Method for detecting multi-parameter field of flame based on fusion of polarization technology and active-passive tomography technology

Abstract

A method for detecting multi-parameter field of flame based on fusion of polarization technology and active-passive tomography technology belongs to the technical field of high-temperature flame thermal radiation measurement. The method aims at the problem of poor measurement accuracy caused by the influence of optical components or the optical characteristics of the flame itself in the existing active-passive tomography technology of high-temperature flame. The method comprises the following steps: obtaining a radiation intensity signal measurement value of a smoke carbon flame, and calculating a spectral radiation physical property parameter distribution; combining a polarized light field signal and a radiation light field signal to calculate emitted radiation intensity; then calculating blackbody spectral radiation intensity and the temperature of the smoke carbon flame, and further obtaining a temperature field of the smoke carbon flame; setting a concentration field and a pressure field, calculating a radiation intensity signal estimation value of the smoke carbon flame, combining the radiation intensity signal measurement value to construct a target function equation, and calculating a target function value; until the concentration field and the pressure field set satisfy a preset threshold value, and the current concentration field and the pressure field are taken as the final flame detection result. The method is used for flame parameter detection.

Description

Technical Field

[0001] The invention relates to a method for detecting a flame multi-parameter field based on the fusion of polarization technology and active and passive tomography technology, and belongs to the technical field of high-temperature flame thermal radiation measurement. Background Art

[0002] Diagnosis of high-temperature flame combustion processes has important applications in the energy, environmental, and industrial sectors. Accurately measuring and analyzing flame parameters such as temperature, concentration, and pressure fields is crucial for optimizing combustion efficiency, reducing pollutant emissions, and improving industrial process safety. However, combustion diagnosis faces numerous challenges due to the complex physical and chemical reactions within the flame. The high temperature of the flame makes conventional measurement equipment susceptible to damage and difficult to operate stably for long periods of time. The presence of various combustion products and suspended particles within the flame leads to strong scattering and absorption of optical measurement signals. The flame combustion process undergoes rapid dynamic changes, requiring measurement equipment with high temporal resolution. The complex internal structure of the flame makes it difficult for traditional two-dimensional measurements to provide comprehensive three-dimensional information. Parameters such as flame temperature, concentration, and pressure are coupled to each other, making it difficult for a single measurement method to accurately separate and obtain each parameter.

[0003] For high-temperature flame combustion diagnostics, non-contact measurement methods have become a major research and application area due to their ability to provide high-precision data without disturbing the flame itself. Common active tomography techniques include laser-induced fluorescence (LIF) tomography, Raman tomography, and photoacoustic tomography. Active tomography uses an external light source (such as a laser) to actively excite specific molecules or particles in the flame, utilizing their response signals (such as scattering, fluorescence, and absorption) for imaging and analysis. The active nature of this method stems from the use of an external light source, which yields clearer signals and higher measurement accuracy. Common passive tomography techniques include multispectral infrared imaging and light field imaging. Passive tomography relies on the radiation and scattered light signals of the flame itself, eliminating the need for an external excitation light source. These signals are collected by imaging and detection systems, and tomographic algorithms are used to reconstruct the distribution of flame parameters such as temperature and concentration. Active tomography offers the advantages of strong signals and high sensitivity, but requires complex laser systems and optical components. The laser beam is susceptible to scattering and absorption as it propagates through the flame, making calibration difficult and measurement accuracy limited. Laser tomography can typically only be performed from a limited range of angles, limiting reconstruction accuracy. Passive chromatography technology, on the other hand, requires simple equipment and is highly adaptable. However, its signal strength depends on the radiation and scattering properties of the flame itself, which is significantly affected by flame intensity and ambient light, resulting in limited measurement accuracy. Active and passive chromatography each have their own advantages and disadvantages, and the appropriate method or combination is typically selected based on specific application requirements.

[0004] In summary, the challenges of high-temperature flame combustion diagnosis primarily lie in the high-temperature resistance of measurement equipment, the complexity of signal processing, the rapid capture of dynamic changes, the difficulty of 3D reconstruction, and the challenges of multi-parameter coupling. These issues urgently require an efficient and accurate multi-parameter field detection method to provide a solution. Summary of the Invention

[0005] Aiming at the problem that the existing active and passive tomography technology of high-temperature flame has poor measurement accuracy due to the influence of optical components or the optical characteristics of the flame itself, the present invention provides a method for detecting the multi-parameter field of flame based on the fusion of polarization technology and active and passive tomography technology.

[0006] The present invention provides a method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology, comprising:

[0007] The radiation intensity signal measurement value L of the soot flame is obtained using a photoelectric detector i ; At the same time, a polarization spectrum camera is used to obtain the polarization light field signal L of the soot flame ih And the infrared light field camera is used to obtain the radiation light field signal L of the soot flame if ;

[0008] Based on the radiation intensity signal measurement value L i Calculate the spectral radiation physical parameter distribution q; then combine it with the polarized light field signal L ih and the radiation light field signal L if Establish the overdetermined inverse problem of light field measurement and solve the outgoing radiation intensity L of the soot flame u ;

[0009] Based on the outgoing radiation intensity L u Calculate the blackbody spectral radiation intensity L of the soot flame bλ ; Then use Planck's law to calculate the temperature T of the soot flame d , and then calculate the temperature field T of the soot flame;

[0010] Set the concentration field C and pressure field P, combine with the temperature field T, establish the radiation transfer equation, and then use the inverse problem algorithm to solve the radiation transfer equation to obtain the radiation intensity signal estimation value L of the soot flame i ';

[0011] Then use the radiation intensity signal measurement value L i and the radiation intensity signal estimate L i ′, construct the objective function equations of the concentration field and pressure field, and calculate the objective function value; if the objective function value meets the preset threshold, the set concentration field C and pressure field P are used as the final flame detection result; otherwise, the set values ​​of the concentration field C and pressure field P are adjusted, and the calculation continues until the objective function value meets the preset threshold.

