A method and system for measuring heat flux on the surface of an arc tunnel test model
By combining a coaxial calorimeter and an infrared thermal imager, the problem of measuring heat flux density distribution under high-temperature conditions in an electric arc wind tunnel was solved, enabling more accurate quantitative measurement of heat flux distribution and reducing the difficulty and deviation of heat measurement.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA ACAD OF AEROSPACE AERODYNAMICS
- Filing Date
- 2026-03-20
- Publication Date
- 2026-06-12
AI Technical Summary
Existing technologies make it difficult to achieve high-precision measurement of the overall distribution of heat flux density on the surface of an electric arc wind tunnel test model, especially under high-temperature conditions. Contact measurement methods are limited, and non-contact heat measurement technologies cannot meet the requirements for long-term heat flux measurement.
By combining a coaxial calorimeter and an infrared thermal imager, a mapping relationship, calibration factor distribution, and failure criteria of the thermal conductivity model are established to determine the effective time period. The calibration factor is then used to calibrate the surface temperature data across the entire field and correct the heat flux density distribution.
It enables more accurate quantitative measurement of heat flow distribution in the complex environment of electric arc wind tunnel, reduces the threshold and difficulty of heat measurement applications, and eliminates measurement deviations caused by changes in material thermophysical properties.
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Figure CN122192694A_ABST
Abstract
Description
Technical Field
[0001] This document relates to the field of aerodynamic thermal testing and measurement research on aircraft ground, and in particular to a method and system for measuring surface heat flow of an electric arc wind tunnel test model. Background Technology
[0002] In arc wind tunnel aerodynamic thermal protection tests, heat flux density is one of the most important measurement parameters. Currently, mainstream measurement methods mainly rely on contact testing methods, such as plug calorimeters, Gordon calorimeters, and coaxial calorimeters. While contact measurements offer high accuracy, they only provide limited discrete-point heat flux data. For complex local interference zones such as shock waves, boundary layers, gaps, wing surfaces, and protrusions in hypersonic vehicles, the limited data obtained by contact methods cannot reflect the overall distribution of local aerodynamic heating. Furthermore, due to the spatial limitations of coaxial calorimeters, their heat flux measurements are spatially averaged and cannot reflect peak heat flux, thus limiting their applicability to such measurement needs. Non-contact optical calorimetry methods, such as infrared thermography and phosphorescent thermography, can provide quantitative information on the entire two-dimensional / three-dimensional thermal environment and are widely used in pulsed shock tunnels. However, these methods are used in pulsed wind tunnels with sub-millisecond to millisecond testing times, resulting in minimal temperature rise on the model surface, which can be considered as isothermal walls, and the material's thermophysical parameters can be treated as constants. Applying infrared calorimetry directly to arc wind tunnels faces significant challenges: First, the long measurement time and hot wall effect. The measurement time in arc wind tunnels is typically on the order of 10⁻¹⁰⁰ seconds. Within this time period, the model surface temperature rises rapidly, reaching over 1000 K under extreme conditions, making it impossible to satisfy the isothermal wall assumption. Material thermal properties change, the testing time increases, and the lateral thermal conductivity effect in metal measurements is significant, posing a considerable challenge to heat flow data algorithm inversion. Therefore, from the perspective of practical engineering needs and the development of high-enthalpy wind tunnel calorimetry technology, there is an urgent need to develop spatially resolved surface heat flow measurement methods for arc wind tunnel experiments. Summary of the Invention
[0003] This specification provides one or more embodiments of a method for measuring surface heat flow of an electric arc wind tunnel test model, including: S1: Send the thermal model into the high enthalpy flow field of the electric arc wind tunnel, and collect the heat flow data of multiple coaxial calorimeters arranged on the surface of the thermal model and the surface temperature data of the model across the entire field obtained by the infrared thermal imager. S2: Establish a mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the thermal model, and extract the average surface temperature history of each coaxial calorimeter at the corresponding position from the full-field surface temperature data according to the mapping relationship. S3: Based on the preset failure criteria of the thermal conductivity model, determine the effective time period for heat flow inversion, and within the effective time period, use the heat flow data at each coaxial calorimeter location and the corresponding surface temperature history to establish a calibration factor distribution; S4: Using the calibration factor distribution, the full-field surface temperature data is calibrated to obtain the full-field hot wall heat flux density distribution on the model surface; S5: Based on the total enthalpy of the high enthalpy flow field and the full-field surface temperature data, the full-field hot wall heat flux density distribution is corrected to the full-field cold wall heat flux density distribution.
