Method and device for measuring section temperature and radiation characteristic parameter distribution

Abstract

The invention provides a method and device for measuring section temperature and radiation characteristic parameter distribution, and the method comprises the steps: carrying out the calculation of each unit of a section, so as to obtain the section temperature and radiation characteristic parameter distribution: carrying out the calculation of the section temperature and radiation characteristic parameter distribution based on a radiation intensity model and an image temperature model according to the simulated section temperature and simulated radiation characteristic parameters; determining an input radiation intensity and an input image temperature; setting initial section temperature and initial radiation characteristic parameters, and determining coefficient matrixes in the radiation intensity model and the image temperature model; determining an output section temperature according to a coefficient matrix in the image temperature model; determining output radiation intensity according to a coefficient matrix in the radiation intensity model; and iteratively updating the radiation characteristic parameter, comparing the output radiation intensity with the input radiation intensity, stopping iteration until an iteration termination condition is met, and determining the final corresponding radiation characteristic parameter and output section temperature. According to the invention, section temperature and radiation characteristic parameter distribution can be reliably given.

Description

Technical Field

[0001] The present invention relates to the field of spectral technology, and particularly to a method and device for measuring the distribution of cross-sectional temperature and radiation characteristic parameters. Background Art

[0002] During hypersonic flight, the high heat flux generated by supersonic combustion and aerodynamic heating makes the scramjet engine face a very harsh high-temperature environment. This severely limits the flight performance of the scramjet engine in the range of high Mach numbers. Therefore, it is necessary to accurately measure the combustion performance parameters of the scramjet engine to study the combustion state law in order to optimize the combustion system structure. In the high-temperature environment of the scramjet engine, radiation is the main heat transfer method, which is suitable for the measurement of the scramjet engine. However, the temperature and spectral radiation characteristic parameters are generally obtained by single-point measurement and calculation, and it is difficult to obtain the spatial distribution of the temperature and radiation characteristic parameters. Summary of the Invention

[0003] An object of an embodiment of the present invention is to provide a method and device for measuring the distribution of cross-sectional temperature and radiation characteristic parameters, which can reliably give the distribution of cross-sectional temperature and radiation characteristic parameters.

[0004] To achieve the above object, an embodiment of the present invention provides a method for measuring the distribution of cross-sectional temperature and radiation characteristic parameters. The method includes performing the following steps for each unit of the cross-section to obtain the distribution of cross-sectional temperature and radiation characteristic parameters: Based on the simulated cross-sectional temperature and simulated radiation characteristic parameters, and based on the radiation intensity model and the image temperature model, determine the input radiation intensity and the input image temperature; Set the initial cross-sectional temperature and the initial radiation characteristic parameters, and based on the input radiation intensity and the input image temperature, and based on the radiation intensity model and the image temperature model, determine the coefficient matrices in the radiation intensity model and the image temperature model; According to the coefficient matrix in the image temperature model and the input image temperature, determine the output cross-sectional temperature; According to the coefficient matrix in the radiation intensity model and the output cross-sectional temperature, determine the output radiation intensity; Iteratively update the radiation characteristic parameters through the radiation characteristic parameter iteration model to update the coefficient matrices of the image temperature model and the radiation intensity model, compare the output radiation intensity and the input radiation intensity, and stop the iteration until the iteration termination condition is met, and determine the final corresponding radiation characteristic parameters and the output cross-sectional temperature.

[0005] Preferably, the radiation intensity model is:

[0006]

[0007] wherein, I λ (i) is the input radiation intensity, A(i, j) is the coefficient matrix in the radiation intensity model, Rd，gI (j→i), R d，wI (j→i) represents the fraction of the total radiant energy emitted by the j-th wall or space element received by the i-th imaging unit per unit area and per unit angle. ΔV and ΔS represent the space element volume and the wall element area, ε is the emissivity, κ a represents the radiation absorption coefficient, and ε and κ a are radiation characteristic parameters, λ is the wavelength, C1 and C2 are the first and second Planck constants respectively, and T j is the cross-sectional temperature of the j-th wall or space element. g and w refer to the space and wall elements.