[0012] According to the method for detecting flame multi-parameter field based on the fusion of polarization technology and active and passive tomography technology of the present invention, the radiation intensity signal measurement value L i The method to obtain is:

[0013] The laser signal emitted by the laser is coupled into the optical fiber, and then divided into 8 measurement beams of equal intensity by the optical fiber beam splitter. The 8 measurement beams are arranged at equal intervals on one side of the soot flame using optical fiber bundle 1. Then, on the other side of the soot flame, optical fiber bundle 2 is used to receive the 8 measurement beams absorbed by the soot flame and incident on the photodetector. The radiation intensity signal measurement value L is obtained based on the received signal of the photodetector. i .

[0014] According to the method for detecting flame multi-parameter fields based on the integration of polarization technology and active and passive tomography technology, the polarization light field signal L of the soot flame is ih and the radiation light field signal L of the soot flame if The method to obtain is:

[0015] Control the polarization spectrum camera and infrared light field camera to collect data synchronously to obtain the polarization light field signal L of the soot flame ih and the radiation light field signal L of the soot flame if The polarized light field signal L of the soot flame ih The results are obtained by calculation based on multi-angle imaging of the combustion process using a polarization spectral camera.

[0016] According to the method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology of the present invention, the calculation method of the spectral radiation property parameter distribution q is:

[0017]

[0018] In the formula is the absorption coefficient distribution obtained in the nth iteration, μ (n) is the convergence factor of the nth iteration, q s is the spectral absorption coefficient, I is the projection coefficient matrix of laser signal detection;

[0019] Will make ||L i -q s I||The spectral absorption coefficient q when the minimum value is obtained s As the spectral radiation property parameter distribution q.

[0020] According to the method for detecting flame multi-parameter field based on the fusion of polarization technology and active and passive tomography technology, the outgoing radiation intensity L u Calculate the blackbody spectral radiation intensity L of the soot flame bλ The method is:

[0021] L u =A λ L bλ ,

[0022] Where A λ is the projection coefficient matrix obtained by back-tracing the pixels detected by the polarization spectrum camera and the infrared light field camera;

[0023] The linear inverse problem algorithm is used to solve the blackbody spectral radiation intensity L bλ :

[0024]

[0025] Where S0 is the initial value of the transition matrix, E is the identity matrix, α is the relaxation factor, and A λ0 A λ The initial value of A λN is the A of the Nth iteration λ Value, S N is the transition matrix of the Nth iteration, p≥2, which is a given positive integer; X N+1 is the blackbody spectral radiation intensity L of the N+1th iteration bλ Alternative value;

[0026] If the iteration M steps reaches the maximum number of iterations or the iteration M steps, X M With X M-1 If the comparison result reaches the minimum convergence accuracy, then calculate X according to the following formula M , and as the blackbody spectral radiation intensity L bλ :

[0027]

[0028] According to the method for detecting flame multi-parameter fields based on the integration of polarization technology and active and passive tomography technology, the temperature T d The calculation method is:

[0029]

[0030] Where λ is the radiation wavelength, c1 is the first radiation constant of Planck's law, and c2 is the second radiation constant of Planck's law.

[0031] According to the method of detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology of the present invention, the radiation transfer equation is established as follows:

[0032]

[0033] Where ν is the center wave number of the laser spectrum of the laser signal, L0 is the radiation intensity of the laser signal, and l represents the polarization light field signal L ih and the radiation light field signal L of the soot flame if The grid point position of the three-dimensional flame obtained; P l is the pressure field at position l, S ν is the line strength function, T l is the temperature field at position l, is a linear function, C l is the concentration field at position l.

[0034] According to the method of detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology, the radiation transfer equation is deformed:

[0035] According to the radiation wavelength λ as a fixed value, the radiation transfer equation about the concentration field C and pressure field P is obtained:

[0036]

[0037] According to the method of detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology of the present invention, the objective function equation for constructing the concentration field and pressure field is:

[0038]

[0039] Where F obj (P, C) is the objective function regarding the concentration field and pressure field.

[0040] According to the method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology, the optical fiber beam splitter is of fused tapered type or planar waveguide type, and the intensities of the eight measurement beams obtained through the optical fiber beam splitter are equal.

[0041] The present invention's beneficial effects: Designed to overcome the complex signal processing, difficulty capturing dynamic changes, and difficulty in three-dimensional reconstruction in existing high-temperature flame combustion diagnostics, the present method combines polarization imaging, light field cameras, and laser tomography to comprehensively and accurately measure flame temperature and concentration fields. Through multi-source data fusion and advanced algorithmic processing, the present method enables high-precision measurement and three-dimensional reconstruction of parameters such as flame temperature, concentration, and pressure, overcoming the limitations of traditional measurement methods and possessing significant application value for optimizing and controlling combustion processes.

