio distribution cloud map of the experimental image and the air image, respectively. The first film cooling effectiveness distribution cloud map includes the film cooling effectiveness of each pixel. The first film cooling effectiveness distribution cloud map is used as the film cooling effectiveness distribution cloud map.

[0015] Optionally, step S102 above further includes:

[0016] S1025. Perform median filtering on the first air film cooling effectiveness distribution cloud map to obtain the second air film cooling effectiveness distribution cloud map.

[0017] S1026. Extract the pixels in the second air film cooling effectiveness distribution cloud map of the leading edge suction side and the leading edge pressure side that are within the threshold range to obtain the third air film cooling effectiveness distribution cloud map of the leading edge suction side and the leading edge pressure side, and use the third air film cooling effectiveness distribution cloud map as the air film cooling effectiveness distribution cloud map.

[0018] Optionally, step S102 above further includes:

[0019] S1027. When there are multiple experimental images, the distribution cloud map of the air film cooling effectiveness of each experimental image is obtained, and the average value of the distribution cloud maps of the air film cooling effectiveness of all experimental images is processed to obtain the final distribution cloud map of the air film cooling effectiveness.

[0020] Optionally, in step S1022 above, the formula for calculating the light intensity ratio is: Wherein, the I Q I represents the light intensity ratio of pixels in the experimental image or the atmospheric image. B I represents the light intensity of a pixel in the dark image. R I represents the light intensity of a pixel in the reference image. p The intensity of light at a pixel in the experimental image or the air image.

[0021] Optionally, in step S1023 above, the fitting formula for the light intensity ratio and oxygen partial pressure ratio is: p Q =a*I p +b, where p Q is the oxygen partial pressure ratio of the pixels in the experimental image or the air image, and a and b are parameters related to the photosensitive material coated on the surface of the turbine blade under test during the PSP test.

[0022] Optionally, in step S1024 above, the conversion formula between oxygen partial pressure ratio and film cooling effectiveness is as follows: Where, p N2 p represents the oxygen partial pressure ratio of the pixels in the experimental image. A This represents the oxygen partial pressure ratio at the corresponding pixel in the air image.

[0023] Optionally, in step S103 above, obtaining the coordinate transformation matrices of the leading edge suction side and the leading edge pressure side based on the black and white grid calibration component and the calibration image respectively includes:

[0024] S1031. Take the side of the calibration image closest to the leading edge of the turbine blade under test as the boundary line between the leading edge suction side and the leading edge pressure side. Using the boundary line as the starting point and a set distance as the ending point, segment the calibration image to obtain an image within the set distance range as the calibration area.

[0025] S1032. Extract the pixel coordinates of all black and white grid vertices in the calibration area to obtain the calibration file;

[0026] S1033. Based on the calibration file, calculate the curve equations of the four sides of each grid in the calibration image, obtain the straight line equations of the four sides of the corresponding grid in the black and white grid calibration component, and obtain the coordinate transformation matrix based on the straight line equations and curve equations of all the grids.

[0027] Optionally, in step S104 above, based on the coordinate transformation matrix, the distribution cloud maps of the film cooling effectiveness on the leading edge suction side and the leading edge pressure side are flattened to obtain flattened images, and the flattened images on the leading edge suction side and the leading edge pressure side are reconstructed to obtain the distribution cloud map of the film cooling effectiveness of the turbine blade under test, including:

[0028] S1041. Based on the coordinate transformation matrix, perform coordinate transformation on each pixel in the distribution cloud map of the effectiveness of air film cooling to obtain new pixel coordinates, and obtain the flattened image based on the new pixel coordinates;

[0029] S1042. Taking the boundary line between the leading edge suction side and the leading edge pressure side as the origin of the horizontal coordinate, taking the pixel horizontal coordinate of the calibration image of the leading edge suction side as a negative value, and taking the pixel horizontal coordinate of the calibration image of the leading edge pressure side as a positive value, the pixel coordinates of the flattened images of the leading edge suction side and the leading edge pressure side are transformed and recombined to obtain the distribution cloud map of the effectiveness of the air film cooling at the leading edge of the blade.

