Flow field tomography reconstruction method, system, device, storage medium and program product

Abstract

The present invention relates to the field of optical tomography technology and provides a flow field tomography reconstruction method, system, device, storage medium and program product. The method comprises: establishing a dual-line joint solution equation and merging it into a single optimization equation; introducing a hybrid regularization constraint into the single optimization equation to establish a hybrid regularized dual-line joint solution calculation mathematical model; based on the hybrid regularized dual-line joint solution calculation mathematical model, setting a non-negative criterion for the absorption coefficient, introducing temperature prior information of the flow field, and obtaining a hybrid regularized solution mathematical model with a temperature limit prior constraint; solving the hybrid regularized solution mathematical model with a temperature limit prior constraint to obtain the absorption coefficient, and using the absorption coefficient to calculate the temperature distribution of the flow field. Utilizing the method of the present invention, regularization constraints can be implemented on the flow field temperature reconstruction results, and at the same time, strong constraints are imposed on the calculation solution by introducing multiple physical prior information, thereby significantly improving the accuracy of flow field tomography reconstruction.

Description

Technical Field

[0001] The present invention belongs to the technical field of optical tomography, and in particular relates to a flow field tomography reconstruction method, system, device, storage medium and program product. Background Art

[0002] Linear tomography combined with dual-line thermometry is widely used to reconstruct temperatures and concentrations in various combustion fields. When the temperature distribution is reconstructed using dual-line tomography, the concentration distribution can be quantitatively calculated using the absorption coefficient distribution of one of the absorption lines and the Beer-Lambert metric. However, in linear dual-line tomography, the absorption coefficient distributions of the two absorption lines are calculated independently, making temperature reconstruction extremely sensitive to experimental noise and tomographic calculation errors, resulting in non-physical artifacts or localized distortion in the tomographic reconstruction results. These issues become more severe when projection information is insufficient or sparse. In addition, the noise immunity and temperature sensitivity range of the selected spectral line pair also directly affect the reconstruction results.

[0003] A possible approach to improve the reconstruction accuracy of dual-line tomography is to solve the dual-line problem jointly and introduce ratio constraints. Summary of the Invention

[0004] To solve the above problems, the present invention provides a flow field tomography reconstruction method, system, device, storage medium and program product, which jointly and synchronously solve the absorption coefficients of two absorption lines, and introduce hybrid regularization into the absorption coefficient distribution and the absorption coefficient ratio distribution to simulate the random pulsation of each result respectively.

[0005] The present invention can be implemented by the following scheme:

[0006] In a first aspect, an embodiment of the present invention provides a flow field tomography reconstruction method, comprising:

[0007] Select two absorption lines, jointly solve the absorption coefficients of the two absorption lines, establish a two-line joint solution equation and merge them into a single optimization equation;

[0008] Introducing hybrid regularization constraints into a single optimization equation, and establishing a hybrid regularized dual-line joint solution computational mathematical model;

[0009] Based on the hybrid regularization dual-line joint solution calculation mathematical model, the non-negative absorption coefficient criterion is set, and the temperature prior information of the flow field is introduced to obtain the hybrid regularization solution mathematical model with temperature limit prior constraints;

[0010] The mixed regularization mathematical model with temperature limit prior constraints is solved to obtain the absorption coefficient, which is then used to calculate the temperature distribution of the flow field.

[0011] As a preferred method,

[0012] The two absorption lines are the near-infrared band center frequencies of water molecules, the main combustion product of hydrocarbon fuels, at 7185.597 cm -1 and 7444.352 cm -1 absorption lines.

[0013] As a preferred method,

[0014] Hybrid regularization is a combination of Tikhonov Regularization and TV Regularization.

[0015] As a preferred method,

[0016] The mathematical model for the hybrid regularized dual-line joint solution includes three parts: the first part is the computational fidelity term, the second part is the hybrid regularization term for each absorption line, and the third part is the hybrid regularization term for the absorption coefficient ratio distribution.