[0008] Preferably, the image temperature model is:

[0009]

[0010] A S T(i, j) = A(i, j) / K(i)

[0011]

[0012]

[0013] where T SC (i) is the input image temperature, A(i, j) is the coefficient matrix in the radiation intensity model, and A s (i, j) is the coefficient matrix in the image temperature model, and T j is the cross-sectional temperature of the j-th wall or space element.

[0014] Preferably, determining the output cross-sectional temperature according to the coefficient matrix of the image temperature model and the input image temperature includes: calculating the output cross-sectional temperature through the following formula:

[0015]

[0016] where D is the regularization matrix, α is the regularization parameter, T SC (i) is the input image temperature, and A s (i, j) is the coefficient matrix in the image temperature model.

[0017] Preferably, the radiation characteristic parameter iteration model is:

[0018]

[0019] where σ s is the radiation scattering coefficient, r is the number of iterations, I λ (i) is the input radiation intensity, ε is the emissivity, κ a represents the radiation absorption coefficient, and ε, κa 、 σ s is a radiation characteristic parameter.

[0020] An embodiment of the present invention further provides a device for measuring the cross-sectional temperature and the distribution of radiation characteristic parameters. The device includes: a forward calculation unit, a coefficient matrix calculation unit, a cross-sectional temperature calculation unit, a radiation intensity calculation unit, and an iteration unit. Among them, the forward calculation unit is used to determine the input radiation intensity and the input image temperature based on the simulated cross-sectional temperature and the simulated radiation characteristic parameters, and based on the radiation intensity model and the image temperature model; the coefficient matrix calculation unit is used to set the initial cross-sectional temperature and the initial radiation characteristic parameters, and determine the coefficient matrix in the radiation intensity model and the image temperature model according to the input radiation intensity and the input image temperature, based on the radiation intensity model and the image temperature model; the cross-sectional temperature calculation unit is used to determine the output cross-sectional temperature according to the coefficient matrix in the image temperature model and the input image temperature; the radiation intensity calculation unit is used to determine the output radiation intensity according to the coefficient matrix in the radiation intensity model and the output cross-sectional temperature; the iteration unit is used to iteratively update the radiation characteristic parameters through the radiation characteristic parameter iteration model to update the coefficient matrix of the image temperature model and the coefficient matrix of the radiation intensity model, compare the output radiation intensity and the input radiation intensity, and stop iterating until the iteration termination condition is met, and determine the final corresponding radiation characteristic parameters and the output cross-sectional temperature.

[0021] Preferably, the radiation intensity model is:

[0022]

[0023] Among them, I λ (i) is the input radiation intensity, A(i, j) is the coefficient matrix in the radiation intensity model, R d，gI (j→i), R d，wI (j→i) represents the share of the total radiation energy emitted by the jth wall surface and space unit received by the ith imaging unit per unit area and unit angle. ΔV and ΔS represent the space unit volume and the wall surface unit area, ε is the emissivity, κ a represents the radiation absorption coefficient, ε and κ a are radiation characteristic parameters, λ is the wavelength, C1 and C2 are the first and second Planck constants respectively, T j is the cross-sectional temperature of the jth wall surface and space unit, and g and w refer to the space and wall surface units.

[0024] Preferably, the image temperature model is:

[0025]

[0026] AS (i, j) = A(i, j) / K(i)

[0027]

[0028] where T SC (i) is the input image temperature, and A s (i, j) is the coefficient matrix in the image temperature model, and T j is the cross-sectional temperature of the j-th wall and spatial unit.

[0029] Preferably, the cross-sectional temperature calculation unit is configured to: calculate and output the cross-sectional temperature through the following formula:

[0030]

[0031] where D is the regularization matrix, α is the regularization parameter, and T SC (i) is the input image temperature, and A s (i, j) is the coefficient matrix in the image temperature model.