[0004] Furthermore, the heat measurement model is a metallic material with known thermal conductivity and isotropic properties, and the coaxial calorimeter is installed at a typical location on the heat measurement model; The outer surface of the thermal model and the sensing surface of the coaxial calorimeter are coated with a high-temperature resistant black paint with an emissivity ranging from 0.9 to 0.95 and a thickness ranging from 20 to 50 μm.
[0005] Furthermore, the method for determining the effective time period is as follows: ; in, This is for measuring the local radius of curvature or minimum wall thickness of the thermal model; The thermal diffusivity of the metal matrix is . The safety factor is set to a value between 10 and 20.
[0006] Furthermore, within the effective time period, the specific method for establishing the calibration factor distribution using the heat flow data and corresponding surface temperature history at each coaxial calorimeter location is as follows: Based on preset uniform material parameters, the full-field surface temperature data is processed using a one-dimensional semi-infinite thermal conductivity algorithm to obtain an uncalibrated pseudo heat flux distribution. For each coaxial calorimeter location, the ratio of the heat flux data to the pseudo heat flux data at the corresponding location is calculated to obtain the calibration factor for that location. Using the coordinates of all coaxial calorimeter positions and their corresponding calibration factors, a calibration factor distribution covering the surface of the calorimetric model is generated through a spatial interpolation algorithm; the spatial interpolation algorithm is an Nth-order polynomial fitting method or a thin-plate spline interpolation fitting method, where N≥2.
[0007] Furthermore, the calibration factor distribution is used to calibrate the full-field surface temperature data to obtain the full-field hot-wall heat flux density distribution of the model surface. The specific method is shown in the following formula: ; in, The hot wall heat flux density at position (x,y) at time t; The calibration factor for position (x,y); The pseudo heat flux is calculated using a one-dimensional semi-infinite thermal conductivity algorithm based on the full-field surface temperature data.
[0008] Furthermore, based on the total enthalpy of the high-enthalpy flow field and the overall surface temperature data, the specific method for correcting the overall hot-wall heat flux density distribution to the overall cold-wall heat flux density distribution is as follows:
[0009] in, For cold wall heat flow; The total enthalpy of the flow field; The enthalpy of cold wall is taken as 0.3 MJ / kg; To measure the hot wall enthalpy of the heat model; The temperature rise across the entire field is obtained using infrared technology.
[0010] Furthermore, in the process of establishing the mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the thermal model, it is first necessary to match the time axis of the data collected by the infrared thermal imager and the data collected by the coaxial calorimeter, specifically as follows: Take the derivatives of the heat flux data and surface temperature data with respect to time: , ,based on , The local characteristics of both are used to calculate the optimal lag time using the cross-correlation function. Therefore, the surface temperature data at time t Perform time shift correction.
[0011] Furthermore, the specific process includes: Let X = Y= The data is then discretized to obtain discrete data vectors X[n] and Y[n], respectively. Define cross-correlation function :
[0012] K is the number of lag steps; and , where are the average values of the discrete data vectors; N is the number of vectors; Determine the optimal number of lag steps k opt and time
[0013] .
[0014] Furthermore, the measurement frequency f of the coaxial calorimeter and infrared thermal imager is not less than 1 kHz.