[0042] The method of this invention combines polarization technology with active and passive tomography techniques to achieve comprehensive and accurate diagnosis of high-temperature flame combustion processes. The acquired signals not only provide more comprehensive and accurate information on flame characteristics, but also provide a powerful tool for in-depth understanding of complex combustion processes, optimizing burner design, and developing advanced combustion theory.

[0043] The method of the present invention can obtain multi-dimensional information, improve parameter complementarity, enhance spatial resolution, and enhance temporal resolution. Polarization information provides clues to the microstructure and heterogeneity of the flame, active tomography (such as laser-induced fluorescence) provides high spatial resolution distribution of specific components, and passive tomography (such as chemiluminescence) provides information on the overall temperature field and main reaction areas. The combination of this multi-dimensional information enables the present invention to fully understand the physical and chemical properties of the flame, provide more constraints, and help solve the ill-posedness of the inverse problem. Using machine learning techniques, such as deep learning, more information can be extracted from multi-source data. Polarization imaging can detect subtle structural changes that are difficult to distinguish with traditional intensity imaging, and tomographic reconstruction technology can provide three-dimensional spatial distribution, overcoming the limitations of two-dimensional projection. Combining these two technologies, three-dimensional flame parameter field reconstruction with high spatial resolution can be achieved. High-speed polarization imaging can capture rapidly changing flame structures, and synchronous measurements of active and passive tomography can track transient combustion processes. This high temporal resolution multi-parameter measurement helps to study combustion dynamics and instabilities.

[0044] The method of the present invention improves the measurement accuracy and reliability of flame parameters, can improve the cross-validation capability, perform error compensation, and enhance robustness. Parameters obtained by different methods can be mutually verified. For example, the temperature field can be obtained by both passive tomography and polarization characteristics. The component distribution measured by active tomography can be compared with the results inferred by polarization characteristics. This cross-validation mechanism greatly improves the credibility of the measurement results. Polarization measurement is sensitive to certain systematic errors (such as optical distortion) and can be corrected by tomography data. Certain artifacts in tomography reconstruction may be identified and eliminated through polarization information. The fusion of multiple technologies provides opportunities for error identification and compensation, improving the overall measurement accuracy. Under certain conditions (such as high concentrations of soot), traditional optical methods may fail, while polarization measurements can still provide useful information. The combination of active and passive tomography technologies makes the method of the present invention more adaptable and able to cope with a wider range of combustion conditions.

[0045] The method of the present invention can deeply study the physical mechanism, enhance the multi-scale analysis capability, and enhance the detection of non-equilibrium processes and the study of interface dynamics. Polarization information reflects the characteristics of microscopic particles and molecular orientation, and tomographic reconstruction provides the distribution of macroscopic parameter fields. Combining information at these two scales, a multi-scale combustion model from micro to macro can be established. Changes in polarization characteristics can indicate local non-equilibrium states, and active tomography (such as laser-induced fluorescence) can detect the distribution of specific excited states. This combination makes it possible to study non-equilibrium combustion processes and plasma-assisted combustion. Polarization information is particularly sensitive to interface changes, and tomography technology provides precise positioning of the interface position. Combining these two types of information, in-depth research can be conducted on interface dynamics issues such as flame front propagation and vortex-flame interaction.

[0046] The method of the present invention has broad applicability, strong configurability, and significant upgrade potential. It has potential applications ranging from laboratory scale to industrial burners and can be used for flame detection of various fuel types, including traditional fossil fuels, biomass fuels, and new synthetic fuels. Certain functions can be selectively enabled based on specific needs, and measurement strategies can be flexibly adjusted based on the research object, such as focusing on polarization measurement or tomographic reconstruction. Its open architecture facilitates the integration of new sensors or algorithms and can be easily expanded to other optical diagnostic techniques, such as Raman spectroscopy and optical coherence tomography. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of the method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology according to the present invention;

[0048] Figure 2 This is a system diagram for implementing the method of the present invention; in the figure, 1-1 is the optical fiber bundle on one side of the soot flame, 1-2 is the optical fiber bundle on the other side of the soot flame, 2 is a polarization spectrum camera, 3 is an infrared light field camera, and 4 is a data processing unit;

[0049] Figure 3 This is an implementation system diagram of Example 1;

[0050] Figure 4 5 is a diagram of the implementation system of Example 2; FIG5 is a polarized light field camera system;

[0051] Figure 5 6 is a multi-spectral polarization system. DETAILED DESCRIPTION

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 any creative efforts shall fall within the scope of protection of the present invention.

[0053] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0054] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but they are not intended to limit the present invention.

