A device and method for measuring dynamic three-dimensional structure of turbulent flame

Abstract

The application discloses a kind of turbulent flame dynamic three-dimensional structure measuring device and method.The measuring device includes: multi-ultraviolet camera imaging system, for capturing the projection image of turbulent flame OH* free radical radiation luminescence in different directions;Optical fixing system, for fixing camera and adjusting the height and angle of viewing angle;A synchronous controller is used to realize the synchronous acquisition of transient flame image;A computer is used to store image and calculate analysis.The measuring method includes: multi-ultraviolet camera imaging system calibration;Shooting and correcting turbulent flame transient image;According to the corrected flame image, the weight coefficient of the target space discrete voxel is calculated using voxel preprocessing technology;Finally, using tomographic reconstruction algorithm, the three-dimensional structure distribution of turbulent flame in target space is reconstructed.The application constructs chemiluminescence tomography system based on multi-ultraviolet camera, realizes the acquisition of low-cost, high-accuracy turbulent flame transient front chemiluminescence information;In the reconstruction process, the calculation amount of weight coefficient is reduced using voxel preprocessing technology, and the measurement accuracy is improved.

Description

TECHNICAL FIELD

[0001] The application relates to a device and a method for measuring dynamic three-dimensional structure of turbulent flame, and belongs to the technical field of optical measurement of turbulent flame. BACKGROUND

[0002] Lean premixed turbulent combustion technology can effectively reduce the emission of nitrogen oxides by reducing the temperature of the flame center reaction zone, and has been widely used in the fields of aero-engine, gas turbine and the like. However, due to the complexity of the turbulent flame flow field and the frequent combustion pulsation, the technology has a dynamic instability problem caused by thermoacoustic coupling oscillation in the actual working condition, which may cause equipment damage in severe cases. Relevant studies have shown that the turbulent flame front plays an important role in the process of combustion heat and mass transfer, and its three-dimensional structure reflects the macroscopic structure of the flame and the combustion stability. Realizing the measurement and characterization of the dynamic three-dimensional structure of the turbulent flame front has important practical significance for the study of the mechanism of turbulent combustion and the optimization design of the turbulent combustor.

[0003] In recent years, a large number of studies have been carried out on the measurement technology of flame front structure. Among them, the optical measurement technology has the characteristics of non-invasion, high sensitivity, high speed and the like, and gradually becomes one of the effective methods for characterizing the fine structure of the flame. The relatively mature optical measurement technologies at present mainly include laser-induced fluorescence technology (Laser Induced Fluorescence, LIF) and flame chemiluminescence computed tomography technology (Computed Tomography of Chemiluminescence, CTC), both of which use chemical reaction free radicals to characterize the flame front structure. LIF uses a laser of a specific wavelength to excite the flame combustion chemical reaction free radicals (such as OH and CH), captures the fluorescence signal generated by the energy level transition of the excited state free radicals by an intensified camera (ICCD), obtains the transient and quantitative free radical distribution information of the flame, and has the advantages of real-time in-situ measurement, high image signal-to-noise ratio and high sensitivity. However, LIF usually needs a high-frequency or high-energy laser, a high-speed camera and an image intensifier to capture the instantaneous fluorescence signal in the nanosecond exposure time scale, and the optical equipment is expensive and the system is complex. Flame chemiluminescence is a phenomenon that the excited state free radicals in the front surface radiate transition and release photons, CTC technology realizes the acquisition of the light emission signal of a specific free radical through a multi-view optical system, obtains the structure information of the flame front in different directions, and performs high-resolution three-dimensional tomographic reconstruction. Compared with LIF, CTC does not need a high-energy laser as an external excitation signal, and therefore has a great advantage in the cost of the hardware system. A large number of studies have shown that CTC is a very potential optical measurement technology, and has been widely concerned in the field of three-dimensional structure reconstruction of the flame front.