[0030] This invention also provides a post-processing system for PSP test images of turbine blade leading edge film cooling effectiveness, including an acquisition module, a first processing module, a coordinate transformation matrix acquisition module, a flattening module, and a reconstruction module.

[0031] The acquisition module is used to acquire image sets of the leading edge suction side and leading edge pressure side of the turbine blade under test under test conditions, and is also used to attach black and white grid calibration parts to the leading edge of the turbine blade under test, and acquire calibration images of the leading edge suction side and the leading edge pressure side respectively.

[0032] The first processing module is used to calculate the distribution cloud maps of the film cooling effectiveness of the leading edge suction side and the leading edge pressure side respectively using the image set;

[0033] The coordinate transformation matrix acquisition module is used to acquire the coordinate transformation matrices of the leading edge suction side and the leading edge pressure side respectively based on the black and white grid calibration component and the calibration image;

[0034] The flattening module is used to flatten the distribution cloud map of the effective air film cooling on the leading edge suction side and the leading edge pressure side according to the coordinate transformation matrix to obtain a flattened image.

[0035] The reconstruction module is used to reconstruct the flattened images of the leading edge suction side and the leading edge pressure side to obtain a cloud map of the effective distribution of the leading edge film cooling of the turbine blade under test.

[0036] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-mentioned data storage methods to solve the technical problem that the distribution of film cooling efficiency at the leading edge of the turbine blade cannot be accurately measured due to the difficulty in processing images obtained by tilting angle and segmented shooting during PSP experiments on large curvature turbine blades.

[0037] This invention also provides a computer-readable storage medium storing a computer program that executes any of the above-described data storage methods, in order to solve the technical problem that the distribution of film cooling efficiency at the leading edge of turbine blades cannot be accurately measured due to the difficulty in processing images obtained by tilting angle and segmented shooting during PSP experiments on large curvature turbine blades.

[0038] Compared with the prior art, the beneficial effects achieved by at least one of the above-mentioned technical solutions adopted in the embodiments of this specification include at least the following: The post-processing method for PSP test images of turbine blade leading edge film cooling effectiveness of the present invention firstly obtains the distribution cloud map of film cooling effectiveness on the leading edge pressure side and leading edge suction side of the turbine blade under test conditions; secondly, by attaching a black and white grid calibration piece to the leading edge of the turbine blade and acquiring calibration images, the coordinate transformation relationship between the calibration images and the black and white grid calibration piece can be obtained; finally, the distribution cloud map of film cooling effectiveness is transformed by coordinate transformation to obtain a flattened image, and then the two flattened images are stitched together by dimensionless processing to obtain the distribution cloud map of film cooling effectiveness of the turbine blade leading edge under test conditions. This method can solve the problems of obtaining, flattening and combining the film cooling effectiveness of the leading edge of large curvature turbine blades under tilt angles and segmented shooting. By accurately obtaining the distribution cloud map of film cooling effectiveness of the leading edge of the blade under different test conditions, the film cooling efficiency under different conditions can be compared. Attached Figure Description

[0039] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart of the post-processing method for PSP test images of turbine blade leading edge film cooling effectiveness disclosed in an embodiment of the present invention;

[0041] Figure 2 This is an experimental image of the suction side of the leading edge of the turbine blade under test, as disclosed in an embodiment of the present invention.

[0042] Figure 3 This is an experimental image of the leading edge pressure side of the turbine blade under test, as disclosed in an embodiment of the present invention.

[0043] Figure 4 This is a schematic diagram of a twisted quadrilateral block and a regular grid-like block for flattening, as disclosed in an embodiment of the present invention.

[0044] Figure 5 This is a cloud map showing the distribution of the effectiveness of film cooling in front of the turbine blades, as disclosed in an embodiment of the present invention. Detailed Implementation

[0045] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0046] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features of the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0047] When conducting film cooling (PSP) effectiveness tests on turbine blades, acquisition modules (i.e., cameras) are typically installed on the leading-edge pressure side and leading-edge suction side above the turbine blade. Under test conditions, dark images, reference images, experimental images, and air images are acquired on both the leading-edge pressure side and leading-edge suction side. Specifically, the dark image is obtained by photographing the turbine blade under test in a dark environment with a filter applied; the reference image is obtained by removing the filter and turning on the excitation light source; the experimental image is obtained by turning on the mains fan to purge nitrogen into the cooling chamber of the turbine blade under test, allowing it to escape from the film cooling vents; and the air image is obtained by turning off the nitrogen purge and purgeing air into the cooling chamber, allowing it to escape from the film cooling vents. It should be noted that during PSP tests, one or more of each of the dark, reference, experimental, and air images can be taken at a time.

