Column skirt model shock wave boundary layer interference measurement method based on dynamic PSP

Abstract

The invention relates to a dynamic PSP-based column skirt model shock wave boundary layer interference measurement method, which is based on a high-Mach-number column skirt model of an aircraft and is used for solving the problems of PSP hardware synchronization, flow field self-luminous shielding, PSP pressure calibration and error analysis and three-dimensional pressure reduction of the column skirt model in a high-Mach-number environment. Finally, the shock wave / boundary layer interference wall surface pressure distribution characteristics of the column skirt model in the millisecond magnitude flow field are obtained, high-resolution full-field non-contact measurement can be realized, and dynamic unsteady measurement can be realized by adopting a fast response PSP technology.

Description

Technical Field

[0001] The invention relates to a column skirt model shock wave boundary layer interference measurement method based on dynamic PSP, and belongs to the field of aerospace experimental technology and non-contact full-field pressure field measurement. Background Art

[0002] Shock wave / boundary layer interference (STBLI) is a common flow phenomenon. Hypersonic STBLI is more compressible than conventional supersonic conditions. After flow reattachment, it will form very high local force / heat loads, which will seriously affect the flight safety of the aircraft. The STBLI problem of the column skirt configuration comes from the high-speed rotating body aircraft of the HIFiRE-1 configuration. There are boundary layer separation, reattachment and shock wave interference at the corners of the column skirt, which leads to severe aerodynamic and aerodynamic heat loads. The measurement of the STBLI structure and surface load distribution of this type of configuration can effectively support the prediction of interference characteristics, thereby providing a basis for aircraft load design and thermal protection.

[0003] High Mach number ground simulation environments mostly use shock wave wind tunnel platforms. The flow field time is short, and conventional pressure measurement methods are difficult to obtain large-area high-resolution pressure distribution characteristics. Summary of the invention

[0004] The technical problem solved by the present invention is: in view of the problems of PSP hardware synchronization and pressure restoration in a high Mach number environment in the current prior art, a column skirt model shock wave boundary layer interference measurement method based on dynamic PSP is proposed.

[0005] The present invention solves the above technical problems by the following technical solutions:

[0006] A method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP, comprising:

[0007] Establish a high Mach millisecond wind tunnel flow field, and synchronously collect dynamic PSP images and high-frequency response pressure sensor data of the aircraft column skirt model in the wind tunnel flow field;

[0008] Shielding treatment of the self-luminescence of high Mach millisecond wind tunnel flow field;

[0009] Dynamic PSP in-situ calibration is performed based on the synchronously collected high-frequency response pressure sensor data to eliminate the influence of temperature effects, and temperature error analysis is performed using ground static calibration results and phosphorescence thermal map data;

[0010] The two-dimensional pressure data of the column skirt model in a wind tunnel flow field of high Mach numbers and milliseconds is measured and restored to three-dimensional pressure data through direct linear transformation. The pressure distribution characteristics of the shock wave boundary layer of the column skirt model are obtained based on the three-dimensional pressure data.

[0011] In the wind tunnel flow field, a PSP high-speed camera, an ultraviolet light source, a pressure sensor, and a synchronous controller are arranged, wherein:

[0012] The synchronous controller receives the external pulse signal, generates a trigger signal and sends it to the PSP high-speed camera, ultraviolet light source and pressure sensor respectively; the PSP high-speed camera and ultraviolet light source receive the trigger signal to collect the PSP image, and the pressure sensor synchronously receives the trigger signal to collect the surface pressure of the model.

[0013] After receiving the external pulse signal, the synchronous controller sends a trigger signal to the PSP high-speed camera, the ultraviolet light source, and the pressure sensor after extending the specified time according to the preset delay.

[0014] The method for shielding the self-luminescence of the wind tunnel flow field is:

[0015] Eliminate the self-luminous image of the PSP image or filter the self-luminous image through a bandpass filter, where:

[0016] After the PSP image is acquired, the self-luminous image is acquired by turning off all light sources and then eliminated from the PSP image;

[0017] The method of filtering the spontaneous emission through a bandpass filter is:

[0018] A 650±Nnm bandpass filter was selected to filter the self-luminescence, and the collected image signal was filtered to reduce the PSP image noise and filter the self-luminescence.