[0015] This specification provides one or more embodiments of a surface heat flow measurement system for an electric arc wind tunnel test model, comprising: Data acquisition module: used to send the heat measurement model into the high enthalpy flow field of the electric arc wind tunnel, and to collect heat flow data from multiple coaxial calorimeters arranged on the surface of the heat measurement model and the full-field surface temperature data of the model obtained by the infrared thermal imager. The first calculation module is used to establish the mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the heat measurement model, and to extract the average surface temperature history of each coaxial calorimeter at the corresponding position from the full-field surface temperature data according to the mapping relationship. Calibration factor distribution establishment module: It is used to determine the effective time period for heat flow inversion based on the preset failure criteria of the thermal conductivity model, and to establish the calibration factor distribution within the effective time period using the heat flow data and the corresponding surface temperature history of each coaxial calorimeter position. Calibration module: used to calibrate the full-field surface temperature data using the calibration factor distribution to obtain the full-field hot wall heat flux density distribution on the model surface; Correction module: used to correct the heat flux density distribution of the hot wall to the heat flux density distribution of the cold wall based on the total enthalpy of the high enthalpy flow field and the surface temperature data of the whole field.
[0016] This specification provides one or more embodiments of an electronic device, including: Processor; and, A memory is configured to store computer-executable instructions, which, when executed, cause the processor to implement the steps of the above-described method for measuring surface heat flux of an electric arc wind tunnel test model.
[0017] This specification provides one or more embodiments of a storage medium for storing computer-executable instructions that, when executed, implement the steps of the above-described method for measuring surface heat flux of an electric arc wind tunnel test model.
[0018] The heat flow testing method proposed in this invention can expand the thermal measurement capabilities of electric arc wind tunnels and is an effective supplement to current thermal measurement methods. Based on existing metal thermal measurement models and algorithm corrections, it lowers the threshold and difficulty of electric arc wind tunnel thermal measurement applications and has strong engineering feasibility. Through coaxial thermal measurement correction, time axis alignment, and noise-resistant data processing algorithms, it eliminates measurement deviations caused by parameters such as emissivity, window transmittance, and changes in material thermal properties, enabling more accurate quantitative measurement of heat flow distribution in the complex electromagnetic and interference environment of electric arc wind tunnels.
[0019] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description
[0020] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0021] Figure 1 A flowchart illustrating a method for measuring surface heat flow of an electric arc wind tunnel test model, provided for one or more embodiments of this specification; Figure 2 A schematic diagram of the composition of a surface heat flow measurement system for an electric arc wind tunnel test model provided for one or more embodiments of this specification; Figure 3 This is a schematic diagram of the structure of an electronic device provided for one or more embodiments of this specification. Detailed Implementation
[0022] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.
[0023] Method Implementation Examples According to an embodiment of the present invention, a method for measuring surface heat flow of an electric arc wind tunnel test model is provided. Figure 1 A flowchart illustrating a method for measuring surface heat flow of an electric arc wind tunnel test model, provided for one or more embodiments of this specification, is shown below. Figure 1 As shown, the surface heat flow measurement method of the electric arc wind tunnel test model according to an embodiment of the present invention specifically includes: S1: The thermal model is sent into the high enthalpy flow field of the electric arc wind tunnel, and the heat flow data of multiple coaxial calorimeters arranged on the surface of the thermal model and the surface temperature data of the model across the entire field are collected by the infrared thermal imager.
[0024] In the electric arc wind tunnel test, the thermal model was rapidly pushed to the center of the high-enthalpy flow field by the feeding mechanism, and the data acquisition system was simultaneously triggered at the instant the model began to enter the flow field to capture the entire process of the thermal response on the model surface and obtain the heat flux density change of the coaxial calorimeter. Infrared thermal imager full-field infrared temperature In this embodiment, a thermally conductive and isotropic metallic material is selected to fabricate the thermal measurement model. i coaxial calorimeters (i≥2) are installed at typical locations on the thermal measurement model. A coating is sprayed onto the outer surface of the thermal measurement model and the sensing surface of the coaxial calorimeters. The coating is a high-temperature resistant, high-emissivity coating; in this embodiment, high-temperature resistant black paint is used, with an emissivity range controlled between 0.9 and 0.95, and a coating thickness range of 20-50 μm.