[0048] This invention discloses a post-processing method for PSP test images of turbine blade leading edge film cooling effectiveness, see [link to relevant documentation]. Figure 1 As shown, the method includes the following steps:

[0049] S101. Collect image sets of the leading-edge suction side and leading-edge pressure side of the turbine blade under test under test conditions for PSP test;

[0050] S102. Calculate the distribution cloud map of the film cooling effectiveness of the leading edge suction side and the leading edge pressure side using the image set respectively;

[0051] S103. A black and white grid calibration piece is attached to the leading edge of the turbine blade to be tested. Calibration images of the leading edge suction side and the leading edge pressure side are collected respectively. Based on the black and white grid calibration piece and the calibration images, the coordinate transformation matrix of the leading edge suction side and the leading edge pressure side is obtained respectively.

[0052] S104. Based on the coordinate transformation matrix, the distribution cloud maps of the effective air film cooling on the leading edge suction side and the leading edge pressure side are flattened to obtain flattened images. The flattened images on the leading edge suction side and the leading edge pressure side are reconstructed to obtain the distribution cloud map of the effective air film cooling on the leading edge of the turbine blade under test.

[0053] Optionally, in step S102, calculating the distribution cloud maps of the film cooling effectiveness on the leading edge suction side and the leading edge pressure side using the image set includes:

[0054] S1021. When conducting a PSP test on the turbine blade under the test conditions, the acquired image set includes a dark image, a reference image, an experimental image, and an air image. The light intensity of each pixel in the dark image, the reference image, the experimental image, and the air image is obtained respectively. The light intensity of each pixel in each of the dark image, the reference image, the experimental image, and the air image can be expressed as I. B I ref , I and I air The experimental images for the leading edge suction side and the leading edge pressure side are shown in [reference 1]. Figure 2 and Figure 3 As shown.

[0055] S1022. Based on the light intensity of each pixel in the dark image and the reference image, calculate the light intensity ratio distribution cloud map of the experimental image and the atmospheric image respectively. The light intensity ratio distribution cloud map includes the light intensity ratio of each pixel, and the light intensity ratio of a pixel can be expressed as I. Q Including the light intensity ratio of pixels in the experimental image The light intensity ratio I of corresponding pixels in an air image A .

[0056] The formula for calculating the light intensity ratio is: Wherein, the I Q I represents the light intensity ratio of pixels in the experimental image or the atmospheric image. B I represents the light intensity of a pixel in the dark image. R I represents the light intensity of a pixel in the reference image. p The light intensity of a pixel in the experimental image or the atmospheric image. Specifically, the light intensity ratio of pixels in the experimental image is: The light intensity ratio of pixels in an atmospheric image is:

[0057] S1023. Based on the fitting formula between light intensity ratio and oxygen partial pressure ratio, calculate the oxygen partial pressure ratio distribution cloud map for the experimental image and the air image respectively using the light intensity ratio distribution cloud map. The oxygen partial pressure ratio distribution cloud map includes the oxygen partial pressure ratio of each pixel, and the oxygen partial pressure ratio of a pixel can be expressed as p. Q This includes the oxygen partial pressure ratio of pixels in the experimental images. The oxygen partial pressure ratio p of the corresponding pixel in the air image A .

[0058] The fitting formula for the light intensity ratio and oxygen partial pressure ratio is: p Q =a*I p +b, where p QThe oxygen partial pressure ratio of the pixels in the experimental image or the air image is denoted as , where a and b are parameters related to the photosensitive material coated on the surface of the turbine blade under test during the PSP test. Specifically, the oxygen partial pressure ratio of the pixels in the experimental image is: Oxygen partial pressure ratio of pixels in an air image: p A =a*I A +b.