[0004] However, there are still some challenges in the current CTC measurement technology for dynamic turbulent flame front. One of the main challenges is the lack of information collection of turbulent flame front. The flame chemiluminescence excited state free radicals mainly include OH*(308 nm), CH*(431 nm) and C2*(470-550 nm). Among them, OH* has high luminescence efficiency in the combustion reaction zone, wide distribution range, narrow luminescence band and is in the ultraviolet region, which is not disturbed by the flame background radiation and is more suitable for the transient characterization of turbulent flame front. However, due to the low quantum efficiency in the ultraviolet band, ordinary cameras need to use image intensifiers to obtain high-quality images of OH* radiation. However, the cost of arranging multiple cameras coupled with image intensifiers is high. In order to reduce the hardware cost, some scholars use optical fiber bundles to couple with ICCD cameras in the optical imaging system to capture multiple view angle chemiluminescence projection images. However, the optical fiber bundles will cause serious signal loss during transmission, and the integration of multiple optical fiber bundles also reduces the field of view area provided to each view angle, which greatly affects the signal-to-noise ratio of image acquisition. In recent years, with the rapid development of ultraviolet imaging technology, high-sensitivity ultraviolet resolution electronic sensors have been applied to industrial cameras, realizing low-cost and high-signal-to-noise-ratio OH* radiation imaging, which provides the possibility for constructing CTC systems based on ultraviolet imaging and realizing high-precision dynamic three-dimensional structure measurement of turbulent flame.

[0005] Another challenge is that the high-resolution tomographic reconstruction of swirling flame front has problems such as large amount of calculation and obvious artifacts. Algebraic Reconstruction Technique (ART) iteratively corrects unknowns by error, which has been widely applied in the field of three-dimensional structure reconstruction of flame front. Simultaneous Algebraic Reconstruction Technique (SART) is developed from ART, which has high iteration efficiency and noise resistance ability, and has attracted wide attention. However, in the reconstruction process of SART algorithm, the flame measurement space is discretized into voxels, and the calculation of weight coefficients is time-consuming, which usually takes tens of hours at a spatial resolution of millions. At the same time, since SART algorithm corrects the discrete voxels of measurement space according to the calculation error of projection intensity, the imaging error causes the reconstructed results to have serious linear artifacts along the projection direction. Related studies have shown that swirling flame expands at the nozzle outlet, and the overall structure usually presents a bowl shape, so there are a large number of zero-intensity voxels in the measurement space near the nozzle outlet that do not contribute to the image intensity. If these voxels are identified and excluded in advance during reconstruction, it will not only reduce the calculation amount of weight coefficients, but also reduce the part of artifacts generated by zero-intensity voxels, and improve the quality of flame structure reconstruction. SUMMARY

[0006] TECHNICAL PROBLEM

[0007] The technical problem to be solved by the present application is that the optical measurement technology has the shortcomings of high cost and insufficient collection of turbulent flame front information, and the existing reconstruction algorithm has the problems of large amount of calculation and obvious artifacts, and a low-cost and high-precision turbulent flame dynamic three-dimensional structure measurement device and method are proposed. The basic idea is: a multi-ultraviolet camera imaging system is used to obtain the projection images of OH* free radical radiation light emission of turbulent flame in different directions, a voxel preprocessing technology is used to identify and exclude zero-intensity voxels, and then a tomographic reconstruction algorithm is used to realize three-dimensional structure reconstruction of turbulent flame.

[0008] Technical scheme:

[0009] A turbulent flame dynamic three-dimensional structure measurement device, characterized in that it comprises:

[0010] A multi-ultraviolet camera imaging system is used to capture the projection images of OH* free radical radiation light emission of turbulent flame in different directions, which comprises an ultraviolet camera, an ultraviolet lens and a narrow-band filter;

[0011] An optical fixing system is used to fix the ultraviolet camera and adjust the height and angle of the viewing angle, which comprises an optical platform and an optical support;

[0012] A synchronous controller is used to control the synchronization of the multi-ultraviolet camera imaging system during shooting, realize instantaneous flame image acquisition, and is connected with the ultraviolet camera through an external trigger line;

[0013] A computer is used to control the ultraviolet camera through software, store the transient flame images captured by the multi-ultraviolet camera imaging system, and calculate the three-dimensional structure distribution of the target space turbulent flame front by using a tomographic reconstruction algorithm.

[0014] The measurement device, wherein the ultraviolet camera has a quantum efficiency greater than 50% at a wavelength of 308 nm, the ultraviolet lens has a transmittance greater than 66% at a wavelength of 308 nm, the narrow-band filter has a bandwidth of 10 nm and a transmittance greater than 81% at a wavelength of 308 nm, and the multi-ultraviolet camera imaging system is suitable for capturing the radiation light emission signal of OH* free radical at a wavelength of 308 nm.

[0015] The measurement device, wherein the optical platform is composed of a plurality of circular guide rails, and the camera can move freely in the circumferential direction of the burner.

[0016] The measurement device, wherein the optical support is composed of a sliding base, a rotating rod holder, a lifting rod holder and a connecting rod, and can realize flexible adjustment of height and angle.