[0017] As a preferred method,

[0018] The mathematical model is solved jointly by two lines with hybrid regularization, and the empirical regularization weight parameters are selected to balance the importance of each sample.

[0019] As a preferred method,

[0020] The absorption coefficient is used to calculate the temperature distribution of the flow field, including:

[0021] The target reconstruction area is discretized into multiple grid cells, and the thermophysical parameters in each grid cell are considered to be uniformly distributed;

[0022] Calculate the temperature value of each grid cell according to the ratio of the absorption coefficients of the two absorption lines;

[0023] The temperature distribution of the flow field is obtained by integrating the temperature values of all grid cells.

[0024] In a second aspect, based on the same inventive concept, an embodiment of the present invention further provides a flow field tomography reconstruction system, the system comprising an absorption coefficient joint solution module, a hybrid regularization module, a priori constraint module, and a solution calculation module;

[0025] The absorption coefficient joint solution module is used to: select two absorption lines, jointly solve the absorption coefficients of the two absorption lines, establish a two-line joint solution equation and merge it into a single optimization equation;

[0026] The hybrid regularization module is used to introduce hybrid regularization constraints into a single optimization equation and establish a hybrid regularized dual-line joint solution calculation mathematical model;

[0027] The prior constraint module is used to: solve the mathematical model based on the dual-line joint solution of hybrid regularization, set the non-negative criterion of the absorption coefficient, and introduce the temperature prior information of the flow field to obtain the hybrid regularization solution mathematical model with the temperature limit prior constraint;

[0028] The solution calculation module is used to solve the mixed regularization solution mathematical model with temperature limit prior constraints to obtain the absorption coefficient, and use the absorption coefficient to calculate the temperature distribution of the flow field.

[0029] In a third aspect, based on the same inventive concept, an embodiment of the present invention further provides an electronic device, comprising at least one processor and at least one memory electrically connected;

[0030] The memory is electrically connected to the processor, wherein the memory stores instructions that can be executed by at least one of the processors, and the instructions are executed by at least one of the processors to enable at least one of the processors to perform any of the flow field tomography reconstruction methods described above.

[0031] In a fourth aspect, based on the same inventive concept, an embodiment of the present invention further provides a computer storage medium, wherein the computer readable storage medium stores a computer program;

[0032] When the computer program is executed by a processor, any of the aforementioned flow field tomography reconstruction methods is implemented.

[0033] In a fifth aspect, based on the same inventive concept, an embodiment of the present invention further provides a computer program product, wherein the computer program product is stored in at least one storage medium;

[0034] The computer program product includes several instructions for causing at least one electronic device to execute any of the aforementioned flow field tomography reconstruction methods.

[0035] Compared with the prior art, the present invention has the following advantages:

[0036] 1. The dual-line joint solution solves the drawback of the traditional independent solution that cannot establish a connection. At the same time, adding a ratio can indirectly control the temperature field;

[0037] 2. Introducing a hybrid regularization penalty method to cope with various complex flow configurations;

[0038] 3. In addition to adding the non-negative criterion of the absorption coefficient, the calculation process also incorporates physical information of the temperature limit to impose strong constraints on the solution and improve the reconstruction accuracy.

[0039] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1 A flow chart of a flow field tomography reconstruction method according to an embodiment of the present invention is shown;

[0042] Figure 2 The curve showing the variation of the intensity of the absorption line spectrum and its ratio with temperature in the embodiment of the present invention is shown;

[0043] Figure 3 The figure shows the simulation results of tomographic reconstruction of three combustion field models using different calculation methods according to an embodiment of the present invention;

[0044] Figure 4 The results show the effect of different projection angles on the Figure 3 Image errors of tomographic reconstruction simulations using different calculation methods for three combustion field models: (a) Gaussian configuration, (b) top hat configuration, and (c) mixed configuration;