[0055] Specific implementation method 1. Combination Figure 1 and Figure 2 As shown, the present invention provides a method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology, including:

[0056] The radiation intensity signal measurement value L of the soot flame is obtained using a photoelectric detector i ; At the same time, a polarization spectrum camera is used to obtain the polarization light field signal L of the soot flame ih And the infrared light field camera is used to obtain the radiation light field signal L of the soot flame if ;

[0057] According to the absorption spectrum theory, based on the radiation intensity signal measurement value L i Calculate the spectral radiation physical parameter distribution q; then combine it with the polarized light field signal L ih and the radiation light field signal L if The underdetermined ill-conditioned inverse problem in the light field measurement process is transformed into an overdetermined inverse problem of light field measurement, and the outgoing radiation intensity L of the soot flame is obtained by solving it. u ;

[0058] According to the structural parameters and position relationship of the light field camera and the polarization spectrum camera, based on the outgoing radiation intensity L u Combined with the inverse problem algorithm, the blackbody spectral radiation intensity L of the soot flame is calculated bλ ; Then use Planck's law to calculate the temperature T of the soot flame d , and then calculate the temperature field T of the soot flame;

[0059] Set the concentration field C and pressure field P, combine with the temperature field T, establish the radiation transfer equation, and then use the inverse problem algorithm to solve the radiation transfer equation to obtain the radiation intensity signal estimation value L of the soot flame i ';

[0060] Then use the radiation intensity signal measurement value L iand the radiation intensity signal estimate L i ′, construct the objective function equations of the concentration field and pressure field, and calculate the objective function value; if the objective function value meets the preset threshold, the set concentration field C and pressure field P are used as the final flame detection result; otherwise, the set values ​​of the concentration field C and pressure field P are adjusted, and the calculation continues until the objective function value meets the preset threshold.

[0061] Further, combined Figure 2 As shown, the radiation intensity signal measurement value L i The method to obtain is:

[0062] The laser signal emitted by the laser is coupled into the single-mode optical fiber through a collimator or focusing lens to improve the beam quality and reduce the loss and interference in spatial transmission;

[0063] The optical signal in the single-mode optical fiber is then divided into 8 measurement beams of equal intensity by a 1×8 optical fiber beam splitter. The 8 measurement beams are arranged at equal intervals on one side of the soot flame using optical fiber bundle 1. On the other side of the soot flame, optical fiber bundle 2 is used to receive the 8 measurement beams absorbed by the soot flame and incident on the photodetector. The radiation intensity signal measurement value L is obtained based on the received signal of the photodetector. i .

[0064] The laser signal emitted by the laser has a set wavelength and power and is a continuous laser signal. The output ends of 8 optical fibers are fixed on a precise optical platform and incident on the soot flame along different directions as measurement beams. After passing through the soot flame, the measurement beams are incident on the collection surface of the photodetector through 8 receiving optical fibers. The photodetector can be a photodiode or a photomultiplier tube, which is used to receive the light signal passing through the flame. Each photodetector corresponds to a measurement beam, forming a multi-channel synchronous measurement system. To maintain the air-fuel ratio of the soot flame stable, a mass flow controller can be used to accurately adjust the flow rate of fuel and air. Environmental parameters such as temperature, humidity and pressure are monitored to ensure the consistency of experimental conditions.

[0065] The laser can be a He-Ne laser, a semiconductor laser or a solid-state laser, and the specific selection depends on the required wavelength and power.

[0066] In this embodiment, the polarized light field signal L of the soot flame ih and the radiation light field signal L of the soot flame if The method to obtain is:

[0067] Control the polarization spectrum camera and infrared light field camera to collect data synchronously to obtain the polarization light field signal L of the soot flame ih and the radiation light field signal L of the soot flame if The polarized light field signal L of the soot flameih The results are obtained by calculation based on multi-angle imaging of the combustion process using a polarization spectral camera.

[0068] During implementation, this embodiment first performs data acquisition. A laser emits a laser signal, which is then detected by a photodetector. While maintaining the air-fuel ratio of the soot flame, a polarization spectroscopy camera and an infrared light field camera simultaneously acquire data. Synchronization is controlled by a synchronization control unit. A detector then synchronously detects the signals from the polarization spectroscopy camera and the infrared light field camera. After being collected by a data acquisition card, the collected signals are processed by a data processing unit to obtain the final concentration and pressure fields.

[0069] The synchronization control unit can be implemented with a high-precision clock signal or trigger to ensure the synchronization of data acquisition between the polarization spectrum camera and the light field camera. A dedicated data acquisition card and software can be used to coordinate the sampling timing of different devices. The light field camera using a microlens array captures the 4D light field information of the flame (XY plane spatial coordinates (x, y) and angular coordinates). Where x is the horizontal coordinate of the light focus point in the XY plane, y is the vertical coordinate of the light focus point in the XY plane, and θ is the angle between the light and the camera optical axis. The angle between the projection of the light on the XY plane and the X-axis. The light field camera should have an appropriate spectral response range, covering the main wavelengths of flame radiation. Use a spectral camera with a polarizing filter array to image the flame from multiple angles. The camera should be able to simultaneously obtain spatial, spectral and polarization information. Liquid crystal tunable filters or grating spectrometers can be used. Polarization spectral cameras are used to obtain polarization and spectral information during the combustion process. A high frame rate (≥100fps) can be selected to capture rapidly changing combustion processes, a wide spectral range (such as 400-1000nm) covering visible light to near-infrared, high polarization resolution (≤0.1°) to accurately measure the polarization state, and high spectral resolution (≤1nm) to distinguish the spectral characteristics of different combustion products. Save the raw data of all sensors to a high-speed storage system, perform preliminary data calibration and noise removal, and prepare for subsequent analysis.

