Three-dimensional flame measurements with large field angle

Approach to reduce light field sampling redundancy for flame temperature reconstruction

Flame temperature measurement through a light field camera shows an attractive research interest due to its capabilities of obtaining spatial and angular rays' information by a single exposure. However, the sampling information collected by the light field camera is vast and most of them are redundant. The reconstruction process occupies a larger computing memory and time-consuming. We propose a novel approach i.e., feature rays under-sampling (FRUS) to reduce the light field sampling redundancy and thus improve the reconstruction efficiency. The proposed approach is evaluated through numerical and experimental studies. Effects of under-sampling methods, flame dividing voxels, noise levels and light field camera parameters are investigated. It has been observed that the proposed approach provides better anti-noise ability and reconstruction efficiency. It can be valuable not only for the flame temperature reconstruction but also for other applications such as particle image velocimetry and light field microscope.

Sparse regularization-based reconstruction for 3D flame chemiluminescence tomography

Flame chemiluminescence tomography (FCT) is a non-intrusive method that is based on using cameras to measure projections, and it plays a crucial role in combustion diagnostics and measurement. Mathematically, the inversion problem is ill-posed, and in the case of limited optical accessibility in practical applications, it is rank deficient. Therefore, the solution process should ideally be supported by prior information, which can be based on the known physics. In this work, the total variation (TV) regularization has been combined with the well-known algebraic reconstruction technique (ART) for practical FCT applications. The TV method endorses smoothness while also preserving typical flame features such as the flame front. Split Bregman iteration has been adopted for TV minimization. Five different noise conditions and the chosen regularization parameter have been tested in numerical studies. Additionally, for the 12 perspectives, an experimental FCT system is demonstrated, which is utilized to recover the three-dimensional (3D) chemiluminescence distribution of candle flames. Both the numerical and experimental studies show that the typical line artifacts that appear with the conventional ART algorithm when recovering the continuous chemiluminescence field of the flames are significantly reduced with the proposed algorithm.

Quantitative Measurement of OH* and CH* Chemiluminescence in Jet Diffusion Flames

Quantitative measurement of chemiluminescence is a challenging work that limits the development of combustion diagnostics based on chemiluminescence. Here, we present a feasible method to obtain effective quantitative chemiluminescence data with an integrating sphere uniform light source. Spatial distribution images of OH* and CH* radiation from methane laminar diffusion flames were acquired using intensified charge-coupled device (CCD) cameras coupled with multiple lenses and narrow-band-pass filters. After the process of eliminating background emissions by three filters and the Abel inverse transformation, the chemiluminescence intensity was converted to a radiating rate based on the uniform light source. The simulated distributions of OH* and CH* agree well with the experimental results. It has also been found that the distribution of OH* is more extensive and closer to the flame front than that of CH*, demonstrating that OH* is more representative of the flame structure. Based on the change in the reaction rate of different formation reactions, OH* distributions can be divided into three regions: intense section near the nozzle, transition section in the middle of the flame, and secondary section downstream the flame, whereas CH* only exists in the first two regions. In addition, as the velocity ratio of methane and co-flowing air increases, the main reactions become more intense, while the secondary reaction of OH* becomes weaker.

Research on a quantitative method for three-dimensional computed tomography of chemiluminescence

To develop a more advanced 3D computed tomography of the chemiluminescence method, the first quantitative 3D diagnosis was realized. The nonlinearity coefficient, the nonuniformity coefficient of the camera response, and various optical fiber attenuation coefficients were obtained through correction experiments. The conversion relationship between the number of photons released by the target object per unit time and the camera gray value at a specified solid angle was also calibrated. To verify the quantitative reconstruction equation, 3D reconstructions of a methane-air flat flame and a simulated phantom were performed for comparison. The method can overcome artificial distortions caused by uncorrected reconstruction.