[0017] A turbulent flame dynamic three-dimensional structure measurement method, characterized in that it comprises the following steps:

[0018] Step one, calibration of measurement device: arrange multiple ultraviolet camera imaging systems, adjust the optical support so that the center of the sensor of each camera is in the same plane and aligned with the axis of the burner; through the mapping relationship between three-dimensional space and two-dimensional projection, use continuous binocular camera calibration to obtain the three-dimensional information of the rotation angle and displacement distance between multiple cameras, and at the same time obtain the distortion parameters of each camera for image correction;

[0019] Step two, using the calibrated measurement device, adjust the camera parameters according to the measurement working condition, shoot and record the transient flame images and a set of background images containing noise of the target space;

[0020] Step three, use the distortion parameters obtained in step one to correct the distortion of the flame image, and use the background images shot in step two to reduce the noise of the flame image;

[0021] Step four, according to the corrected flame image, calculate the weight coefficient of the discrete voxel of the target space, and the weight coefficient is the contribution degree of the discrete voxel to the pixel intensity of the camera sensor; use voxel preprocessing technology to pre-identify zero-intensity voxels and exclude them, so as to reduce the calculation amount of weight coefficient;

[0022] Step five, use tomographic reconstruction algorithm to inverse the three-dimensional structure distribution of the turbulent flame front of the target space.

[0023] In step four, it is assumed that light is a geometric ray bundle with radiation energy, and since the receiving aperture angle of a single pixel is very small, the camera lens can be equivalent to a pinhole, and the camera imaging process can be equivalent to a pinhole imaging model. The target space is discretized into uniform cubes (voxels), and it is assumed that the chemical luminescence intensity in each voxel is a constant value, and the intensity of each pixel on the camera sensor is the integral of the voxel intensity in the projection direction. Assuming that the projection direction of a certain pixel point P1 passes through voxels V1, V2…V n , the radiation transfer calculation formula is:

[0024]

[0025] In the formula, is the intensity value of voxel V i , the weight coefficient of pixel P1, that is, the coupling term of the length of light passing through the voxel and the flame scattering and absorption coefficient, is the intensity value of voxel V i , and is the intensity value of pixel P1.

[0026] Considering all voxels and pixels, the radiation transfer calculation formula can be expressed as:

[0027] A M×N ×X N×1 =BM×1

[0028] In the formula, M is the number of pixels, N is the number of measured space voxels, A is a weight coefficient matrix, X is a voxel intensity matrix, and B is a pixel intensity matrix.

[0029] Beneficial effects:

[0030] Compared with the existing optical measurement technology of three-dimensional structure of turbulent flame, the present application has the following advantages:

[0031] (1) A multi-UV camera imaging system is adopted, which has high quantum efficiency in the UV band, realizes low-cost and high-accuracy acquisition of transient chemiluminescence information of turbulent flame, and further acquires high-precision dynamic three-dimensional structure distribution of turbulent flame through tomographic reconstruction algorithm.

[0032] (2) The expansion of turbulent flame at the nozzle outlet is fully considered, and a large number of zero-intensity voxels which do not contribute to image intensity exist in the target space, voxel preprocessing technology is adopted to identify and exclude these voxels, which effectively reduces the weight coefficient calculation amount and improves the three-dimensional reconstruction efficiency of flame structure.

[0033] (3) The measurement system has no influence on the measurement of turbulent flame in structure, and belongs to a non-contact measurement method, which has the characteristics of simple, reliable and practical experimental device. BRIEF DESCRIPTION OF DRAWINGS

[0034] Figure 1 Structure diagram of the measuring device;

[0035] Figure 2 Structure diagram of the optical fixing device;

[0036] Figure 3 Calibration diagram of the measuring device;

[0037] Figure 4 Flowchart of the reconstruction algorithm based on voxel preprocessing technology

[0038] Figure 5 Three-dimensional view of the reconstruction result of the turbulent flame front structure;

[0039] Figure 6 Horizontal slice of the reconstruction result of the turbulent flame front structure;

[0040] 1 - UV camera, 2 - UV lens, 3 - narrowband filter, 4 - premixed turbulent combustor, 5 - gas valve, 6 - mass flowmeter, 7 - synchronous controller, 8 - computer, 9 - optical platform, 10 - circular guide rail, 11 - sliding base, 12 - rotating rod holder, 13 - connecting rod, 14 - lifting rod holder. DETAILED DESCRIPTION

[0041] The application will be further described below with reference to the accompanying drawings and examples. The examples described below are only used to illustrate the application and not to limit the scope of the application. After reading the application, those skilled in the art can make various modifications to the application, and the modifications fall within the scope defined by the appended claims.