[0025] Multiple coaxial calorimeters arranged on the model surface record local heat flux density data in real time at a high frame rate of no less than 1 kHz, while an infrared thermal imager continuously acquires surface temperature distribution images of the entire model at a high frame rate of no less than 1 kHz.
[0026] S2: Establish a mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the thermal model, and extract the average surface temperature history of each coaxial calorimeter at the corresponding position from the full-field surface temperature data according to the mapping relationship.
[0027] In establishing the mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the thermal model, it is first necessary to match the time axes of the data collected by the infrared thermal imager and the data collected by the coaxial calorimeter. Specifically, it is necessary to compare the dynamic change trend of the measured heat flow signal of the coaxial calorimeter with the dynamic change trend of the temperature signal extracted by the infrared thermal imager in the corresponding pixel area. By analyzing the local characteristics of both at the moment of abrupt change, the optimal lag time between them is calculated, and the time axis of the infrared temperature data is shifted and corrected accordingly to ensure that the two types of data strictly correspond in time history. The specific calculation method is as follows: Take the derivatives of the heat flux data and surface temperature data with respect to time: , Let X = Y= The data is then discretized to obtain discrete data vectors X[n] and Y[n], respectively. Define cross-correlation function : ; Where K is the number of lag steps; and , where are the average values of the discrete data vectors; N is the number of vectors; based on , The local characteristics of both are used to calculate the optimal lag time using the cross-correlation function. Therefore, the surface temperature data at time t Perform time shift correction, and determine the optimal number of lag steps k. opt and time The method is as follows: .
[0028] Establish a mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the thermal model, and identify the first... The average surface temperature history of each sensor is extracted from the corresponding region in the infrared image. .
[0029] S3: Based on the preset failure criteria of the thermal conductivity model, determine the effective time period for heat flow inversion, and within the effective time period, establish the calibration factor distribution using the heat flow data and corresponding surface temperature history at each coaxial calorimeter location.
[0030] Failure criteria based on the one-dimensional semi-infinite thermal conductivity assumption of the metal matrix determine the effective time period for full-field heat flow inversion. The method for determining this is as follows: ; in, This is for measuring the local radius of curvature or minimum wall thickness of the thermal model; The thermal diffusivity of the metal matrix is . The safety factor is set to a value between 10 and 20.
[0031] Within a defined effective time period, the heat flow data from each coaxial calorimeter location are used. With the corresponding surface temperature history Establish calibration factor distribution The specific method is as follows: Assuming uniform material parameters across the entire field, a one-dimensional semi-infinite thermal conductivity algorithm is used to analyze the temperature data across the entire field. The process yields an uncalibrated pseudo-heat flux. distributed; For each coaxial calorimeter location The ratio of the heat flux data to the pseudo heat flux data at the corresponding location is calculated to obtain the calibration factor for that location. ; Using the coordinates of all coaxial calorimeter positions and its corresponding calibration factor A calibration factor distribution covering the surface of the thermal model is generated using a spatial interpolation algorithm. The spatial interpolation algorithm is an Nth-order polynomial fitting method or a thin-plate spline interpolation fitting method, where N≥2.
[0032] S4: Using the calibration factor distribution, the full-field surface temperature data is calibrated to obtain the full-field hot wall heat flux density distribution on the model surface.