[0059] S1024. Based on the conversion formula between oxygen partial pressure ratio and film cooling effectiveness, the first film cooling effectiveness distribution cloud map is calculated for the leading edge suction side and the leading edge pressure side using the oxygen partial pressure ratio distribution cloud map of the experimental image and the air image, respectively. The first film cooling effectiveness distribution cloud map includes the film cooling effectiveness of each pixel. The first film cooling effectiveness distribution cloud map is used as the film cooling effectiveness distribution cloud map.

[0060] The conversion formula between oxygen partial pressure ratio and film cooling effectiveness is as follows: in, p represents the oxygen partial pressure ratio of the pixels in the experimental image. A This represents the oxygen partial pressure ratio at the corresponding pixel in the air image.

[0061] Optionally, step S102 above further includes:

[0062] S1025. The first air film cooling effectiveness distribution cloud map is processed by median filtering to obtain the second air film cooling effectiveness distribution cloud map. Median filtering can improve the accuracy of the cooling effectiveness of the pixels.

[0063] S1026. Extract the pixels whose film cooling effectiveness is within the threshold range from the second film cooling effectiveness distribution cloud maps of the leading edge suction side and the leading edge pressure side, respectively, to obtain the third film cooling effectiveness distribution cloud maps of the leading edge suction side and the leading edge pressure side. Use the third film cooling effectiveness distribution cloud map as the film cooling effectiveness distribution cloud map. In specific implementation, the threshold range for film cooling effectiveness can be set between 0 and 1, that is, information from pixels whose film cooling effectiveness is within the range of 0 to 1 is selected to form the film cooling effectiveness distribution cloud map.

[0064] Optionally, step S102 above further includes:

[0065] S1027. When there are multiple experimental images, the distribution cloud map of the air film cooling effectiveness of each experimental image is obtained, and the average value of the distribution cloud maps of the air film cooling effectiveness of all experimental images is processed to obtain the final distribution cloud map of the air film cooling effectiveness.

[0066] Specifically, when n experimental images are captured simultaneously, the final air-film cooling effectiveness of each pixel can be expressed as: Where, η i . represents the effectiveness of film cooling at the pixel of the i-th experimental image.

[0067] Optionally, in step S103 above, obtaining the coordinate transformation matrices of the leading edge suction side and the leading edge pressure side based on the black and white grid calibration component and the calibration image respectively includes:

[0068] S1031. Take the side of the calibration image closest to the leading edge of the turbine blade under test as the boundary line between the leading edge suction side and the leading edge pressure side. Using the boundary line as the starting point and a set distance as the ending point, segment the calibration image to obtain an image within the set distance range as the calibration area.

[0069] In practice, the distance range can be set as the boundary line as the starting point, and the coordinates of the vertices of each grid within a region extending downstream in the direction of suction and pressure, which is 20 times the spacing between air film pores.

[0070] S1032. Extract the pixel coordinates of all black and white grid vertices in the calibration area to obtain the calibration file.

[0071] S1033. Based on the calibration file, calculate the curve equations of the four sides of each grid in the calibration image, obtain the straight line equations of the four sides of the corresponding grid in the black and white grid calibration component, and obtain the coordinate transformation matrix based on the straight line equations and curve equations of all the grids. In specific implementation, the calibration area can be divided into quadrilateral blocks, and the slope and intercept of the four sides of each block can be calculated to obtain the curve equation of each side of the quadrilateral block. Simultaneously, based on the width-to-height ratio of the quadrilateral blocks divided in the calibration area, the corresponding regular grid-like blocks in the black and white grid calibration component can be obtained. The distorted quadrilateral blocks and the regular grid-like blocks for flattening are as follows... Figure 4 As shown.