[0042] The embodiment provides a flame three-dimensional structure red measurement device structure as shown in Figure 1 , comprising:

[0043] A multi-ultraviolet camera imaging system is used for capturing projection images of OH* free radical radiation luminescence of a turbulent flame in different directions, and comprises an ultraviolet camera 1, an ultraviolet lens 2, and a narrowband filter 3. In the example, eight ultraviolet cameras are used, arranged horizontally on an equiradius circular guide rail with a premixed turbulent burner as the center, and the cameras are spaced apart by an angle of 40°.

[0044] A turbulent combustion flame generating device comprises a premixed turbulent burner 4, a valve 5, and a mass flow meter 6. In the example, methane and air are mixed, and the geometric turbulence number of the premixed turbulent burner 4 is 0.55.

[0045] A synchronous controller 7 is used for controlling synchronization of the multi-ultraviolet camera imaging system during shooting, so as to realize instantaneous flame image acquisition, and is connected to the ultraviolet camera 1 through an external trigger line. In the example, the frame rate of the synchronous controller is set to 20 Hz.

[0046] A computer 8 is used for controlling the ultraviolet camera 1, storing the transient flame images captured by the multi-ultraviolet camera imaging system, and calculating the three-dimensional structure distribution of the target space turbulent flame front surface by using a tomographic reconstruction algorithm. In the example, a SART algorithm based on voxel preprocessing technology is used.

[0047] An optical fixing system is used for fixing the ultraviolet camera and adjusting the height and angle of the view angle, and details are shown in Figure 2 , comprising an optical platform 9 (a plurality of circular guide rails 10 are arranged on the optical platform 9), a sliding base 11, a rotating lever frame 12, a connecting rod 13, and a lifting lever frame 14.

[0048] The specific operation of the measurement device calibration is as follows, and the operation of the ultraviolet camera 1 and the ultraviolet lens 2 is by default applied to all eight ultraviolet cameras and ultraviolet lenses:

[0049] 1) First, set the aperture of the ultraviolet lens 2 to 3.8, set the ultraviolet camera 1 to a continuous acquisition-real-time display mode, and determine the center pixel position of the ultraviolet camera 1 sensor at the same time;

[0050] 2) Use the sliding base 11 to arrange the ultraviolet cameras 1 at an interval of 40°, use the rotating lever frame 12 and the lifting lever frame 14 to adjust the view angle of the ultraviolet camera 1, and make the center pixel point of the ultraviolet camera 1 sensor coincide with the center of the nozzle outlet of the turbulent burner.

[0051] 3) Calibrate each ultraviolet camera by chessboard calibration method to obtain the internal parameters of the ultraviolet camera, including the intrinsic matrix M1 and the radial distortion matrix D;

[0052] 4) Perform binocular camera calibration to obtain the external parameters between the ultraviolet cameras. Simultaneously capture the black and white chessboard by the adjacent two ultraviolet cameras, and obtain the rotation displacement matrix between each two ultraviolet cameras through corner point recognition Figure 3 for the black and white chessboard image captured by the adjacent two ultraviolet cameras. In this example, the ultraviolet cameras are numbered as 1, 2, 3, …, 8 in counterclockwise direction, and the calibration order is 1-2, 2-3, 3-4, …, 7-8, 8-1. The relative rotation displacement matrix obtained by each calibration is denoted as P1, P2, …, P8;

[0053] 5) Integrate and calibrate the calibration parameters, define Q = P8P7P6P5P4P3P2P1. In ideal case, Q is a unit matrix, but due to the existence of calibration error and the accumulation in calculation, the result of Q often deviates to a certain extent. The cumulative deviation of the calibration result in angle and displacement is calculated by the difference between Q and the unit matrix.

[0054] The embodiment provides a low-cost high-precision turbulent flame dynamic three-dimensional structure measurement method. The measurement method is based on the turbulent flame dynamic three-dimensional structure measurement in the embodiment, and the steps of the measurement method are as follows:

[0055] Step 1, calibration of the measuring device. The purpose of calibration is to obtain the three-dimensional information of the rotation angle and displacement distance between the multiple cameras for light tracking calculation, and to obtain the distortion parameters of each camera for image correction.

[0056] Step 2, turbulent flame image acquisition and processing: acquire the instantaneous image and background image of the turbulent flame, and perform distortion correction and noise reduction processing on the image.