[0019] N is obtained through experimental calibration, and the calibration method is:

[0020] After turning off all controllable light sources, the wind tunnel blows air to collect PSP images I (N) ;

[0021] Only the UV light source is turned on, and the wind tunnel blows air to collect PSP images, and I (S+N) , calculate the signal-to-noise ratio SNR;

[0022]

[0023] When the signal-to-noise ratio is greater than 6, the N setting is reasonable. Otherwise, reduce the N value and repeat the test to calibrate the flow field until the N setting is reasonable.

[0024] The in-situ calibration method is:

[0025] Collect PSP images when the wind tunnel is stopped and PSP images when the wind tunnel is running;

[0026] Perform background denoising on two types of images;

[0027] The grayscale ratio operation values ​​of the two types of images are calculated according to the grayscale of the PSP pixels after the two types of images are denoised;

[0028] The grayscale ratio calculation values ​​of the two types of images are polynomially fitted with the pressure values ​​collected by the pressure sensor to determine the in-situ calibration coefficients.

[0029] After obtaining the in-situ calibration coefficient through in-situ calibration, the wind tunnel is parked and ground static calibration is performed. The ground static calibration results and the phosphorescence thermal image data collected synchronously with the fast response PSP are used to perform temperature error analysis to reduce the temperature error caused by the temperature effect of the pressure-sensitive coating in the wind tunnel test.

[0030] Before in-situ calibration, pressure-sensitive coating is coated on the surface of the aircraft column skirt model, while the surface of the pressure sensor is not coated.

[0031] PSP image in wind tunnel parking state PSP image in wind tunnel operation The grayscale ratio calculation value is i represents the sensor number (i=1,2,…,n); the in-situ calibration coefficients include A, B, and C, and the calculation method is:

[0032]

[0033] Where P ref is the pressure value of the sensor under the wind tunnel operation state, T is the temperature;

[0034] The temperature error analysis method is:

[0035] After the ground static calibration, the calibration coefficients A(T), B(T) and C(T) of the same pressure-sensitive paint samples at different temperatures are obtained, and the error band of the model surface pressure measurement results is given according to the temperature rise data of the model phosphorescence thermal map to complete the error analysis.

[0036] The method of directly linearly transforming back to three-dimensional pressure data is:

[0037] After obtaining the in-situ calibration coefficients based on the in-situ calibration, the full-field two-dimensional pressure data of the PSP can be obtained. The projection matrix is ​​calculated through direct linear transformation through the known three-dimensional points of the model and the corresponding two-dimensional PSP image projection points. Finally, the three-dimensional restoration of the two-dimensional PSP pressure data is achieved through the projection matrix.

[0038] The calculation method of the projection matrix is:

[0039] Get the projection matrix of known 3D points and 2D image projection points:

[0040]

[0041] Where [X,Y,Z,1] T is the world coordinate of a 3D point, [u,v,1]T is the corresponding image pixel coordinate; H is the projection matrix, and s is the depth of the three-dimensional point.

[0042] The advantages of the present invention compared with the prior art are:

[0043] The present invention provides a column skirt model shock wave boundary layer interference measurement method based on dynamic PSP, which can solve the PSP hardware synchronization, flow field self-luminous shielding, PSP pressure calibration and error analysis, and column skirt model three-dimensional pressure restoration problems in high Mach number environment, and finally obtain the shock wave / boundary layer interference wall pressure distribution characteristics of the column skirt model in the millisecond flow field. Compared with the traditional method of arranging pressure measuring points, this optical measurement method can achieve high-resolution full-field non-contact measurement. The use of fast-response PSP technology can realize dynamic unsteady measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A schematic diagram of a synchronous scheme for collecting shock tunnel signals provided by the present invention;

[0045] Figure 2 A flow chart of PSP data processing based on in-situ calibration provided by the present invention. DETAILED DESCRIPTION

[0046] A method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP is proposed. The method is based on a high Mach number column skirt model of an aircraft and is used to solve the problems of PSP hardware synchronization, flow field self-luminous shielding, PSP pressure calibration and error analysis, and three-dimensional pressure restoration of the column skirt model in a high Mach number environment. Finally, the shock wave / boundary layer interference wall pressure distribution characteristics of the column skirt model in a millisecond-level flow field are obtained, and high-resolution full-field non-contact measurement can be achieved. The fast-response PSP technology can be used to realize dynamic unsteady measurement.