[0045] Figure 5 Shown Figure 3 Temperature reconstruction results of the three combustion field models for experimental tests on the Mckenna combustion flame: (a) is the reconstruction result of the present invention, (b) is the ART reconstruction result, and (c) is the Tikhonov reconstruction result;

[0046] Figure 6 Shown Figure 3 Comparison of thermocouple measurement data and experimental tomography results for three combustion field models;

[0047] Figure 7 A schematic structural diagram of an electronic device according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0049] The flow field tomography reconstruction method of the present invention is applicable to different temperature measurement absorption line pairs of different components. The two absorption spectral lines should have greatly different low-state energy levels and have strong spectral line intensity within the flow field temperature range to be measured.

[0050] For the sake of explanation, a double-line example is given as follows: water molecules, the main combustion product of hydrocarbon fuels, are selected as the target, and the temperature absorption line (absorption spectrum line) is 7185.597 cm -1 and 7444.352 cm -1 The spectral line pair (7185.597cm -1 and 7444.352 cm -1 is the center frequency of the spectral line, which is the near-infrared band), and has sufficient temperature measurement sensitivity within the temperature range of the hydrocarbon fuel combustion flow field.

[0051] Figure 1 A flow field schematic diagram of a flow field tomography reconstruction method according to an embodiment of the present invention is shown.

[0052] Assume that the absorption coefficients of the two selected absorption lines are α ν1 、 α ν2 , the least squares solutions of the following equations can be solved by Tikhonov Regularization (Tikhonov regularization / Tikhonov regularization / Ridge regression):

[0053] ,

[0054] in: μR ( α ν ) is a regularization term that controls the degree of smoothness; W Is the projection weight matrix, whose elements are the path lengths of the laser when it passes through a specific grid. Once the optical path arrangement is determined, W Matrices can be calculated using algebraic geometric relationships; A is the integrated absorbance, which can be obtained by nonlinear fitting of the experimental spectrum by the Voigt function of the spectrum.

[0055] When the frequency is v [cm-1 When the laser beam passes through the target area, its intensity decreases along the optical path due to the absorption effect of water molecules. L [cm] decay. This process can be quantitatively described by Beer-Lambert's law as the integrated absorbance A ν,i [cm -1 ], which can be expressed as follows:

[0056] ,

[0057] in: I 0 is the incident light intensity; I t is the transmitted light intensity; i Indicates the i beam path; j Indicates the j grids; α ν,j [cm -2 ]= P j X j S ( T j ) is the frequency v [cm -1 ] absorption coefficient; P [atm] is the local pressure; X is the mole fraction of absorbed gas; S ( T )[cm -2 atm -1 ] is the temperature-dependent spectral line intensity.

[0058] The absorption coefficient is detailed below α ν1 、 α ν2 The solution process:

[0059] In the two-line joint solution method, the system of equations Merge into a single optimization equation to calculate the double-line absorption coefficient distribution with the minimum error between the double-line integral value and the measured value. The single optimization equation after the merger is:

[0060] ,

[0061] Which contains α ν1 , α ν2 Regularization term for two variables R ( α ν1 ,α ν2 ), which can ensure the reliable calculation solution of the single optimization equation and suppress the fluctuation of the dual-line temperature measurement.

[0062] Tikhonov Regularization and Total-Variation Regularization (TV Regularization) are two classic regularization methods. Tikhonov Regularization is suitable for images with smooth distributions but not for scenes with sharp gradient boundaries. TV Regularization is advantageous in removing image noise while preserving image edges.

[0063] For the above single optimization equation, this embodiment uses a mixture of Tikhonov Regularization and TVRegularization regularization methods to perform hybrid regularization constraints on the dual-line ratio distribution and the absorption coefficient distributions, and establishes the following hybrid regularized dual-line joint solution calculation mathematical model:

[0064] ,

[0065] in: is the regularization weight parameter.