[0032] Preferably, the radiation characteristic parameter iteration model is:

[0033]

[0034] where σ s is the radiation scattering coefficient, r is the number of iterations, I λ (i) is the input radiation intensity, ε is the emissivity, and κ a represents the radiation absorption coefficient, and ε, κ a , and σ s are radiation characteristic parameters.

[0035] Through the above technical solutions, the embodiments of the present invention provide a method and device for measuring the cross-sectional temperature and the distribution of radiation characteristic parameters, which can reliably give the cross-sectional temperature and the distribution of radiation characteristic parameters.

[0036] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent specific implementation part. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The drawings are used to provide a further understanding of the embodiments of the present invention, and constitute a part of the specification, and are used to explain the embodiments of the present invention together with the following specific implementation, but do not constitute a limitation to the embodiments of the present invention. In the drawings:

[0038] Figure 1 is a flowchart of a method for measuring the cross-sectional temperature and the distribution of radiation characteristic parameters provided by an embodiment of the present invention;

[0039] Figure 2It is a layout diagram of a simulated camera provided by an embodiment of the present invention;

[0040] Figure 3a It is the set cross-sectional temperature distribution provided by an embodiment of the present invention;

[0041] Figure 3b It is the cross-sectional temperature distribution obtained by radiation calculation provided by an embodiment of the present invention.

[0042] Figure 4a It is a comparison diagram of the set cross-sectional absorption coefficient distribution and the cross-sectional absorption coefficient distribution obtained by radiation calculation provided by an embodiment of the present invention;

[0043] Figure 4b It is the relative error curve provided by an embodiment of the present invention;

[0044] Figure 5 It is a structural block diagram of a device for measuring the cross-sectional temperature and radiation characteristic parameter distribution provided by an embodiment of the present invention.

[0045] Description of reference numerals

[0046] 1 - Forward calculation unit, 2 - Coefficient matrix calculation unit, 3 - Cross-sectional temperature calculation unit, 4 - Radiation intensity calculation unit, 5 - Iteration unit Detailed implementation manners

[0047] The following details the specific implementation manners of the embodiments of the present invention with reference to the accompanying drawings. It should be understood that the specific implementation manners described herein are only used to illustrate and explain the embodiments of the present invention, and are not used to limit the embodiments of the present invention.

[0048] Figure 1 It is a flowchart of a method for measuring the cross-sectional temperature and radiation characteristic parameter distribution provided by an embodiment of the present invention. As Figure 1 shown, the method includes performing the following steps for each unit of the cross-section to obtain the cross-sectional temperature and radiation characteristic parameter distribution:

[0049] The present invention selects a suitable grid model and iteratively fits the cross-sectional temperature and radiation characteristic parameter distribution based on the DRESOR method.

[0050] Step S101, based on the simulated cross-sectional temperature and simulated radiation characteristic parameters, determine the input radiation intensity and input image temperature based on the radiation intensity model and the image temperature model;

[0051] Specifically, the spectral radiation intensity received by the multispectral imaging device mainly includes the following parts: direct emission from the wall unit; reflection from the wall unit; direct emission from the space medium unit; scattering from the space medium unit. As shown in Equation (1):

[0052]

[0053] Among them, is the detected directional radiation path intensity, represents the radiation intensity direction, r w and r w ' represent different wall units, r, r', r" represent different spatial units, s, s', s" represent different paths, W and V represent the wall and space, ds' is the infinitesimal path length, dA' is the infinitesimal wall area, dV" is the infinitesimal spatial volume, I b is the blackbody radiation intensity, is the DRESOR number, β is the attenuation coefficient, and w is the extinction coefficient.

[0054] Discretize the integral term in Equation (1). Divide the calculation plane into m grid cells, divide the wall into n grid cells, and divide the camera into I line-of-sight directions (pixel cells). Equation (1) can be rewritten as the following equation:

[0055]

[0056] Among them, the DRESOR number R d，gI (j→i), R d，wI (j→i) represents the fraction of the total radiant energy emitted by the j-th wall and spatial unit received by the i-th imaging unit per unit area and unit angle. σ is the Stefan-Boltzmann constant, T is the temperature, ε is the emissivity, the subscripts g and w refer to the spatial and wall units, ΔV and ΔS represent the spatial unit volume and the wall unit area, κ a represents the radiation absorption coefficient. In this way, the radiation intensity received by the camera is rewritten as a function only related to the temperature and DRESOR number in the system. Among them, the DRESOR number is determined by the system shape and the radiation parameter distribution and can be calculated by the Monte Carlo method.