[0033] Using the calibration factor distribution For the full-field surface temperature data The calibration process was performed to obtain the full-field hot-wall heat flux density distribution on the model surface. The specific method is shown in the following formula: ; in, The hot wall heat flux density at position (x,y) at time t; The calibration factor for position (x,y); The pseudo heat flux is calculated using a one-dimensional semi-infinite thermal conductivity algorithm based on the full-field surface temperature data.
[0034] S5: Based on the total enthalpy of the high enthalpy flow field and the full-field surface temperature data, the full-field hot wall heat flux density distribution is corrected to the full-field cold wall heat flux density distribution.
[0035] Based on the total enthalpy H of the high enthalpy flow field o and the full-field surface temperature data The full-field hot wall heat flux density distribution Corrected to full-field cold wall heat flux density distribution The specific method is as follows: ; in, For cold wall heat flow; The total enthalpy of the flow field; The enthalpy of cold wall is taken as 0.3 MJ / kg; To measure the hot wall enthalpy of the heat model; The total temperature rise obtained from infrared measurements. Total enthalpy of the flow field. It is obtained by back-calculation using stagnation pressure and stagnation heat flux.
[0036] In this embodiment, the heat flux data processing uses the modified Cook-Felderman formula: ; For step S1, The value range is [8500, 8900], in step S3 Take 1; This is for surface temperature rise correction.
[0037] The beneficial effects of this invention are as follows: The heat flow testing method proposed in this invention can expand the thermal measurement capabilities of electric arc wind tunnels and is an effective supplement to current thermal measurement methods. Based on existing metal thermal measurement models and algorithm corrections, it lowers the threshold and difficulty of electric arc wind tunnel thermal measurement applications and has strong engineering feasibility. Through coaxial thermal measurement correction, time axis alignment, and noise-resistant data processing algorithms, it eliminates measurement deviations caused by parameters such as emissivity, window transmittance, and changes in material thermal properties, enabling more accurate quantitative measurement of heat flow distribution in the complex electromagnetic and interference environment of electric arc wind tunnels.
[0038] System Implementation Examples According to an embodiment of the present invention, a surface heat flow measurement system for an electric arc wind tunnel test model is provided. Figure 2 A schematic diagram illustrating the composition of a surface heat flow measurement system for an electric arc wind tunnel test model, provided for one or more embodiments of this specification, is shown below. Figure 2 As shown, the surface heat flow measurement system of the electric arc wind tunnel test model according to an embodiment of the present invention specifically includes: Data acquisition module 20: used to send the heat measurement model into the high enthalpy flow field of the electric arc wind tunnel, and to collect the heat flow data of multiple coaxial calorimeters arranged on the surface of the heat measurement model and the surface temperature data of the model across the entire field obtained by the infrared thermal imager. First calculation module 22: used to establish the mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the heat measurement model, and extract the average surface temperature history of each coaxial calorimeter at the corresponding position from the full-field surface temperature data according to the mapping relationship. Calibration factor distribution establishment module 24: is used to determine the effective time period for heat flow inversion based on the preset failure criteria of the thermal conductivity model, and to establish the calibration factor distribution within the effective time period using the heat flow data and corresponding surface temperature history of each coaxial calorimeter position; Calibration module 26: used to calibrate the full-field surface temperature data using the calibration factor distribution to obtain the full-field hot wall heat flux density distribution of the model surface; Correction module 28: used to correct the heat flux density distribution of the hot wall to the heat flux density distribution of the cold wall based on the total enthalpy of the high enthalpy flow field and the surface temperature data of the whole field.
[0039] The embodiments of the present invention are system embodiments corresponding to the above method embodiments. The specific operation of each module can be understood by referring to the description of the method embodiments, and will not be repeated here.