[0066] The above hybrid regularized two-line joint solution computational mathematical model suppresses image noise while maintaining true gradient boundaries. The first row (part 1) of the model is the computational fidelity term, the second row (part 2) is the hybrid regularization term for each absorption line, and the third row (part 3) is the hybrid regularization term for the absorption coefficient ratio distribution. The second row (part 2) ensures the accuracy of each absorption coefficient distribution solution, facilitating subsequent concentration distribution calculations. The third row (part 3) determines the distribution characteristics of the two-line ratio, directly controlling the final temperature distribution.

[0067] The hybrid regularized two-line joint solution calculation mathematical model requires the selection of appropriate regularization weight parameters to balance the contribution of each part.

[0068] In this example, by pre-solving multiple representative flow field distribution cases, we empirically determined regularization weight parameters with high reconstruction accuracy. This example provides a set of reliable empirical regularization weight parameters for both the noise-free and 2% noise levels, as shown in Table 1.

[0069] Table 1

[0070]

[0071] Where: e represents the power of 10.

[0072] It should be noted that cross-validation is also a feasible method for selecting regularization weight parameters, but its computational complexity is large. In addition, the selection of regularization weight parameters can also be assisted by artificial intelligence methods such as machine learning. The reference regularization parameters provided in Table 1 are applicable to the water molecule line pairs used in this embodiment. Other line selection methods can be optimized according to any of the aforementioned feasible methods.

[0073] In addition, the physical prior information of the combustion flow field can be used to constrain the computational solution. For example, for the traditional computational method, the set of equations , the non-negative criterion of the absorption coefficient can be set for constraint solving.

[0074] Specifically, in addition to the non-negative absorption coefficient criterion, this embodiment also introduces temperature prior information of the flow field for constraint.

[0075] Figure 2 The absorption line 7185.597 cm selected in this example is plotted. -1 and 7444.352 cm -1 The curve of spectral line intensity and double line ratio changing with temperature.

[0076] from Figure 2 As can be seen from the figure, the ratio of the selected absorption line pairs increases monotonically with increasing temperature in the range of 273 K to 2000 K. Therefore, when the upper and lower limits of the flow field temperature are known, the double-line ratio can be set to R The temperature limit further constrains the aforementioned hybrid regularized two-line joint solution computational mathematical model.

[0077] The mathematical model of hybrid regularization solution with temperature limit prior constraints is:

[0078] ,

[0079] It should be noted that the temperature limit of the combustion flow field can be obtained through other optical measurement methods, computational fluid dynamics simulation (CFD), or thermocouple measurement.

[0080] Solve the mixed regularization mathematical model with temperature limit prior constraints and obtain the optimal solution, namely the absorption coefficient α ν1 , α ν2 .

[0081] When the absorption coefficients of the two absorption lines α ν1 、 α ν2 After calculation, the local temperature of the combustion flow fieldR j It can be calculated from the ratio of the absorption coefficients and expressed as follows:

[0082] ,

[0083] Where: h [J∙s] is Planck’s constant; c [cm∙s -1 ] is the speed of light; k [J∙K -1 ] is the Boltzmann constant; E " [cm -1 ] is the low-state energy level of the spectral line; T 0[K] is the reference temperature.

[0084] By transforming the above local temperature formula, we can get the temperature T j The calculation expression is:

[0085] ,

[0086] Solving for temperature T j The temperature distribution of the flow field can be obtained by using the calculation expression of

[0087] According to this embodiment, regularization constraints can be imposed on the flow field temperature reconstruction results, and strong constraints can be imposed on the computational solution by introducing a variety of physical prior information, which can significantly improve the accuracy of tomographic reconstruction and provide a new calculation method for dual-line temperature measurement tomography technology.

[0088] Control Example

[0089] First, a hybrid regularized dual-line joint solution combustion flow field tomographic reconstruction method proposed in the present invention is simulated and tested, and compared with traditional reconstruction algorithms, including ART (Algebra Reconstruction Technique) and Tikhonov Regularization.