[0057] Considering the response characteristics of the camera to the received radiation wavelength, replace the source term σT 4 in Equation (2) with the spectral radiation intensity C1λ -5 exp(-C2 / (λT)) (Wien radiation law) to obtain Equation (3):

[0058]

[0059] In the formula, λ is the wavelength, and C1 and C2 are the first and second Planck constants respectively. Perform a matrix transformation on Equation (3) to obtain the radiation intensity model:

[0060]

[0061] Among them, I λ(i) is the input radiation intensity, A(i, j) is the coefficient matrix in the radiation intensity model, and R d，gI (j→i), R d，wI (j→i) represents the fraction of the total radiant energy emitted by the j-th wall or space element received by the i-th imaging unit per unit area and per unit angle. ΔV and ΔS represent the volume of the space element and the area of the wall element respectively. ε is the emissivity, and κ a represents the radiation absorption coefficient. ε and κ a are radiation characteristic parameters. λ is the wavelength, C1 and C2 are the first and second Planck constants respectively, and T j is the cross-sectional temperature of the j-th wall or space element. g and w refer to the space and wall elements respectively.

[0062] The image temperature model is as follows:

[0063]

[0064] A S (i, j) = A(i, j) / K(i) (8)

[0065]

[0066] where, T SC (i) is the input image temperature, A(i, j) is the coefficient matrix in the radiation intensity model, and A s (i, j) is the coefficient matrix in the image temperature model, and T j is the cross-sectional temperature of the j-th wall or space element.

[0067] By setting the simulated cross-sectional temperature and simulated radiation characteristic parameters under the simulated working conditions, based on the above models, the input radiation intensity and the input image temperature can be determined.

[0068] Step S102: Set the initial cross-sectional temperature and initial radiation characteristic parameters. According to the input radiation intensity and the input image temperature, based on the radiation intensity model and the image temperature model, determine the coefficient matrices in the radiation intensity model and the image temperature model;

[0069] Specifically, after obtaining the input radiation intensity and the input image temperature, the initial cross-sectional temperature and initial radiation characteristic parameters can be set, and substituting them into the radiation intensity model and the image temperature model to calculate the coefficient matrix A(i, j) in the radiation intensity model and the coefficient matrix A s (i, j).

[0070] Step S103: Determine the output cross-sectional temperature according to the coefficient matrix in the image temperature model and the input image temperature;

[0071] Specifically, the output cross-section temperature is calculated by the following formula:

[0072]

[0073] where D is the regularization matrix, α is the regularization parameter, T SC (i) is the input image temperature, and A s (i, j) is the coefficient matrix in the image temperature model.

[0074] The values of the regularization matrix D and the regularization parameter α are determined by the following formula. Here, T0 represents the solution of Equation (7) in the least squares sense.

[0075] α ≈ 2||T SC -A S T0|| 2 / ||DT SC，0 || 2 (12)

[0076] Step S104: Determine the output radiation intensity according to the coefficient matrix in the radiation intensity model and the output cross-section temperature;

[0077] Specifically, substitute the output cross-section temperature into T in Equation (6) j to calculate E λ (j), and then calculate the output radiation intensity through Equation (4).

[0078] Step S105: Iteratively update the radiation characteristic parameters through the radiation characteristic parameter iteration model to update the coefficient matrices of the image temperature model and the radiation intensity model. Compare the output radiation intensity and the input radiation intensity, and stop the iteration until the iteration termination condition is satisfied, and determine the final corresponding radiation characteristic parameters and output cross-section temperature.

[0079] Specifically, after obtaining the output radiation intensity, compare the output radiation intensity with the input radiation intensity. If the relative error between the two is less than 0.05, stop the iteration. At this time, the radiation characteristic parameters and the output cross-section temperature used are the final ones to be obtained.