[0040] Device Example 1 This invention provides an electronic device, such as... Figure 3As shown, it includes: a memory 30, a processor 32, and a computer program stored in the memory 30 and executable on the processor 32. When the computer program is executed by the processor 32, it performs the following method steps: S1: Send the thermal model into the high enthalpy flow field of the electric arc wind tunnel, and collect the heat flow data of multiple coaxial calorimeters arranged on the surface of the thermal model and the surface temperature data of the model across the entire field obtained by the infrared thermal imager. S2: Establish a mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the thermal model, and extract the average surface temperature history of each coaxial calorimeter at the corresponding position from the full-field surface temperature data according to the mapping relationship. S3: Based on the preset failure criteria of the thermal conductivity model, determine the effective time period for heat flow inversion, and within the effective time period, use the heat flow data at each coaxial calorimeter location and the corresponding surface temperature history to establish a calibration factor distribution; S4: Using the calibration factor distribution, the full-field surface temperature data is calibrated to obtain the full-field hot wall heat flux density distribution on the model surface; S5: Based on the total enthalpy of the high enthalpy flow field and the full-field surface temperature data, the full-field hot wall heat flux density distribution is corrected to the full-field cold wall heat flux density distribution.
[0041] Device Example 2 This invention provides a computer-readable storage medium storing an information transmission implementation program. When executed by a processor 32, the program performs the following method steps: S1: Send the thermal model into the high enthalpy flow field of the electric arc wind tunnel, and collect the heat flow data of multiple coaxial calorimeters arranged on the surface of the thermal model and the surface temperature data of the model across the entire field obtained by the infrared thermal imager. S2: Establish a mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the thermal model, and extract the average surface temperature history of each coaxial calorimeter at the corresponding position from the full-field surface temperature data according to the mapping relationship. S3: Based on the preset failure criteria of the thermal conductivity model, determine the effective time period for heat flow inversion, and within the effective time period, use the heat flow data at each coaxial calorimeter location and the corresponding surface temperature history to establish a calibration factor distribution; S4: Using the calibration factor distribution, the full-field surface temperature data is calibrated to obtain the full-field hot wall heat flux density distribution on the model surface; S5: Based on the total enthalpy of the high enthalpy flow field and the full-field surface temperature data, the full-field hot wall heat flux density distribution is corrected to the full-field cold wall heat flux density distribution.
[0042] The computer-readable storage media described in this embodiment include, but are not limited to, ROM, RAM, disk, or optical disk.
[0043] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for measuring surface heat flux of an electric arc wind tunnel test model, characterized in that, include: S1: Send the thermal model into the high enthalpy flow field of the electric arc wind tunnel, and collect the heat flow data of multiple coaxial calorimeters arranged on the surface of the thermal model and the surface temperature data of the model across the entire field obtained by the infrared thermal imager. S2: Establish a mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the thermal model, and extract the average surface temperature history of each coaxial calorimeter at the corresponding position from the full-field surface temperature data according to the mapping relationship. S3: Based on the preset failure criteria of the thermal conductivity model, determine the effective time period for heat flow inversion, and within the effective time period, use the heat flow data at each coaxial calorimeter location and the corresponding surface temperature history to establish a calibration factor distribution; S4: Using the calibration factor distribution, the full-field surface temperature data is calibrated to obtain the full-field hot wall heat flux density distribution on the model surface; S5: Based on the total enthalpy of the high enthalpy flow field and the full-field surface temperature data, the full-field hot wall heat flux density distribution is corrected to the full-field cold wall heat flux density distribution.
2. The method according to claim 1, characterized in that, The heat measurement model is a metallic material with known thermal conductivity and isotropic properties, and the coaxial calorimeter is installed at a typical location on the heat measurement model. The outer surface of the thermal model and the sensing surface of the coaxial calorimeter are coated with a high-temperature resistant black paint with an emissivity ranging from 0.9 to 0.95 and a thickness ranging from 20 to 50 μm.
3. The method according to claim 1, characterized in that, The method for determining the effective time period is as follows: ； in, This is for measuring the local radius of curvature or minimum wall thickness of the thermal model; The thermal diffusivity of the metal matrix is . The safety factor is set to a value between 10 and 20.