Two-Dimensional Tomographic Simultaneous Multispecies Visualization—Part II: Reconstruction Accuracy

Recently we demonstrated the simultaneous detection of the chemiluminescence of the radicals OH* (310 nm) and CH* (430 nm), as well as the thermal radiation of soot in laminar and turbulent methane/air diffusion flames. As expected, a strong spatial and temporal coupling of OH* and CH* in laminar and moderate turbulent flames was observed. Taking advantage of this coupling, multispecies tomography enables us to quantify the reconstruction quality completely independent of any phantom studies by simply utilizing the reconstructed distribution of both species. This is especially important in turbulent flames, where it is difficult to separate measurement noise from turbulent fluctuations. It is shown that reconstruction methods based on Tikhonov regularization should be preferred over the widely used algebraic reconstruction technique (ART) and multiplicative algebraic reconstruction techniques (MART), especially for high-speed imaging or generally in the limit of low signal-to-noise ratio.

Two-Dimensional Tomographic Simultaneous Multi-Species Visualization—Part I: Experimental Methodology and Application to Laminar and Turbulent Flames

In recent years, the tomographic visualization of laminar and turbulent flames has received much attention due to the possibility of observing combustion processes on-line and with high temporal resolution. In most cases, either the spectrally non-resolved flame luminescence or the chemiluminescence of a single species is detected and used for the tomographic reconstruction. In this work, we present a novel 2D emission tomographic setup that allows for the simultaneous detection of multiple species (e.g., OH*, CH* and soot but not limited to these) using a single image intensified CCD camera. We demonstrate the simultaneous detection of OH* (310 nm), CH* (430 nm) and soot (750 nm) in laminar methane/air, as well as turbulent methane/air and ethylene/air diffusion flames. As expected, the reconstructed distributions of OH* and CH* in laminar and turbulent flames are highly correlated, which supports the feasibility of tomographic measurements on these kinds of flames and at timescales down to about 1 ms. In addition, the possibilities and limitations of the tomographic approach to distinguish between locally premixed, partially premixed and non-premixed conditions, based on evaluating the local intensity ratio of OH* and CH* is investigated. While the tomographic measurements allow a qualitative classification of the combustion conditions, a quantitative interpretation of instantaneous reconstructed intensities (single shot results) has a much greater uncertainty.

Three-dimensional rapid flame chemiluminescence tomography via deep learning

Flame chemiluminescence tomography (FCT) plays an important role in combustion monitoring and diagnostics due to the easy implementation and non-intrusion. However, on account of the high data throughput and the inefficiency of the conventional iteration methods, the 3D reconstructions in FCT are typically conducted off-line and time-consuming. In this work, we present a 3D rapid FCT reconstruction system based on convolutional neural networks (CNN) model for practical combustion measurement, which has the ability to reconstruct 3D flame distribution rapidly after training process. First, the numerical simulation has been performed by creating three cases of phantoms which are designed to mimic the 3D conical flame. Next, after the evaluation of loss function and training time, the optimal CNN architecture has been determined and certificated quantitatively. Finally, a real time FCT system consisting of 12 color CCD cameras is realized and multispectral separation algorithm is adopted to extract CH* and C2* components. Certificated by practical measurements testing, the proposed CNN model is able to reconstruct 3D flame structure from real time captured projections with credible accuracy and structure similarity. Furthermore, compared with conventional iteration reconstruction method, the proposed CNN model shows better performance on obviously improving reconstruction speed and it is expected to achieve 3D rapid monitoring of flames.

Design and modeling of pulsed-laser three-dimensional imaging system inspired by compound and human hybrid eye

A pulsed-laser three-dimensional imaging system inspired by compound and human hybrid eye is proposed. A diffractive optical element is used to enlarge field of view (FOV) of transmitting system and a receiving system consisting of a non-uniform microlens array, an aperture array, and an avalanche photodiode array is designed. The non-uniform microlens array is arranged on a curved surface to mimic large FOV feature of the compound eye. Meanwhile, the non-uniform microlens array is modeled to mimic space-variant resolution property of the human eye. On the basis of the proposed system, some simulation experiments are carried out. Results show that the entire FOV is up to 52°, and the resolution is 30 × 18. The proposed system has a high resolution in the center FOV and a low resolution in the peripheral FOV. The rotation and scaling invariances of the human eye are verified on the proposed system. The signal-to-noise ratio (SNR) increases with the increase in the number of rings and the maximum SNR locates at the outmost periphery area. This work is beneficial to the design of the pulsed laser three-dimensional imaging system with large FOV, high speed, and high resolution.