[0057] The specific operation is as follows:

[0058] 1) Connect the ultraviolet camera 1 to the synchronous controller 7 through the external trigger line, set the frame rate to 20 Hz using the synchronous controller 7, set the ultraviolet camera 1 to the hardware trigger mode using the computer 8, and set the exposure time to 200 μs;

[0059] 2) Open the gas valve 5, set the real-time flow of the mass flow meter 6 using the computer 8, and ignite the turbulent flame. In this example, the methane flow is set to 15 L / min, the air flow is set to 175 L / min, and the equivalence ratio is 0.59;

[0060] 3) Using computer 8 to control the synchronization controller 7, so that the eight ultraviolet cameras 1 can simultaneously acquire the transient projection images of the turbulent flame at eight angles;

[0061] 4) Using computer 8 to set the real-time flow of the mass flow meter 6 to 0, and after the flame is naturally extinguished, a set of black background images are taken, the gas path valve 5 is closed, and the gas tightness of the device is checked;

[0062] 5) Using computer 8 to arrange the taken images, using the radial distortion coefficient calibrated in step 1 to correct the flame images and the background images, and subtracting the background images from the flame images to obtain the real OH* radiation projection.

[0063] Step three, three-dimensional reconstruction of the dynamic structure of the turbulent flame: using voxel preprocessing technology to optimize the weight coefficient calculation of the discrete voxels in the target space (flow chart as Figure 4 ), and using tomographic reconstruction algorithm to inverse reconstruct the three-dimensional structure distribution of the turbulent flame front in the target space.

[0064] The specific operation is as follows:

[0065] 1) According to the system calibration results and the flame images, the target space is selected and the voxels are divided. In this example, the flame reconstruction space size is 50x50x45mm (X axisxY axisxZ axis), which is evenly divided into 250x250x225 voxels, and the spatial resolution is 0.2x0.2x0.2mm. Considering all voxels and pixels, the radiation transmission calculation formula can be expressed as:

[0066] A M×N ×X N×1 =B M×1

[0067] In the formula, M is the number of pixels, N is the number of measured space voxels, A is the weight coefficient matrix, X is the voxel intensity matrix, and B is the pixel intensity matrix.

[0068] 2) The pixels of the flame images are numbered in turn, and the spatial position of each pixel point is calculated. Starting from the pixel point, the light rays are traced in reverse to obtain the voxels through which the light rays pass;

[0069] 3) The pixel intensity is read. If the pixel point intensity is 0, the intensity integral of the light ray passing through the voxel is 0, and this part of the zero-intensity voxel is recorded and excluded;

[0070] 4) The weight coefficients of the remaining voxels are calculated;

[0071] 5) Given the weight coefficient matrix A and the pixel intensity matrix B, the SART algorithm is used to inverse reconstruct the voxel intensity matrix X, and the SART calculation formula is:

[0072]

[0073] where x j is an element in matrix X; x j (k) and x j (k+1) represent the intensity value of the jth voxel after the kth and (k+1)th iteration, respectively; b i represents the actual projection intensity value of the ith ray; represents the calculated projection intensity value of the ith ray; represents the cumulative value of the contribution of the voxel to the ith ray; λ represents the relaxation factor; I θ represents the set of all rays under projection angle θ; A ij represents the weight coefficient of the jth voxel on the ith ray; represents the intensity value of the nth voxel after the kth iteration; A in represents the weight coefficient of the nth voxel on the ith ray.

[0074] The relaxation factor and the initial iteration number are set, the root mean square error of the actual projection intensity value and the calculated projection intensity after each iteration is calculated, the optimal iteration number is determined, and then the iteration number is reset to obtain the optimal calculation result. In this example, the relaxation factor λ is set to 1.5, and the initial iteration number is 1000 times. The root mean square error reaches the minimum value of 0.126 at the 410th time.

[0075] 6) After obtaining the voxel intensity matrix X, the missing voxels in the target space are assigned a value of 0, so that the structure of the target space is complete. In this example, the three-dimensional view of the reconstructed result of the turbulent flame front structure is shown in Figure 5 , and the horizontal slice of the reconstructed result is shown in Figure 6 .