[0090] The flow field models used for testing include Gaussian, top-hat, and hybrid configurations. The flow field temperature and water molecule concentration use the same configuration, with the temperature distribution ranging from 400 K to 1800 K and the water molecule concentration ranging from 0.01 to 0.15. The target reconstruction area is discretized into a 20 × 20 grid cell with a grid resolution of 1 cm. Four projection angles are used, with 20 equally spaced beams set at each angle. The specific simulation process includes the following steps:

[0091] Step 1: simulate the absorbance of each grid in the simulation flow field model through the HITRAN database.

[0092] Step 2: Absorption weight matrix determined by light path arrangement W The absorption spectra of all beams passing through the target area are calculated based on the element size in .

[0093] Step 3: Use the Voigt spectral model to fit the simulated absorption spectrum and obtain the integrated absorbance of the target absorption line.

[0094] In step 4, the integrated absorbance vectors of the two absorption lines obtained from step 3 are substituted into the aforementioned "hybrid regularized solution mathematical model with temperature limit prior constraints" for optimal solution. It should be noted that only the non-negativity criterion constraint of the absorption coefficient was added during the simulation.

[0095] Step 5: Combine the calculated absorption coefficient distribution of the two absorption lines with the aforementioned "temperature T j Calculate the temperature distribution using the calculation expression of ".

[0096] Under the above simulation reconstruction steps, the combustion flow fields of the three configurations were reconstructed and the reconstruction results are as follows: Figure 3 It can be seen that the reconstruction performance of the combustion flow field tomographic reconstruction method proposed by the present invention using a hybrid regularized dual-line joint solution is significantly better than other methods, effectively suppressing reconstruction artifacts and improving the reconstruction accuracy of high-temperature areas.

[0097] In order to quantitatively evaluate the accuracy level of each method under different numbers of projection angles, the image error of each reconstruction result was calculated, such as Figure 4 As shown in the figure, the reconstruction error of all methods decreases with the increase in the number of projection angles. The ART and Tikhonov Regularization reconstruction methods have similar accuracy levels. However, the hybrid regularized dual-line joint solution combustion flow field tomographic reconstruction method proposed in this paper significantly reduces the reconstruction error. After the number of projector angles reaches 4, the reconstruction error is less than 2.5%, and even within 1%. This accuracy level is also much higher than the calculation results in similar literature.

[0098] Verification Example

[0099] To verify that the hybrid regularized dual-line combined solution combustion flow field tomographic reconstruction method proposed in the present invention also has an improvement effect in actual application, this embodiment is further illustrated by experimental measurement.

[0100] The experimental measurement object is a flat flame produced by a standard McKenna burner, and the measurement height is 5 mm above the burner. The experiment uses four projection angles, with 25 equally spaced beams arranged at each angle, and a resolution of 4 mm. The flame fuel is CH4 / air premixed gas, where the methane flow rate is set to 1.31 L / min and the air flow rate is set to 15.6 L / min. The equivalence ratio can be calculated to be 0.8. To stabilize the flame, the flow rate of the accompanying nitrogen shielding gas is set to 20 L / min. Two lasers with central wavelengths of 1392 nm and 1343 nm are used to obtain the water molecule at 7185.597 cm by time division multiplexing. -1 and 7444.352cm -1 There are two absorption lines at .

[0101] The experimental absorption spectrum is obtained by detecting the laser intensity and baseline fitting. Then, the experimental data is processed according to steps 3 to 5 in the control example, and the two-dimensional distribution of the temperature at 5 mm above the McKenna burner is finally reconstructed. The experimental reconstruction results are shown in Figure 2. Figure 5 shown.

[0102] Experimental results show that the hybrid regularized dual-line joint solution combustion flow field tomographic reconstruction method proposed in this invention can also effectively suppress reconstruction artifacts in actual application and restore the flat characteristics of the central area of the McKenna combustion flame to the greatest extent.