[0072] Optionally, in step S104 above, based on the coordinate transformation matrix, the distribution cloud maps of the film cooling effectiveness on the leading edge suction side and the leading edge pressure side are flattened to obtain flattened images, and the flattened images on the leading edge suction side and the leading edge pressure side are reconstructed to obtain the distribution cloud map of the film cooling effectiveness of the turbine blade under test, including:

[0073] S1041. Based on the coordinate transformation matrix, perform coordinate transformation on each pixel in the distribution cloud map of the effectiveness of air film cooling to obtain new pixel coordinates, and obtain the flattened image based on the new pixel coordinates;

[0074] S1042. Taking the boundary line between the leading edge suction side and the leading edge pressure side as the origin of the horizontal coordinate, taking the pixel horizontal coordinate of the calibration image of the leading edge suction side as a negative value, and taking the pixel horizontal coordinate of the calibration image of the leading edge pressure side as a positive value, the pixel coordinates of the flattened images of the leading edge suction side and the leading edge pressure side are transformed and recombined to obtain the distribution cloud map of the effectiveness of the air film cooling at the leading edge of the blade.

[0075] In the specific implementation of steps S1041 and S1042 above, firstly, pixels located within the calibration area in the distribution cloud map of the film cooling effectiveness under the test conditions are selected. Each pixel in the area is mapped to a small grid block in the calibration file. Points within the distorted small blocks are linearly converted into points within the regular small blocks proportionally, and the film cooling effectiveness of each pixel in the distorted small blocks is correspondingly assigned to the pixel in the regular small block. Secondly, based on the known width and height values ​​of the black and white grids, the coordinates of the flattened cloud map are converted into a dimensionless arc length S / d. f He Ye Gao Z / d f The abscissa of the suction side is set to negative, and the abscissa of the pressure side is set to positive. The formula for converting the abscissa of the suction side is: S / d f =N*L*(X i -Y all ) / Y all The formula for converting the horizontal axis on the pressure side is: S / d f =N*L*(X i -1) / Y all The formula for converting the ordinate of the suction side and the pressure side is the same: Z / d f =m*H*(Y i -1) / X all Where m and N are the number of rows and columns of black and white squares in the calibration area, respectively; L and H are the width and height of the black and white squares, respectively; and X is the height of the black and white squares. i and Y i Let X and X be the coordinates of the i-th pixel. all Y represents the total number of pixels in each row. all This represents the total number of pixels in each column. Finally, the flattened file is written in a format readable by post-processing software such as Tecplot, and then imported into Tecplot to obtain a complete image showing the combined suction and pressure sides. (See also...) Figure 5 The image shows a cloud map illustrating the effective distribution of film cooling in front of the turbine blades. (See also...) Figure 5 As shown, the distribution cloud map of the effectiveness of film cooling after processing by the method of the present invention can clearly show the cold air outflow trajectory of each film hole at the leading edge of each turbine blade, and can also perform spanwise averaging and area averaging on the effectiveness of film cooling at the leading edge of the turbine blade.

[0076] The present invention discloses a post-processing method for turbine blade leading-edge film cooling (PSP) effectiveness test images. First, it obtains film cooling effectiveness distribution cloud maps of the turbine blade's leading-edge pressure and suction sides under test conditions. Second, by attaching a black-and-white grid calibration piece to the leading edge of the turbine blade and acquiring calibration images, the coordinate transformation relationship between the calibration images and the black-and-white grid calibration piece can be obtained. Finally, the film cooling effectiveness distribution cloud map is transformed using the coordinate transformation relationship to obtain a flattened image. Then, two flattened images are stitched together using dimensionless processing to obtain the film cooling effectiveness distribution cloud map of the turbine blade under test under test conditions. This method can solve the problems of acquiring, flattening, and combining the film cooling effectiveness of large-curvature turbine blades under tilted angles and segmented shooting conditions. By accurately obtaining the film cooling effectiveness distribution cloud maps of the blade leading edge under different test conditions, the film cooling efficiency under different conditions can be compared.

[0077] Based on the same inventive concept, this invention also provides a post-processing system for turbine blade leading-edge film cooling (PSP) test images, as described in the following embodiments. Since the principle by which this system solves the problem is similar to the above-described post-processing method for turbine blade leading-edge film cooling (PSP) test images, the implementation of this system can refer to the implementation of the above method, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0078] Specifically, this invention also provides a post-processing system for PSP test images of turbine blade leading edge film cooling effectiveness, including an acquisition module, a first processing module, a coordinate transformation matrix acquisition module, a flattening module, and a reconstruction module.