Claims

1. A dynamic three-dimensional structure measurement device for turbulent flames, characterized in that, include: A multi-ultraviolet camera imaging system for capturing projected images of OH* free radical radiative emission from turbulent flames in different directions includes an ultraviolet camera, an ultraviolet lens, and a narrowband filter. The ultraviolet camera has a quantum efficiency greater than 50% in the 308nm band, the ultraviolet lens has a transmittance greater than 66% in the 308nm band, and the narrowband filter has a transmittance greater than 81% in the 308nm band. An optical fixing system for fixing the ultraviolet camera and adjusting the height and angle of the viewing angle includes an optical platform and an optical support. A synchronization controller is used to control the synchronization of the multi-ultraviolet camera imaging system during shooting, so as to realize instantaneous flame image acquisition. It is connected to the ultraviolet camera through an external trigger line. A computer calculates the three-dimensional structural distribution of the turbulent flame in the target space using a tomographic reconstruction algorithm based on transient flame images captured by the multi-ultraviolet camera imaging system. The computer uses a tomographic reconstruction algorithm to calculate the three-dimensional structural distribution of the turbulent flame in the target space, including: 1) Select the target space and divide it into voxels based on the calibration results of the multi-ultraviolet camera imaging system and the flame image; 2) Number the pixels of the flame image sequentially and calculate the spatial position of each pixel. Then, trace the light rays backward from the pixel to obtain the voxels through which the light rays pass. 3) Read the pixel intensity. If the pixel intensity is 0, record and exclude zero-intensity voxels associated with that pixel. 4) Based on the ray tracing results and the flame absorption and scattering coefficient, calculate the weight coefficients of the remaining voxels to obtain the weight coefficient matrix A; 5) Based on the obtained weight coefficient matrix A, invert and reconstruct the voxel intensity matrix X: A M×N ×X N×1 =B M×1 In the formula, M is the number of pixels, N is the number of voxels in the measurement space, and B is the pixel intensity matrix; 6) Based on the reconstructed voxel intensity matrix X, assign the missing voxels in the target space to 0 to obtain the target space with complete structure.

2. The measuring device according to claim 1, characterized in that, In step 5), the SART algorithm is used to invert and reconstruct the voxel intensity matrix X. The SART calculation formula is: In the formula, x j x is an element in matrix X; j (k) and x j (k+1) represent the intensity values ​​of the j-th voxel after the k-th and (k+1)-th iterations, respectively; b i This represents the actual projected intensity value of the i-th ray; This represents the calculated projection intensity value of the i-th ray; The cumulative contribution of the voxel through which the i-th ray passes is represented; λ represents the relaxation factor; I θ A represents the set of all rays at the projection angle θ; ij This represents the weight coefficient of the j-th voxel on the i-th ray; A represents the intensity value of the nth voxel after the kth iteration; in This represents the weight coefficient of the nth voxel on the i-th ray; Set the relaxation factor and the initial number of iterations, calculate the root mean square error between the actual projection intensity value and the calculated projection intensity after each iteration, determine the optimal number of iterations, and then reset the number of iterations to obtain the optimal calculation result.

3. The measuring device according to claim 1, characterized in that, The narrowband filter has a bandwidth of 10nm.

4. The measuring device according to claim 1, characterized in that, The optical platform consists of multiple circular guide rails, enabling the camera to move freely around the burner.

5. The measuring device according to claim 1, characterized in that, The optical support consists of a sliding base, a rotating rod frame, a lifting rod frame, and a connecting rod, enabling flexible adjustment of height and angle.

6. A method for measuring the dynamic three-dimensional structure of a turbulent flame based on the measuring device described in any one of claims 1-5, characterized in that, Includes the following steps: Step 1, Measurement device calibration: Set up the multi-ultraviolet camera imaging system and adjust the optical support so that the sensor center of each camera is located on the same plane and aligned with the central axis of the burner; By using the mapping relationship between three-dimensional space and two-dimensional projection, continuous binocular camera calibration is used to obtain three-dimensional information on the rotation angle and displacement distance between multiple cameras, while the distortion parameters of each camera are obtained for image correction. Step 2: Turbulent Flame Image Acquisition and Processing: Using the calibrated measuring device, capture and record transient flame images of the target space and a set of background images with background noise; use the distortion parameters obtained in Step 1 to perform distortion correction on the flame images, and use the background images to perform noise reduction on the flame images; Step 3: 3D reconstruction of the dynamic structure of turbulent flames: Based on the corrected flame image, the weight coefficients of discrete voxels in the target space are optimized using voxel preprocessing technology; the 3D structure distribution of turbulent flames in the target space is inverted and reconstructed using a tomographic reconstruction algorithm.

7. The measurement method according to claim 6, characterized in that, Step 1 involves calibrating the multi-UV camera imaging system using a binocular camera calibration method, defining a calibration matrix, and evaluating the calibration results.

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