[0047] The shock wave boundary layer interference measurement method of the column skirt model based on dynamic PSP includes the following steps:

[0048] Establish a high Mach millisecond wind tunnel flow field, and synchronously collect dynamic PSP images and high-frequency response pressure sensor data of the aircraft column skirt model in the wind tunnel flow field;

[0049] Shielding treatment of the self-luminescence of high Mach millisecond wind tunnel flow field;

[0050] Dynamic PSP in-situ calibration is performed based on the synchronously collected high-frequency response pressure sensor data to eliminate the influence of temperature effects, and temperature error analysis is performed using ground static calibration results and phosphorescence thermal map data;

[0051] The two-dimensional pressure data of the column skirt model in a wind tunnel flow field of high Mach numbers and milliseconds is measured and restored to three-dimensional pressure data through direct linear transformation. The pressure distribution characteristics of the shock wave boundary layer of the column skirt model are obtained based on the three-dimensional pressure data.

[0052] In the wind tunnel flow field, a PSP high-speed camera, a UV light source, a pressure sensor, and a synchronous controller are set up, including:

[0053] The synchronous controller receives the external pulse signal, generates a trigger signal and sends it to the PSP high-speed camera, ultraviolet light source and pressure sensor respectively; the PSP high-speed camera and ultraviolet light source receive the trigger signal to collect the PSP image, and the pressure sensor synchronously receives the trigger signal to collect the surface pressure of the model.

[0054] After receiving the external pulse signal, the synchronous controller sends a trigger signal to the PSP high-speed camera, ultraviolet light source, and pressure sensor after extending the specified time according to the preset delay.

[0055] The method for shielding the self-luminescence of the wind tunnel flow field is:

[0056] Eliminate the self-luminous image of the PSP image or filter the self-luminous image through a bandpass filter, where:

[0057] After the PSP image is acquired, the self-luminous image is acquired by turning off all light sources and then eliminated from the PSP image;

[0058] The method of filtering the spontaneous emission through a bandpass filter is:

[0059] A 650±Nnm bandpass filter was selected to filter the self-luminescence, and the collected image signal was filtered to reduce the PSP image noise and filter the self-luminescence.

[0060] N is obtained through experimental calibration, and the calibration method is:

[0061] After turning off all controllable light sources, the wind tunnel blows air to collect PSP images I (N) ;

[0062] Only the UV light source is turned on, and the wind tunnel blows air to collect PSP images, and I (S+N) , calculate the signal-to-noise ratio SNR;

[0063]

[0064] When the signal-to-noise ratio is greater than 6, the N setting is reasonable. Otherwise, reduce the N value and repeat the test to calibrate the flow field until the N setting is reasonable.

[0065] The in-situ calibration method is:

[0066] Collect PSP images when the wind tunnel is stopped and PSP images when the wind tunnel is running;

[0067] Perform background denoising on two types of images;

[0068] The grayscale ratio operation values ​​of the two types of images are calculated according to the grayscale of the PSP pixels after the two types of images are denoised;

[0069] The grayscale ratio calculation values ​​of the two types of images are polynomially fitted with the pressure values ​​collected by the pressure sensor to determine the in-situ calibration coefficients.

[0070] After in-situ calibration using the in-situ calibration coefficient, the wind tunnel is parked and ground static calibration is performed. The ground static calibration results and the phosphorescence thermal image data collected synchronously with the fast response PSP are used to perform temperature error analysis to reduce the temperature error caused by the temperature effect of the pressure-sensitive coating in the wind tunnel test.

[0071] Before in-situ calibration, pressure-sensitive coating is coated on the surface of the aircraft column skirt model, while the surface of the pressure sensor is not coated.

[0072] PSP image in wind tunnel parking state PSP image in wind tunnel operation The grayscale ratio calculation value is i represents the sensor number (i=1,2,…,n); the in-situ calibration coefficients include A, B, and C, and the calculation method is:

[0073]

[0074] Where P ref is the pressure value of the sensor under the wind tunnel operation state, T is the temperature;

[0075] The temperature error analysis method is:

[0076] After the ground static calibration, the calibration coefficients A(T), B(T) and C(T) of the same pressure-sensitive paint samples at different temperatures are obtained, and the error band of the model surface pressure measurement results is given according to the temperature rise data of the model phosphorescence thermal map to complete the error analysis.