[0079] The acquisition module is used to acquire image sets of the leading edge suction side and leading edge pressure side of the turbine blade under test under test conditions, and is also used to attach black and white grid calibration parts to the leading edge of the turbine blade under test, and acquire calibration images of the leading edge suction side and the leading edge pressure side respectively.

[0080] The first processing module is used to calculate the distribution cloud maps of the film cooling effectiveness of the leading edge suction side and the leading edge pressure side respectively using the image set;

[0081] The coordinate transformation matrix acquisition module is used to acquire the coordinate transformation matrices of the leading edge suction side and the leading edge pressure side respectively based on the black and white grid calibration component and the calibration image;

[0082] The flattening module is used to flatten the distribution cloud map of the effective air film cooling on the leading edge suction side and the leading edge pressure side according to the coordinate transformation matrix to obtain a flattened image.

[0083] The reconstruction module is used to reconstruct the flattened images of the leading edge suction side and the leading edge pressure side to obtain a cloud map of the effective distribution of the leading edge film cooling of the turbine blade under test.

[0084] In this embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-described data storage methods.

[0085] Specifically, the computer device can be a computer terminal, a server, or a similar computing device.

[0086] In this embodiment, a computer-readable storage medium is provided, which stores a computer program that performs any of the above-described data storage methods.

[0087] Specifically, computer-readable storage media, including both permanent and non-permanent, removable and non-removable media, can store information using any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer-readable storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable storage media does not include transient media, such as modulated data signals and carrier waves.

[0088] Obviously, those skilled in the art should understand that the modules or steps of the above-described embodiments of the present invention can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the embodiments of the present invention are not limited to any particular hardware and software combination.

[0089] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, various modifications and variations can be made to the embodiments of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for post-processing images of a PSP test of the effectiveness of film cooling on the leading edge of a turbine blade, characterized in that: include: Collect image sets of the leading edge suction side and leading edge pressure side of the PSP test of the turbine blade under test conditions; Calculate the film cooling effectiveness distribution cloud diagrams of the leading edge suction side and the leading edge pressure side respectively through the image set; Pasting a black and white grid calibration piece on the leading edge of the turbine blade to be tested, collecting calibration pictures of the leading edge suction side and the leading edge pressure side respectively, and obtaining the coordinate transformation matrix of the leading edge suction side and the leading edge pressure side respectively according to the black and white grid calibration piece and the calibration pictures; According to the coordinate transformation matrix, the film cooling effectiveness distribution cloud maps of the leading edge suction side and the leading edge pressure side are flattened to obtain flattened images, and the flattened images of the leading edge suction side and the leading edge pressure side are recombined to obtain the blade leading edge film cooling effectiveness distribution cloud map of the turbine blade to be tested.

2. The turbine blade leading edge film cooling effectiveness PSP test image post-processing method according to claim 1, characterized in that: The air film cooling effectiveness distribution cloud diagrams of the leading edge suction side and the leading edge pressure side are calculated respectively through the image set, including: When the PSP test is performed on the turbine blade to be tested under the test conditions, the image set collected includes a dark image, a reference image, an experimental image and an air image, and the light intensity of each pixel point in the dark image, the reference image, the experimental image and the air image is obtained respectively; According to the light intensity of each pixel point in the dark image and the reference image, respectively calculate the light intensity ratio distribution cloud map of the experimental image and the air image, wherein the light intensity ratio distribution cloud map includes the light intensity ratio of each pixel point; According to the fitting formula of the light intensity ratio and the oxygen partial pressure ratio, the oxygen partial pressure ratio distribution cloud maps of the experimental image and the air image are calculated respectively through the light intensity ratio distribution cloud map, and the oxygen partial pressure ratio distribution cloud map includes the oxygen partial pressure ratio of each pixel point; According to the conversion formula between the oxygen partial pressure ratio and the effectiveness of film cooling, the first film cooling effectiveness distribution cloud maps of the leading edge suction side and the leading edge pressure side are calculated respectively through the oxygen partial pressure ratio distribution cloud maps of the experimental image and the air image, the first film cooling effectiveness distribution cloud map includes the film cooling effectiveness of each pixel point, and the first film cooling effectiveness distribution cloud map is used as the film cooling effectiveness distribution cloud map.