[0103] In order to verify the experimental reconstruction effect of the dual-line combined solution of the combustion flow field tomographic reconstruction method proposed in this invention, thermocouple measurements were carried out. The radial direction ( X = 0 mm) and compared with the experimental reconstruction results, such as Figure 6 The results show that the present invention effectively reconstructs the temperature of the central area of the combustion flame and accurately restores the thermal gradient boundary generated by heat transfer, which is basically consistent with the trend of the thermocouple measurement results.

[0104] Based on the above method, an embodiment of the present invention further provides a flow field tomography reconstruction system corresponding to the above method, wherein the system includes an absorption coefficient joint solution module, a hybrid regularization module, a priori constraint module, and a solution calculation module;

[0105] The absorption coefficient joint solution module is used to: select two absorption lines, jointly solve the absorption coefficients of the two absorption lines, establish a two-line joint solution equation and merge it into a single optimization equation;

[0106] The hybrid regularization module is used to introduce hybrid regularization constraints into a single optimization equation and establish a hybrid regularized dual-line joint solution calculation mathematical model;

[0107] The prior constraint module is used to: solve the mathematical model based on the dual-line joint solution of hybrid regularization, set the non-negative criterion of the absorption coefficient, and introduce the temperature prior information of the flow field to obtain the hybrid regularization solution mathematical model with the temperature limit prior constraint;

[0108] The solution calculation module is used to solve the mixed regularization solution mathematical model with temperature limit prior constraints to obtain the absorption coefficient, and use the absorption coefficient to calculate the temperature distribution of the flow field.

[0109] Based on the same inventive concept as disclosed above, the present invention also provides an electronic device. Figure 7 As shown, the electronic device of an embodiment of the present invention includes at least one electrically connected processor and at least one memory, wherein the memory is electrically connected to the processor, wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method as described above.

[0110] It should be noted that the electrical connection between the above-mentioned units does not necessarily mean the connection between lines. An indirect connection method is applicable to the embodiments of the present invention as long as the purpose of the present invention is achieved.

[0111] Based on the same inventive concept, the present invention further provides a computer storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0112] Based on the same inventive concept, the present invention further provides a computer program product, which is stored in at least one storage medium; the computer program product includes several instructions for enabling at least one computer device to execute the above method.

[0113] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A flow field tomography reconstruction method, characterized in that: The method comprises, Two absorption lines are selected, and the absorption coefficients of the two absorption lines are jointly solved. A two-line joint solution equation is established and merged into a single optimization equation, including: The system of equations Merge into a single optimization equation to calculate the double-line absorption coefficient distribution with the minimum error between the double-line integral value and the measured value. The single optimization equation after the merger is: ， in: α ν1 、 α ν2 represent the absorption coefficients of the two absorption lines respectively; A 1 and A 2 is the integrated absorbance, which is obtained by nonlinear fitting of the experimental spectrum by the Voigt function of the spectrum; W Is the projection weight matrix, whose elements are the path lengths of the laser when it passes through a specific grid. Once the optical path arrangement is determined, W Matrices are calculated using algebraic geometric relationships; μR ( α ν1 )and μR ( α ν2 ) is a regularization term that controls the degree of smoothness; α ν1 and α ν2 Regularization term for two variables R ( α ν1 , α ν2 ), ensuring the reliable calculation solution of the single optimization equation and suppressing the fluctuation of the dual-line temperature measurement; A hybrid Tikhonov Regularization and TV Regularization regularization constraint is introduced into a single optimization equation to establish a hybrid regularized two-line joint solution computational mathematical model. The hybrid regularized two-line joint solution computational mathematical model includes three parts: the first part is a computational fidelity term, the second part is a hybrid regularization term for each absorption line, and the third part is a hybrid regularization term for the absorption coefficient ratio distribution: ， in: is the regularization weight parameter; Set the non-negative criterion for the absorption coefficient and set the dual-line ratio after obtaining the upper and lower limit information of the flow field temperature. R The temperature limit further constrains the hybrid regularized two-line joint solution mathematical model, and the hybrid regularized solution mathematical model with temperature limit prior constraints is obtained: ； The mixed regularization mathematical model with temperature limit prior constraints is solved to obtain the absorption coefficient, which is then used to calculate the temperature distribution of the flow field.