[0077] The method of directly linearly transforming back to three-dimensional pressure data is:

[0078] After obtaining the in-situ calibration coefficients based on the in-situ calibration, the full-field two-dimensional pressure data of the PSP can be obtained. Through the known three-dimensional points of the model and the corresponding two-dimensional PSP image projection points, the projection matrix is ​​calculated through direct linear transformation. Finally, the three-dimensional restoration of the two-dimensional PSP pressure data is achieved through the projection matrix.

[0079] The projection matrix is ​​calculated as:

[0080] Get the projection matrix of known 3D points and 2D image projection points:

[0081]

[0082] Where [X,Y,Z,1] T is the world coordinate of a 3D point, [u,v,1] T is the corresponding image pixel coordinate. H is the projection matrix, and s is the depth of the three-dimensional point.

[0083] The following is further described in conjunction with the accompanying drawings and preferred embodiments of the specification:

[0084] In the current embodiment, if Figure 1 The figure shows the hardware structure of the shock wave boundary layer interference measurement of the column skirt model based on the dynamic PSP;

[0085] (1) The PSP hardware system is designed as follows: After the aircraft column skirt model is coated with paint, the operation time of the shock wave wind tunnel is generally a few milliseconds to tens of milliseconds, which is short. Therefore, the PSP high-speed camera, ultraviolet light source and high-frequency pressure sensor must be strictly synchronized. The synchronization strategy is shown in the figure below: After the flow field is established, the wind tunnel measurement and control system sends a high-level 5V TTL pulse signal to the synchronization controller. After the synchronization controller receives the pulse signal, it delays for a certain period of time and then sends a trigger signal to the high-speed camera, ultraviolet light source and pressure sensor. Among them, the delay time of the high-speed camera and the pressure sensor is the same, and the delay time of the ultraviolet light source is slightly longer. In this way, the synchronous acquisition of PSP images and pressure is achieved.

[0086] (2) Design of flow field self-luminous shielding scheme

[0087] Under high Mach number conditions, when the total temperature of the flow field is high, the flow field will have self-luminescence, which will interfere with the acquisition of the PSP image. There are two solutions. One is to subtract the self-luminescence image from the PSP image to eliminate the self-luminescence component. The self-luminescence image is acquired after turning off all controllable light sources. The other is to select a 650±Nnm bandpass filter to filter the self-luminescence, which can effectively reduce the PSP image noise. N is obtained through experimental calibration. The calibration method is to turn off all controllable light sources, blow air through the wind tunnel to acquire the PSP image, and obtain I (N) Then only the UV light source is turned on, and the wind tunnel blows air to collect the PSP image, and I (S+N) , calculate the signal-to-noise ratio SNR as:

[0088]

[0089] When the signal-to-noise ratio is greater than 6, the N setting is reasonable, otherwise reduce the N value and repeat the up-calibration process.

[0090] (3) In-situ calibration technology based on high-frequency response pressure sensor

[0091] In a high Mach number shock tunnel environment, the wind tunnel operation time is short and the temperature rise is small. When the total temperature of the incoming flow is high, the temperature effect of the pressure-sensitive coating cannot be ignored, that is, the fluorescence intensity of the stimulated radiation is related to both pressure and temperature. In order to eliminate the influence of the temperature effect of the pressure-sensitive coating, the high-frequency response pressure sensor data collected synchronously with the PSP data can be used for in-situ calibration, and the ground static calibration results can be used to assist the phosphorescence thermogram thermal measurement data for temperature error analysis. The PSP data processing flow based on in-situ calibration and temperature error analysis is as follows: Figure 2 As shown;

[0092] In-situ calibration: The grayscale ratio of the PSP pixels before and after the wind in a small area around the sensor is averaged to obtain i represents the sensor number (i=1,2,…,n), which is related to the pressure value P of the sensor. i Polynomial fitting is performed as shown in the following formula (2), and the calibration coefficients of pressure-sensitive paint A(T), B(T) and C(T) are obtained. The selection of the neighborhood size is crucial. Since the pressure sensor is not sprayed with PSP paint, it appears as a nearly circular black hole on the PSP image. Therefore, the neighborhood is selected as a ring neighborhood, and the inner circle should avoid the noise points at the edge of the pressure hole. These noise points are mainly caused by using tools such as paper clips to block the pressure hole to protect the pressure sensor when spraying the pressure-sensitive paint.