3. The turbine blade leading edge film cooling effectiveness PSP test image post-processing method according to claim 2, characterized in that: Also includes: Performing median filtering on the first film cooling effectiveness distribution cloud map to obtain a second film cooling effectiveness distribution cloud map; Pixel points whose film cooling effectiveness is within a threshold range are extracted from the second film cooling effectiveness distribution cloud map of the leading edge suction side and the leading edge pressure side respectively to obtain third film cooling effectiveness distribution cloud maps of the leading edge suction side and the leading edge pressure side, and the third film cooling effectiveness distribution cloud map is used as the film cooling effectiveness distribution cloud map.

4. The turbine blade leading edge film cooling effectiveness PSP test image post-processing method according to claim 2 or 3, characterized in that: Also includes: When there are multiple experimental images, the film cooling effectiveness distribution cloud map of each experimental image is obtained respectively, and the film cooling effectiveness distribution cloud maps of all the experimental images are averaged to obtain the final film cooling effectiveness distribution cloud map.

5. The method for post-processing images of a PSP test of the effectiveness of film cooling at the leading edge of a turbine blade according to claim 2, characterized in that: The calculation formula of light intensity ratio is: Among them, the I Q is the light intensity ratio of the pixels in the experimental image or the air image, I B is the light intensity of the pixel in the dark image, I R is the light intensity of the pixel in the reference image, I p is the light intensity of a pixel in the experimental image or the air image.

6. The turbine blade leading edge film cooling effectiveness PSP test image post-processing method according to claim 5, characterized in that: The fitting formula of light intensity ratio and oxygen partial pressure ratio is: Q =a*I p +b, where p Q is the oxygen partial pressure ratio of the pixel points in the experimental image or the air image, and a and b are parameters related to the photosensitive material coated on the surface of the turbine blade to be tested during the PSP test.

7. The turbine blade leading edge film cooling effectiveness PSP test image post-processing method according to claim 6, characterized in that: The conversion formula between oxygen partial pressure ratio and film cooling effectiveness is: in, is the oxygen partial pressure ratio of the pixel in the experimental image, p A is the oxygen partial pressure ratio of the corresponding pixel in the air image.

8. The turbine blade leading edge film cooling effectiveness PSP test image post-processing method according to claim 1, characterized in that: According to the black and white grid calibration piece and the calibration picture, the coordinate transformation matrix of the leading edge suction side and the leading edge pressure side is obtained respectively, including: The side of the calibration image close to the leading edge of the turbine blade to be measured is used as the boundary line between the leading edge suction side and the leading edge pressure side, the boundary line is used as the starting point, and the set distance is used as the end point, and the calibration image is segmented to obtain an image within the set distance range as the calibration area; Extracting pixel coordinates of all black and white grid vertices in the calibration area to obtain a calibration file; According to the calibration file, the curve equations of the four sides of each grid in the calibration image are calculated, the straight line equations of the four sides of the corresponding grid in the black and white grid calibration piece are obtained, and the coordinate transformation matrix is ​​obtained according to the straight line equations and the curve equations of all the grids.

9. The turbine blade leading edge film cooling effectiveness PSP test image post-processing method according to claim 8, characterized in that: According to the coordinate transformation matrix, the film cooling effectiveness distribution cloud maps of the leading edge suction side and the leading edge pressure side are flattened to obtain flattened images, and the flattened images of the leading edge suction side and the leading edge pressure side are recombined to obtain a blade leading edge film cooling effectiveness distribution cloud map of the turbine blade to be tested, including: According to the coordinate transformation matrix, coordinate transformation is performed on each pixel point in the film cooling effectiveness distribution cloud map to obtain new pixel coordinates, and the flattened image is obtained according to the new pixel coordinates; The boundary line between the leading edge suction side and the leading edge pressure side is taken as the origin of the horizontal coordinate, the pixel horizontal coordinate of the calibration image of the leading edge suction side is taken as a negative value, and the pixel horizontal coordinate of the calibration image of the leading edge pressure side is taken as a positive value. The pixel coordinates of the flattened images of the leading edge suction side and the leading edge pressure side are converted and reorganized to obtain the distribution cloud map of the effectiveness of film cooling at the leading edge of the blade.

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