[0070] Polarization spectroscopic cameras can use high-quality linear polarizers to ensure a high extinction ratio. Consider using broadband polarizers to accommodate the wide spectral range of flame radiation. Install a motorized rotation stage to precisely rotate the polarizer, ensuring that the rotation speed matches the camera frame rate. Consider adding a quarter-wave plate or half-wave plate for circular or elliptical polarization analysis. Use a scientific-grade camera with high sensitivity and high dynamic range. Consider using a polarization camera, such as a four-axis polarization camera, to simultaneously acquire images in multiple polarization directions. Use high-quality lenses to minimize optical distortion, employ bandpass filters to select specific wavelength ranges for analysis, and consider using tunable filters for multi-wavelength polarization imaging. Design a precise camera triggering system to synchronize with polarizer rotation. Use a high-precision timer or FPGA for microsecond synchronization. Use a standard polarization source for system calibration to determine the system's Mueller matrix or Stokes vector response. Perform multi-angle polarization measurements on steady-state flames, repeating the measurements multiple times to improve the signal-to-noise ratio. For dynamic flames, design a high-speed polarization measurement solution to capture the dynamic characteristics of the flame. Design a flame tomography system to obtain three-dimensional polarization distributions.

[0071] The polarization data processing and analysis process is as follows: First, preprocessing is performed, including basic image processing such as background subtraction and flat-field correction, and polarization-related image distortion correction is considered. Stokes parameters, degree of polarization, and polarization angle are then calculated, and Fourier analysis is used to process the rotated polarizer data. A complete 4x4 Mueller matrix image is acquired, and the Mueller matrix decomposition is analyzed to extract physical information. Polarization information can be used to infer internal flame asymmetry and inhomogeneity, and to analyze the relationship between polarization characteristics and flame temperature and component distribution.

[0072] Furthermore, the calculation method of the spectral radiation property parameter distribution q is:

[0073]

[0074] In the formula is the absorption coefficient distribution obtained in the nth iteration, μ (n) is the convergence factor of the nth iteration, q s is the spectral absorption coefficient, I is the projection coefficient matrix of laser signal detection;

[0075] Will make ||L i -q s I||The spectral absorption coefficient q when the minimum value is obtained s As the spectral radiation property parameter distribution q.

[0076] The original optical measurement data is converted into physical meaningful spectral radiation property parameters, which not only describe the interaction characteristics of flame and light, but also provide key information for subsequent flame internal state inversion. By combining multiple optical measurement techniques and advanced data processing methods, high spatial resolution and high spectral resolution parameter distribution can be obtained, laying the foundation for accurate characterization of the flame.

[0077] In the calculation of the outgoing radiation intensity L u , the underdetermined problem is converted into an overdetermined problem, and the multi-source data is comprehensively utilized, which can significantly improve the accuracy and reliability of the inversion results.

[0078] Based on the outgoing radiation intensity L u , the method for calculating the blackbody spectral radiation intensity L bλ of the soot flame is as follows:

[0079] Integrating along different detection line directions, the linear equation group with the flame blackbody spectral radiation intensity L bλ as the variable can be obtained:

[0080] L u = A λ L bλ ,

[0081] In the formula, A λ is the projection coefficient matrix obtained by reverse tracking the pixels based on the comprehensive detection of the polarized spectral camera and the infrared light field camera;

[0082] The linear inverse problem algorithm Landeweber is used to solve the blackbody spectral radiation intensity L bλ :

[0083]

[0084] In the formula, S0 is the initial value of the transition matrix, E is the unit matrix, α is the relaxation factor, A λ0 is the initial value of A λ , A λN is the value of A λ at the Nth iteration, S N is the transition matrix at the Nth iteration, p≥2 is a given positive integer; X N+1 is the replacement value of the blackbody spectral radiation intensity L bλ at the N+1th iteration;

[0085] If the iteration M steps reach the maximum number of iterations or the comparison result of X M and X M-1 at the Mth iteration reaches the minimum convergence accuracy, then X M is calculated according to the following formula and used as the blackbody spectral radiation intensity L bλ :

[0086]

[0087] Soot flame temperature T d The calculation method is:

[0088]

[0089] Where λ is the radiation wavelength, c1 is the first radiation constant of Planck's law, and its value is 3.7418×10 -16 W·m 2 ; c2 is the second radiation constant of Planck’s law, c2=1.4388×10 -2 m.K.

[0090] Going further, the radiation transfer equation is established as:

[0091]

[0092] Where ν is the center wave number of the laser spectrum of the laser signal, L0 is the radiation intensity of the laser signal, and l represents the polarization light field signal L ih and the radiation light field signal L of the soot flame if The grid point position of the three-dimensional flame obtained; P l is the pressure field at position l, S ν is the line strength function, T l is the temperature field at position l, is a linear function, C l is the concentration field at position l.

[0093] Reshape the radiative transfer equation:

[0094] According to the radiation wavelength λ as a fixed value, the radiation transfer equation about the concentration field C and pressure field P is obtained:

[0095]

[0096] Finally, the objective function equation for constructing the concentration field and pressure field is:

[0097]

[0098] Where F obj (P, C) is the objective function regarding the concentration field and pressure field.

[0099] As an example, the optical fiber beam splitter is of a fused-taper type or a planar waveguide type, and the eight measurement beams obtained through the optical fiber beam splitter have equal intensities.