2. The method according to claim 1, characterized in that The two absorption lines are absorption lines of water molecules in the flow field to be measured.

3. The method according to claim 2, characterized in that The two absorption lines are the center frequencies of the near-infrared band of water molecules, which are 7185.597 cm -1 and 7444.352 cm -1 absorption lines.

4. The method according to claim 1, wherein The mathematical model is solved jointly by two lines with hybrid regularization, and the empirical regularization weight parameters are selected to balance the importance of each sample.

5. The method according to claim 1, wherein The absorption coefficient is used to calculate the temperature distribution of the flow field, including: The target reconstruction area is discretized into multiple grid cells, and the thermophysical parameters in each grid cell are considered to be uniformly distributed; Calculate the temperature value of each grid cell according to the ratio of the absorption coefficients of the two absorption lines; The temperature distribution of the flow field is obtained by integrating the temperature values of all grid cells.

6. A flow field tomography reconstruction system, used to implement the flow field tomography reconstruction method according to any one of claims 1 to 5, characterized in that: The system includes an absorption coefficient joint solution module, a hybrid regularization module, a priori constraint module, and a solution calculation module; The absorption coefficient joint solution module is used to: select two absorption lines, jointly solve the absorption coefficients of the two absorption lines, establish a two-line joint solution equation and merge it into a single optimization equation; The hybrid regularization module is used to introduce hybrid regularization constraints into a single optimization equation and establish a hybrid regularized dual-line joint solution calculation mathematical model; The prior constraint module is used to: solve the mathematical model based on the dual-line joint solution of hybrid regularization, set the non-negative criterion of the absorption coefficient, and introduce the temperature prior information of the flow field to obtain the hybrid regularization solution mathematical model with the temperature limit prior constraint; The solution calculation module is used to solve the mixed regularization solution mathematical model with temperature limit prior constraints to obtain the absorption coefficient, and use the absorption coefficient to calculate the temperature distribution of the flow field.

7. The system according to claim 6, characterized in that The two absorption lines are absorption lines of water molecules in the flow field to be measured.

8. The system according to claim 7, characterized in that The two absorption lines are the center frequencies of the near-infrared band of water molecules, which are 7185.597 cm -1 and 7444.352 cm -1 absorption lines.

9. The system according to claim 6, wherein: The mathematical model is solved jointly by two lines with hybrid regularization, and the empirical regularization weight parameters are selected to balance the importance of each sample.

10. The system according to claim 6, wherein: The absorption coefficient is used to calculate the temperature distribution of the flow field, including: The target reconstruction area is discretized into multiple grid cells, and the thermophysical parameters in each grid cell are considered to be uniformly distributed; Calculate the temperature value of each grid cell according to the ratio of the absorption coefficients of the two absorption lines; The temperature distribution of the flow field is obtained by integrating the temperature values of all grid cells.

11. An electronic device, characterized in that: comprising at least one processor and at least one memory electrically connected; The memory is electrically connected to the processor, wherein the memory stores instructions that can be executed by at least one of the processors, and the instructions are executed by at least one of the processors to enable at least one of the processors to perform the flow field tomography reconstruction method according to any one of claims 1 to 5.

12. A computer-readable storage medium, characterized in that The computer readable storage medium stores a computer program; When the computer program is executed by a processor, the flow field tomography reconstruction method according to any one of claims 1 to 5 is implemented.

13. A computer program product, characterized in that The computer program product is stored in at least one storage medium; The computer program product includes several instructions for causing at least one electronic device to execute the flow field tomography reconstruction method according to any one of claims 1 to 5.

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