[0080] If the relative error between the two is greater than or equal to 0.05, perform iteration through the radiation characteristic parameter iteration model, that is, increment r by 1:

[0081]

[0082] where σ s is the radiation scattering coefficient, r is the number of iterations, I λ (i) is the input radiation intensity, ε is the emissivity, and κ a represents the radiation absorption coefficient, and ε, κ a , σs are radiation characteristic parameters.

[0083] After iteration, new radiation characteristic parameters are obtained, and then the initial radiation characteristic parameters in the above text are replaced, and the above steps are executed again until the relative error between the output radiation intensity and the input radiation intensity is less than 0.05 or the number of iterations reaches the set upper limit of 200, then the iteration is stopped, and the final corresponding radiation characteristic parameters and the output section temperature are determined.

[0084] The present invention provides an embodiment as follows:

[0085] A 10*10 cm cross-sectional square area is selected as the research object. The wall temperature is set to 1000 K, the emissivity is set to 1.0, and the cross-sectional space is divided into 10*10 grid cells. The positions of the simulated cameras are as Figure 2 shown. Among them, the field of view angles of the three cameras are all 150°, and the distance from the wall is 1 cm.

[0086] Ignoring scattering, taking the spectral radiation intensity along the pixel points of the three simulated cameras and the pixel distribution of the image temperature as input information, iterative calculations are performed. Figure 3a and Figure 3b respectively give the set cross-sectional temperature distribution and the cross-sectional temperature distribution obtained by radiation calculation. Figure 4a gives a comparison between the set cross-sectional absorption coefficient distribution and the cross-sectional absorption coefficient distribution obtained by radiation calculation. Figure 4b gives the relative error curve of the calculated cross-sectional absorption coefficient distribution based on the set cross-sectional absorption coefficient distribution.

[0087] From Figure 4b it can be seen that the calculated cross-sectional absorption coefficient distribution is close to the set reference, and the maximum error is less than 4%, which proves the accuracy of the method.

[0088] Figure 5 is the structural block diagram of the device for measuring the cross-sectional temperature and the distribution of radiation characteristic parameters provided by an embodiment of the present invention. As Figure 5As shown, the device includes: a forward calculation unit 1, a coefficient matrix calculation unit 2, a cross-section temperature calculation unit 3, a radiation intensity calculation unit 4, and an iteration unit 5. Among them, the forward calculation unit 1 is used to determine the input radiation intensity and the input image temperature based on the simulated cross-section temperature and the simulated radiation characteristic parameters, according to the radiation intensity model and the image temperature model; the coefficient matrix calculation unit 2 is used to set the initial cross-section temperature and the initial radiation characteristic parameters, and determine the coefficient matrix in the radiation intensity model and the image temperature model according to the input radiation intensity and the input image temperature, based on the radiation intensity model and the image temperature model; the cross-section temperature calculation unit 3 is used to determine the output cross-section temperature according to the coefficient matrix in the image temperature model and the input image temperature; the radiation intensity calculation unit 4 is used to determine the output radiation intensity according to the coefficient matrix in the radiation intensity model and the output cross-section temperature; the iteration unit 5 is used to iteratively update the radiation characteristic parameters through the radiation characteristic parameter iteration model to update the coefficient matrix of the image temperature model and the coefficient matrix of the radiation intensity model, compare the output radiation intensity with the input radiation intensity, and stop the iteration until the iteration termination condition is met, and output the corresponding cross-section temperature and radiation characteristic parameters.

[0089] Preferably, the radiation intensity model is:

[0090]

[0091] Where, I λ (i) is the input radiation intensity, A(i, j) is the coefficient matrix in the radiation intensity model, R d，gI (j→i), R d，wI (j→i) represents the share of the total radiation energy emitted by the jth wall and space unit received by the ith imaging unit per unit area and unit angle, ΔV and ΔS represent the space unit volume and the wall unit area, ε is the emissivity, κ a represents the radiation absorption coefficient, ε and κ a are radiation characteristic parameters, λ is the wavelength, C1 and C2 are the first and second Planck constants respectively, T j is the cross-section temperature of the jth wall and space unit, and g and w refer to the space and wall units.