4. The method according to claim 1, characterized in that, Within the effective time period, the specific method for establishing the calibration factor distribution using the heat flow data and corresponding surface temperature history at each coaxial calorimeter location is as follows: Based on preset uniform material parameters, the full-field surface temperature data is processed using a one-dimensional semi-infinite thermal conductivity algorithm to obtain an uncalibrated pseudo heat flux distribution. For each coaxial calorimeter location, the ratio of the heat flux data to the pseudo heat flux data at the corresponding location is calculated to obtain the calibration factor for that location. Using the coordinates of all coaxial calorimeter positions and their corresponding calibration factors, a calibration factor distribution covering the surface of the calorimetric model is generated through a spatial interpolation algorithm; the spatial interpolation algorithm is an Nth-order polynomial fitting method or a thin-plate spline interpolation fitting method, where N≥2.
5. The method according to claim 1, characterized in that, The calibration factor distribution is used to calibrate the full-field surface temperature data, and the specific method for obtaining the full-field hot-wall heat flux density distribution of the model surface is shown in the following formula: ； in, The hot wall heat flux density at position (x,y) at time t; The calibration factor for position (x,y); The pseudo heat flux is calculated using a one-dimensional semi-infinite thermal conductivity algorithm based on the full-field surface temperature data.
6. The method according to claim 1, characterized in that, Based on the total enthalpy of the high-enthalpy flow field and the full-field surface temperature data, the specific method for correcting the full-field hot wall heat flux density distribution to the full-field cold wall heat flux density distribution is as follows: in, For cold wall heat flow; The total enthalpy of the flow field; The enthalpy of cold wall is taken as 0.3 MJ / kg; To measure the hot wall enthalpy of the heat model; The temperature rise across the entire field is obtained using infrared technology.
7. The method according to claim 1, characterized in that, In the process of establishing the mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the thermal model, it is first necessary to match the time axis of the data collected by the infrared thermal imager and the data collected by the coaxial calorimeter, specifically as follows: Take the derivatives of the heat flux data and surface temperature data with respect to time: , ,based on , The local characteristics of both are used to calculate the optimal lag time using the cross-correlation function. Therefore, the surface temperature data at time t Perform time shift correction.
8. The method according to claim 7, characterized in that, The specific process includes: Let X = Y= The data is then discretized to obtain discrete data vectors X[n] and Y[n], respectively. Define cross-correlation function : K is the number of lag steps; and , where are the average values of the discrete data vectors; N is the number of vectors; Determine the optimal number of lag steps k opt and time 。 9. The method according to claim 1, characterized in that, The measurement frequency f of the coaxial calorimeter and infrared thermal imager is not less than 1 kHz.
10. A surface heat flux measurement system for an electric arc wind tunnel test model, characterized in that, include: Data acquisition module: used to send the heat measurement model into the high enthalpy flow field of the electric arc wind tunnel, and to collect heat flow data from multiple coaxial calorimeters arranged on the surface of the heat measurement model and the full-field surface temperature data of the model obtained by the infrared thermal imager. The first calculation module is used to establish the mapping relationship between the pixel coordinates of the infrared image and the surface coordinates of the heat measurement model, and to extract the average surface temperature history of each coaxial calorimeter at the corresponding position from the full-field surface temperature data according to the mapping relationship. Calibration factor distribution establishment module: It is used to determine the effective time period for heat flow inversion based on the preset failure criteria of the thermal conductivity model, and to establish the calibration factor distribution within the effective time period using the heat flow data and the corresponding surface temperature history of each coaxial calorimeter position. Calibration module: used to calibrate the full-field surface temperature data using the calibration factor distribution to obtain the full-field hot wall heat flux density distribution on the model surface; Correction module: used to correct the heat flux density distribution of the hot wall to the heat flux density distribution of the cold wall based on the total enthalpy of the high enthalpy flow field and the surface temperature data of the whole field.