[0093]

[0094] Temperature error analysis: Temperature error analysis is performed based on the ground static calibration results and phosphorescent thermogram thermal measurement data. Static calibration of the same pressure-sensitive paint sample as the wind tunnel test is completed in the ground calibration chamber to obtain the pressure-sensitive paint calibration coefficients A(T), B(T) and C(T) at different temperatures. Then, based on the model temperature rise data of the phosphorescent thermogram, the error band of the wind tunnel pressure measurement results can be given to complete the temperature error analysis.

[0095] (4) Three-dimensional pressure restoration technology based on direct linear transformation

[0096] The two-dimensional pressure is restored to the three-dimensional column skirt digital model by using multiple three-dimensional points and their corresponding image projection points (3D-2D point pairs) to solve the projection matrix, and then the remaining three-dimensional points are mapped to the two-dimensional image. The direct linear transformation method is used to transform the projection transformation equation into a linear transformation equation that is easier to solve. The transformation process is as follows:

[0097] First, the projection transformation equation of the 3D-2D point pair is:

[0098]

[0099] Among them, [X,Y,Z,1] T is the world coordinate of a 3D point, [u,v,1] Tis the corresponding image pixel coordinate. H is the projection matrix, and s is the depth of the three-dimensional point.

[0100] Then, eliminating s, we get:

[0101]

[0102] Define the column vector of matrix H: h 1 =[h 1 ,h 2 ,h 3 ,h 4 ] T ,h 2 =[h 5 ,h 6 ,h 7 ,h 8 ] T ,h 3 =[h 9 ,h 10 ,h 11 ,h 12 ] T , therefore, the above formula (4) can be written as:

[0103] P T h 1 -uP T h 3 =0

[0104] P T h 2 -vP T h 3 =0 (5)

[0105] Further written in matrix form:

[0106]

[0107] Substitute h 1 =[h 1 ,h 2 ,h 3 ,h 4 ] T ,h 2 =[h 5 ,h 6 ,h 7 ,h 8 ] T ,h 3 =[h 9 ,h 10 ,h 11 ,h 12 ] T get:

[0108]

[0109] The above equation (7) has 12 unknowns and requires at least 6 3D-2D point pairs. Therefore, the linear transformation equation is:

[0110]

[0111] The above equation (8) is a linear equation system with Ax=0. Its approximate non-zero solution is solved by least squares, but it is impossible to directly solve the non-zero solution by linear least squares. At this time, the SVD decomposition method is used for approximate solution: A is decomposed by SVD, and the last column vector of V after decomposition is the least squares solution of Ax=0.

[0112] The high Mach number column skirt model shock wave boundary layer interference measurement method based on dynamic PSP can solve the problems of PSP hardware synchronization, flow field self-luminous shielding, PSP pressure calibration and error analysis, and three-dimensional pressure restoration of the column skirt model in a high Mach number environment, and finally obtain the flow pressure distribution characteristics of the shock wave / boundary layer interference zone of the column skirt model in the high Mach number millisecond flow field.

[0113] Although the present invention has been disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

[0114] The contents not described in detail in the specification of the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP, characterized in that include: Establish a high Mach millisecond wind tunnel flow field, and synchronously collect dynamic PSP images and high-frequency response pressure sensor data of the aircraft column skirt model in the wind tunnel flow field; Shielding treatment of the self-luminescence of high Mach millisecond wind tunnel flow field; Dynamic PSP in-situ calibration is performed based on the synchronously collected high-frequency response pressure sensor data to eliminate the influence of temperature effects, and temperature error analysis is performed using ground static calibration results and phosphorescence thermal map data; The two-dimensional pressure data of the column skirt model in a wind tunnel flow field of high Mach numbers and milliseconds is measured and restored to three-dimensional pressure data through direct linear transformation. The pressure distribution characteristics of the shock wave boundary layer of the column skirt model are obtained based on the three-dimensional pressure data.