[0100] Example 1

[0101] Combine Figure 3As shown, active optical tomography detection is performed using a polarization spectroscopic camera, a light field camera, and a laser. This precise and comprehensive combination can obtain the high-resolution 3D structure of the flame, detailed polarization characteristics, and the spatial distribution of specific chemical components, providing rich experimental data for a deeper understanding of the complex combustion process. The polarization spectroscopic camera is equipped with a high-frame rate (over 1000fps) CMOS sensor to ensure the capture of rapidly changing flame polarization information. The light field camera is equipped with a high-quality linear polarizer and a 1 / 4 wave plate for precise polarization state analysis. A high-precision rotation stage driven by a stepper motor is used to precisely control the angular position of the camera. A high-precision clock source and distributed triggers are used to ensure that the synchronization accuracy of all cameras reaches the microsecond level. For the light field camera, a high-resolution CMOS sensor is used with a resolution of at least 4K (4096x 3072 pixels), a frame rate ≥100fps, a dynamic range ≥14 bits, and a quantum efficiency peak ≥80%. The number of microlenses in the microlens array matches the number of sensor pixels, typically 100,000-300,000. The microlens focal length is precisely controlled with an error of <1%, and the array alignment accuracy relative to the sensor is <1μm. High-speed data transmission interfaces include PCIe 4.0x16 or CoaXPress 2.0, with a bandwidth of ≥30GB / s. The optical system's main lens features a high-quality, large aperture (f / 1.4-f / 2.8), a focal length range of 24-70mm, variable focus, and an APO design for chromatic aberration correction. The precision synchronization system achieves time synchronization accuracy of <100ns and trigger jitter of <10ns. The active optical tomography system utilizes high-power pulsed lasers, such as Nd:YAG or Nd:YLF, with a repetition rate ≥1kHz and a pulse width of <10ns. The data acquisition and control system utilizes a high-performance computer, large-capacity storage, and an advanced data acquisition and processing system. The CPU should have at least 32 cores, such as an AMD Threadripper or Intel Xeon, with ≥256GB of DDR4-3200 RAM. The GPU should be an NVIDIA RTX 3090 or Tesla A100. A 2TB NVMe SSD (read / write speed >5GB / s) should be used for cache, and a 100TB RAID 6 array should be used for primary storage. The data acquisition and processing system includes a real-time data acquisition module, a light field reconstruction module, a polarization analysis module, a laser tomography reconstruction module, and a data fusion and analysis module. The specific operation process is as follows: ① Perform system calibration, including calibration of the polarization camera system, the light field camera, and the laser tomography system. A standard polarization source (such as a polarizer and quarter-wave plate combination) is used to perform full-angle and multi-wavelength calibration of the multi-angle polarization system. A precision calibration plate and mobile platform are used to calibrate the spatial resolution and depth response of the light field camera. A fluorescent target or standard scatterer is used to calibrate the laser scanning range, resolution, and detector response. A mutually visible marker is used to achieve precise spatial alignment of the light field camera, polarization camera, and laser system.(ii) The experimental preparation stage, flame / burner setup, precise control of fuel flow and oxidant ratio, ensure the stability and repeatability of the flame, set appropriate ventilation and temperature control, minimize external disturbance, use precise three-dimensional adjustment platform, ensure that the field of view of all cameras and lasers completely covers the area of interest. (iii) Synchronous measurement adjustment, including timing control, polarization data acquisition and laser scanning. Start the high-precision timing controller to ensure the synchronization accuracy of all systems is better than 1 μs, the light field camera continuously acquires 4D light field information of the flame at a high frame rate (such as 500 fps), the multi-angle polarization system synchronously acquires polarization images at different angles, at least 4 images of different polarization states are acquired at each angle, and the laser tomography system scans according to the preset three-dimensional scanning mode and simultaneously acquires multi-wavelength scattering or fluorescence signals. (iv) Data processing process includes light field reconstruction, polarization analysis and tomographic reconstruction. Advanced light field reconstruction algorithms (such as wavefront coding or deep learning methods) are used to reconstruct the 3D structure of the flame in real time, the Stokes parameter analysis method is used to reconstruct the complete polarization distribution of the flame from multi-angle polarization data, and the algebraic reconstruction technique (ART) or the filtered back projection method (FBP) is applied to process the laser tomography data to reconstruct the spatial distribution of specific components.

[0102] Example Two

[0103] In combination Figure 4As shown, the detection is performed using a polarized light field camera system with laser active optical tomography. The polarized light field camera uses a high-resolution CMOS sensor for high-precision imaging, capturing detailed structures of the flame; a microlens array is used to provide light field information, capturing the direction and intensity of light at each viewpoint; a polarizing filter (linear polarizer) is used to analyze the polarized light in the flame, obtaining more information about the composition and structure of the flame; a high-speed data transmission interface ensures fast transmission of large amounts of data, reducing data delay. The laser active optical tomography system uses a high-power pulsed laser (such as a Nd:YAG laser), providing a strong pulsed light source for exciting specific molecules in the flame. The data acquisition and control system uses a high-performance computer equipped with multi-core processors and large memory for complex data analysis and modeling tasks, and uses large-capacity storage for storing large amounts of raw data and processed results, ensuring data integrity and traceability. The data acquisition and processing system is used to control experimental equipment, collect data, and perform post-processing and analysis of data. The specific operation process is as follows: ① System calibration, use standard targets for calibration to ensure that the resolution of the camera meets the experimental requirements, and calibrate the spatial resolution of the polarized light field camera. Use standard scanning targets and calibration tools to ensure the accuracy and repeatability of laser scanning, and calibrate the scanning range and resolution of the laser tomography system. ② Experimental preparation stage, set up the flame or burner in the measurement area to ensure that the flame is within the optimal viewing angle range of the camera and laser. Adjust the field of view of the camera and laser to ensure complete coverage of the area of interest, and adjust the position of the tripod and support to ensure that all equipment can capture the full picture of the flame. ③ Start the timing controller to ensure that all systems run synchronously, use a synchronous trigger to coordinate the working time of the camera and laser to avoid time errors in data acquisition. The polarized light field camera continuously acquires 4D light field information of the flame, recording light intensity information at each angle and polarization state of the flame in real time. The laser tomography system scans according to the preset scanning mode, acquires scattering or fluorescence signals, controls the laser scanning path, and records the excitation signals at each position in the flame. ④ Real-time processing of light field data, reconstructing the 3D structure of the flame, using light field imaging algorithms to convert the acquired 4D data into three-dimensional images of the flame. Use laser tomography data to reconstruct the spatial distribution of specific components, and extract the distribution information of different chemical components in the flame by solving the laser tomography data. ⑤ Data fusion and analysis, aligning the light field and tomography data in space and time, using spatial alignment algorithms and time synchronization algorithms to accurately register the data from different systems. Apply data fusion algorithms to generate comprehensive multi-parameter field distributions, combining light field and laser tomography data to generate comprehensive flame images containing temperature, concentration, and polarization information.