[0092] Preferably, the image temperature model is:

[0093]

[0094] A S (i, j) = A(i, j) / K(i)

[0095]

[0096] Among them, T SC (i) is the input image temperature, and A s (i, j) is the coefficient matrix in the image temperature model, and T j is the cross-sectional temperature of the j-th wall and space unit.

[0097] Preferably, the cross-sectional temperature calculation unit 3 is configured to: calculate and output the cross-sectional temperature through the following formula:

[0098]

[0099] Among them, D is the regularization matrix, α is the regularization parameter, and T SC (i) is the input image temperature, and A s (i, j) is the coefficient matrix in the image temperature model.

[0100] Preferably, the radiation characteristic parameter iteration model is:

[0101]

[0102] Among them, σ s is the radiation scattering coefficient, r is the number of iterations, I λ (i) is the input radiation intensity, ε is the emissivity, and κ a represents the radiation absorption coefficient, and ε, κ a , σ s are the radiation characteristic parameters.

[0103] The embodiments of the device for measuring the cross-sectional temperature and the distribution of radiation characteristic parameters described above are similar to those of the method for measuring the cross-sectional temperature and the distribution of radiation characteristic parameters described above, and will not be elaborated here.

[0104] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0105] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices produce means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0106] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that implement the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0107] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are performed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0108] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0109] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0110] A computer-readable medium includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer 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, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer-readable medium does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0111] It should also be noted that the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article or apparatus comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or apparatus. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising the element.

[0112] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for measuring cross-sectional temperature and radiation characteristic parameter distribution, characterized in that: The method includes performing the following steps for each unit of the cross section to obtain the distribution of cross section temperature and radiation characteristic parameters: According to the simulated cross-sectional temperature and the simulated radiation characteristic parameters, based on the radiation intensity model and the image temperature model, the input radiation intensity and the input image temperature are determined; Setting an initial cross-sectional temperature and an initial radiation characteristic parameter, and determining coefficient matrices in the radiation intensity model and the image temperature model according to the input radiation intensity and the input image temperature, based on the radiation intensity model and the image temperature model; Determining an output cross-sectional temperature according to a coefficient matrix in the image temperature model and the input image temperature; Determining the output radiation intensity according to the coefficient matrix in the radiation intensity model and the output cross-sectional temperature; The radiation characteristic parameters are iteratively updated through the radiation characteristic parameter iteration model to update the coefficient matrix of the image temperature model and the coefficient matrix of the radiation intensity model, and the output radiation intensity and the input radiation intensity are compared until the iteration termination condition is met, and the iteration is stopped to determine the final corresponding radiation characteristic parameters and output cross-sectional temperature.

2. The method for measuring cross-sectional temperature and radiation characteristic parameter distribution according to claim 1, characterized in that: The radiation intensity model is: Among them, I λ (i) is the input radiation intensity, A(i, j) is the coefficient matrix in the radiation intensity model, R d，gI (j→i), R d，wI (j→i) represents the fraction of the total radiation energy emitted by the jth wall and space unit received by the ith imaging unit per unit area and unit angle, ΔV and ΔS represent the volume of the space unit and the area of ​​the wall unit, ε is the emissivity, κ a represents the radiation absorption coefficient, ε and κ a is the radiation characteristic parameter, λ is the wavelength, C1 and C2 are Planck's first and second constants respectively, T j is the cross-sectional temperature of the jth wall and space unit, g and w refer to the space and wall units.

3. The method for measuring cross-sectional temperature and radiation characteristic parameter distribution according to claim 1, characterized in that: The image temperature model is: A S (i,j)=A(i,j) / K(i) Among them, T SC (i) is the input image temperature, A(i, j) is the coefficient matrix in the radiation intensity model, A s (i, j) is the coefficient matrix in the image temperature model, T j is the cross-sectional temperature of the jth wall and space unit.