2. The method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP according to claim 1 is characterized in that: In the wind tunnel flow field, a PSP high-speed camera, an ultraviolet light source, a pressure sensor, and a synchronous controller are arranged, wherein: The synchronous controller receives the external pulse signal, generates a trigger signal and sends it to the PSP high-speed camera, ultraviolet light source and pressure sensor respectively; the PSP high-speed camera and ultraviolet light source receive the trigger signal to collect the PSP image, and the pressure sensor synchronously receives the trigger signal to collect the surface pressure of the model.

3. The method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP according to claim 2 is characterized in that: After receiving the external pulse signal, the synchronous controller sends a trigger signal to the PSP high-speed camera, the ultraviolet light source, and the pressure sensor after extending the specified time according to the preset delay.

4. The method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP according to claim 2 is characterized in that: The method for shielding the self-luminescence of the wind tunnel flow field is: Eliminate the self-luminous image of the PSP image or filter the self-luminous image through a bandpass filter, where: After the PSP image is acquired, the self-luminous image is acquired by turning off all light sources and eliminated from the PSP image; The method of filtering the spontaneous emission through a bandpass filter is: A 650±Nnm bandpass filter was selected to filter the self-luminescence, and the collected image signal was filtered to reduce the PSP image noise and filter the self-luminescence.

5. The method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP according to claim 4 is characterized in that: N is obtained through experimental calibration, and the calibration method is: After turning off all controllable light sources, the wind tunnel blows air to collect PSP images I (N) ; Only the UV light source is turned on, and the wind tunnel blows air to collect PSP images, and I (S+N) , calculate the signal-to-noise ratio SNR; When the signal-to-noise ratio is greater than 6, the N setting is reasonable. Otherwise, reduce the N value and repeat the test to calibrate the flow field until the N setting is reasonable.

6. The method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP according to claim 4 is characterized in that: The in-situ calibration method is: Collect PSP images when the wind tunnel is stopped and PSP images when the wind tunnel is running; Perform background denoising on two types of images; The grayscale ratio operation values ​​of the two types of images are calculated according to the grayscale of the PSP pixels after the two types of images are denoised; The grayscale ratio calculation values ​​of the two types of images are polynomially fitted with the pressure values ​​collected by the pressure sensor to determine the in-situ calibration coefficients.

7. The method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP according to claim 6 is characterized in that: After obtaining the in-situ calibration coefficient through in-situ calibration, the wind tunnel is parked and ground static calibration is performed. The ground static calibration results and the phosphorescence thermal image data collected synchronously with the fast response PSP are used to perform temperature error analysis to reduce the temperature error caused by the temperature effect of the pressure-sensitive coating in the wind tunnel test. Before in-situ calibration, pressure-sensitive coating is coated on the surface of the aircraft column skirt model, while the surface of the pressure sensor is not coated.

8. The method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP according to claim 6 is characterized in that: PSP image in wind tunnel parking state PSP image in wind tunnel operation The grayscale ratio calculation value is i represents the sensor number (i=1,2,…,n); the in-situ calibration coefficients include A, B, and C, and the calculation method is: Where P ref is the pressure value of the sensor under the wind tunnel operation state, T is the temperature; The temperature error analysis method is: After the ground static calibration, the pressure-sensitive paint calibration coefficients A(T), B(T) and C(T) of the same pressure-sensitive paint samples at different temperatures are obtained, and the error band of the model surface pressure measurement results is given according to the temperature rise data of the model phosphorescence thermal map to complete the temperature error analysis.

9. The method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP according to claim 6 is characterized in that: The method of directly linearly transforming back to three-dimensional pressure data is: After obtaining the in-situ calibration coefficients based on the in-situ calibration, the full-field two-dimensional pressure data of the PSP can be obtained. Through the known three-dimensional points of the model and the corresponding two-dimensional PSP image projection points, the projection matrix is ​​calculated through direct linear transformation. Finally, the three-dimensional restoration of the two-dimensional PSP pressure data is achieved through the projection matrix.

10. The method for measuring shock wave boundary layer interference of a column skirt model based on dynamic PSP according to claim 9 is characterized in that: The calculation method of the projection matrix is: Get the projection matrix of known 3D points and 2D image projection points: Where [X,Y,Z,1] T is the world coordinate of a 3D point, [u,v,1] T is the corresponding image pixel coordinate; H is the projection matrix, and s is the depth of the three-dimensional point.

Images