[0104] Example Three

[0105] In combination Figure 5As shown, the analysis is performed using a light field camera with a multi-spectral polarization system and a laser active optical tomography. The high-resolution CMOS sensor in the light field camera system has a resolution of at least 4K (4096x 3072 pixels), a frame rate of ≥100 fps, a dynamic range of ≥14 bits, and a quantum efficiency peak of ≥80%. The number of microlenses in the microlens array matches the sensor pixels, typically 100,000-300,000, the microlens focal length is precisely controlled with an error of <1%, and the array alignment accuracy is <1 μm relative to the sensor; the high-speed data transmission interface type can be selected as PCIe 4.0x16 or CoaXPress 2.0, with a bandwidth of ≥30 GB / s; the main lens of the optical system uses high-quality, large-aperture (f / 1.4-f / 2.8) lenses with a focal length range of 24-70 mm, variable focal length, and color correction using APO design; the time synchronization accuracy of the precision synchronization system is <100 ns, and the trigger jitter is <10 ns. The multi-spectral polarization system selects multiple high-speed polarization cameras (4-8), each equipped with a high-frame-rate (1000 fps or higher) CMOS sensor to ensure the capture of rapidly changing flame polarization information; the multi-spectral imaging system is equipped with a spectral filter (such as a liquid crystal tunable filter or a spectral spectrometer) for each camera, covering multiple wavelength ranges (ultraviolet to near-infrared); each camera is equipped with a high-quality linear polarizer and a 1 / 4 waveplate for accurate polarization state analysis; a high-precision rotary stage driven by a stepper motor is used to accurately control the angular position of the camera; a high-precision clock source and distributed trigger are used to ensure the synchronization accuracy of all cameras to the microsecond level. The laser active optical tomography system and the data acquisition and control system are as shown in Example 2. The specific operation process is as follows: ① System calibration, including polarization and spectral system calibration, light field camera calibration, laser tomography system calibration, and multi-system spatial registration. Use a standard polarization source (such as a polarizer and 1 / 4 waveplate combination) and a multi-spectral light source to calibrate the system at full angle and multiple wavelengths; use a precision calibration board and a moving platform to calibrate the spatial resolution and depth response of the light field camera; use a fluorescent target or a standard scatterer to calibrate the laser scanning range, resolution, and detector response; use a common visible marker to accurately align the light field camera, polarization camera, and laser system in space. ② Experimental control, accurately control the fuel flow and oxidant ratio to ensure the stability and repeatability of the flame; set appropriate ventilation and temperature control to minimize external disturbances; use a precision three-dimensional adjustment platform to ensure that the fields of view of all cameras and lasers completely cover the area of interest; implement laser safety protocols to ensure the safety of all operating personnel.③ Perform synchronous measurements, activating a high-precision timing controller to ensure synchronization accuracy of all systems is better than 1μs. The light field camera continuously captures 4D light field information of the flame at a high frame rate (e.g., 500 fps). The multi-angle polarization system simultaneously captures polarization and spectral images at different angles, capturing at least four images of different polarization states and multiple wavelength ranges at each angle. The laser tomography system scans according to a preset 3D scanning pattern, simultaneously capturing scattered or fluorescent signals at multiple wavelengths. ④ Perform data processing, including light field reconstruction, polarization analysis, spectral analysis, and tomographic reconstruction. Advanced light field reconstruction algorithms are used to reconstruct the 3D structure of the flame in real time. Stokes parameter analysis is used to reconstruct the complete polarization distribution of the flame from multi-angle polarization data. Multispectral imaging data processing is performed to analyze flame characteristics at different wavelengths. Algebraic reconstruction techniques (ART) or filtered back projection (FBP) are applied to process the laser tomography data and reconstruct the spatial distribution of specific components. ⑤ Perform data fusion and analysis, using image registration algorithms and timestamp information to accurately align light field, polarization, spectral, and tomographic data in spatial and temporal dimensions; develop data fusion algorithms based on physical models and machine learning to generate comprehensive multi-parameter field distributions containing temperature, concentration, velocity, and polarization information; and perform Monte Carlo simulations to evaluate uncertainties in the measurement and reconstruction process.