4. The method for measuring cross-sectional temperature and radiation characteristic parameter distribution according to claim 1, characterized in that: Determining the output cross-sectional temperature according to the coefficient matrix of the image temperature model and the input image temperature comprises: The output section temperature is calculated by the following formula: Where D is the regularization matrix, α is the regularization parameter, and T SC (i) is the input image temperature, A s (i,j) is the coefficient matrix in the image temperature model.

5. The method for measuring cross-sectional temperature and radiation characteristic parameter distribution according to claim 1, characterized in that: The radiation characteristic parameter iteration model is: Among them, σ s is the radiation scattering coefficient, r is the number of iterations, I λ (i) is the input radiation intensity, ε is the emissivity, κ a represents the radiation absorption coefficient, ε, κ a , σ s is the radiation characteristic parameter.

6. A device for measuring cross-sectional temperature and radiation characteristic parameter distribution, characterized in that: The device includes: Forward calculation unit, coefficient matrix calculation unit, cross-section temperature calculation unit, radiation intensity calculation unit and iteration unit, wherein, The forward calculation unit is used to determine the input radiation intensity and the input image temperature according to the simulated cross-sectional temperature and the simulated radiation characteristic parameters, based on the radiation intensity model and the image temperature model; The coefficient matrix calculation unit is used to set the initial cross-sectional temperature and the initial radiation characteristic parameters, and determine the coefficient matrix in the radiation intensity model and the image temperature model according to the input radiation intensity and the input image temperature, based on the radiation intensity model and the image temperature model; The cross-section temperature calculation unit is used to determine the output cross-section temperature according to the coefficient matrix in the image temperature model and the input image temperature; The radiation intensity calculation unit is used to determine the output radiation intensity according to the coefficient matrix in the radiation intensity model and the output cross-sectional temperature; The iteration unit is used to iteratively update the radiation characteristic parameters through the radiation characteristic parameter iteration model to update the coefficient matrix of the image temperature model and the coefficient matrix of the radiation intensity model, compare the output radiation intensity with the input radiation intensity, stop the iteration until the iteration termination condition is met, and determine the final corresponding radiation characteristic parameters and output cross-sectional temperature.

7. The device for measuring cross-sectional temperature and radiation characteristic parameter distribution according to claim 6, characterized in that: The radiation intensity model is: Among them, I λ (i) is the input radiation intensity, A(i, j) is the coefficient matrix in the radiation intensity model, R d，gI (j→i), R d，wI (j→i) represents the fraction of the total radiation energy emitted by the jth wall and space unit received by the ith imaging unit per unit area and unit angle, ΔV and ΔS represent the volume of the space unit and the area of ​​the wall unit, ε is the emissivity, κ a represents the radiation absorption coefficient, ε and κ a is the radiation characteristic parameter, λ is the wavelength, C1 and C2 are Planck's first and second constants respectively, T j is the cross-sectional temperature of the jth wall and space unit, g and w refer to the space and wall units.

8. The device for measuring cross-sectional temperature and radiation characteristic parameter distribution according to claim 6, characterized in that: The image temperature model is: A S (i,j)=A(i,j) / K(i) Among them, T SC (i) is the input image temperature, A s (i, j) is the coefficient matrix in the image temperature model, which is the cross-sectional temperature of the jth wall and space unit.

9. The device for measuring cross-sectional temperature and radiation characteristic parameter distribution according to claim 6, characterized in that: The cross-section temperature calculation unit is used for: The output section temperature is calculated by the following formula: Where D is the regularization matrix, α is the regularization parameter, and T SC (i) is the input image temperature, A s (i, j) is the coefficient matrix in the image temperature model.

10. The device for measuring cross-section temperature and radiation characteristic parameter distribution according to claim 6, characterized in that: The radiation characteristic parameter iteration model is: Among them, σ s is the radiation scattering coefficient, r is the number of iterations, I λ (i) is the input radiation intensity, ε is the emissivity, κ a represents the radiation absorption coefficient, ε, κ a , σ s is the radiation characteristic parameter.

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