[0106] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely illustrative of the principles and applications of the invention. It should be understood that many modifications may be made to the illustrative embodiments, and that other arrangements may be devised, without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in ways other than those described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be used in conjunction with other described embodiments.

Claims

1. A method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology, characterized in that: include: The radiation intensity signal measurement value L of the soot flame is obtained using a photoelectric detector i ; At the same time, a polarization spectrum camera is used to obtain the polarization light field signal L of the soot flame ih And the infrared light field camera is used to obtain the radiation light field signal L of the soot flame if ; Based on the radiation intensity signal measurement value L i Calculate the spectral radiation physical parameter distribution q; then combine it with the polarized light field signal L ih and the radiation light field signal L if Establish the overdetermined inverse problem of light field measurement and solve the outgoing radiation intensity L of the soot flame u ; Based on the outgoing radiation intensity L u Calculate the blackbody spectral radiation intensity L of the soot flame bλ ; Then use Planck's law to calculate the temperature T of the soot flame d , and then calculate the temperature field T of the soot flame; Set the concentration field C and pressure field P, combine with the temperature field T, establish the radiation transfer equation, and then use the inverse problem algorithm to solve the radiation transfer equation to obtain the radiation intensity signal estimation value L of the soot flame i '; Then use the radiation intensity signal measurement value L i and the radiation intensity signal estimate L i ', construct the objective function equations of the concentration field and pressure field, and calculate the objective function value; if the objective function value meets the preset threshold, the set concentration field C and pressure field P are used as the final flame detection result; otherwise, the set values ​​of the concentration field C and pressure field P are adjusted, and the calculation is continued until the objective function value meets the preset threshold; Reshape the radiative transfer equation: According to the radiation wavelength λ as a fixed value, the radiation transfer equation about the concentration field C and pressure field P is obtained: Where ν is the center wave number of the laser spectrum of the laser signal, L0 is the radiation intensity of the laser signal, and l represents the polarization light field signal L ih and the radiation light field signal L of the soot flame if The grid point position of the three-dimensional flame obtained; P l is the pressure field at position l, S ν is the line strength function, T l is the temperature field at position l, is a linear function, C l is the concentration field at position l; The objective function equation for constructing the concentration field and pressure field is: Where F obj (P, C) is the objective function regarding the concentration field and pressure field.

2. The method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology according to claim 1 is characterized in that: The radiation intensity signal measurement value L i The method to obtain is: The laser signal emitted by the laser is coupled into the optical fiber, and then divided into 8 measurement beams of equal intensity by the optical fiber beam splitter. The 8 measurement beams are arranged at equal intervals on one side of the soot flame using optical fiber bundle 1. Then, on the other side of the soot flame, optical fiber bundle 2 is used to receive the 8 measurement beams absorbed by the soot flame and incident on the photodetector. The radiation intensity signal measurement value L is obtained based on the received signal of the photodetector. i .

3. The method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology according to claim 2 is characterized in that: Polarized light field signal L of soot flame ih and the radiation light field signal L of the soot flame if The method to obtain is: Control the polarization spectrum camera and infrared light field camera to collect data synchronously to obtain the polarization light field signal L of the soot flame ih and the radiation light field signal L of the soot flame if The polarized light field signal L of the soot flame ih The results are obtained by calculation based on multi-angle imaging of the combustion process using a polarization spectral camera.

4. The method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology according to claim 3 is characterized in that: The calculation method of spectral radiation property parameter distribution q is: In the formula is the absorption coefficient distribution obtained in the nth iteration, μ (n) is the convergence factor of the nth iteration, q s is the spectral absorption coefficient, I is the projection coefficient matrix of laser signal detection; Will make ||L i -q s I||The spectral absorption coefficient q when the minimum value is obtained s As the spectral radiation property parameter distribution q.

5. The method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology according to claim 4 is characterized in that: Based on the outgoing radiation intensity L u Calculate the blackbody spectral radiation intensity L of the soot flame bλ The method is: L u =A λ L bλ , Where A λ is the projection coefficient matrix obtained by back-tracing the pixels detected by the polarization spectrum camera and the infrared light field camera; The linear inverse problem algorithm is used to solve the blackbody spectral radiation intensity L bλ : Where S0 is the initial value of the transition matrix, E is the identity matrix, α is the relaxation factor, and A λ0 A λ The initial value of A λN is the A of the Nth iteration λ Value, S N is the transition matrix of the Nth iteration, p≥2, which is a given positive integer; X N+1 is the blackbody spectral radiation intensity L of the N+1th iteration bλ Alternative value; If the iteration M steps reaches the maximum number of iterations or the iteration M steps, X M With X M-1 If the comparison result reaches the minimum convergence accuracy, then calculate X according to the following formula M , and as the blackbody spectral radiation intensity L bλ :

6. The method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology according to claim 5 is characterized in that: Soot flame temperature T d The calculation method is: Where λ is the radiation wavelength, c1 is the first radiation constant of Planck's law, and c2 is the second radiation constant of Planck's law.

7. The method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology according to claim 6 is characterized in that: The radiation transfer equation is established as:

8. The method for detecting flame multi-parameter fields based on the fusion of polarization technology and active and passive tomography technology according to claim 2 is characterized in that: The optical fiber beam splitter is of fused tapered type or planar waveguide type, and the intensities of the eight measurement beams obtained through the optical fiber beam splitter are equal.

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