Three-dimensional dynamic measurements of CH* and C2* concentrations in flame using simultaneous chemiluminescence tomography

Correction procedure for a tomographic optical setup employing imaging fiber bundles and intensified cameras

For reliable tomographic measurements the underlying 2D images from different viewing angles must be matched in terms of signal detection characteristics. Non-linearity effects introduced by intensified cameras and spatial intensity variations induced from inhomogeneous transmission of the optical setup can lead, if not corrected, to a biased tomographic reconstruction result. This paper presents a complete correction procedure consisting of a combination of a non-linearity and flatfield correction for a tomographic optical setup employing imaging fiber bundles and four intensified cameras. Influencing parameters on the camera non-linearity are investigated and discussed. The correction procedure is applied to 3D temperature measurements by two-color pyrometry and compared to results without correction. The present paper may serve as a guideline for an appropriate correction procedure for any type of measurement involving optical tomography and intensified cameras.

Tri-zone flame spatial structure imaging combined with endogenic polarized scattering

We propose a multi-mode optical imaging method to retrieve the 2D and 3D spatial structures of the preheating, reaction, and recombination zones of an axisymmetric steady flame. In the proposed method, an infrared camera, a visible light monochromatic camera, and a polarization camera are triggered synchronously to capture 2D flame images, and their corresponding 3D images are reconstructed by combining different projection position images. The results of the experiments conducted indicate that the infrared and visible light images represent the flame preheating and flame reaction zones, respectively. The polarized image can be obtained by computing the degree of linear polarization (DOLP) of raw images captured by the polarization camera. We discover that the highlighted regions in the DOLP images lie outside the infrared and visible light zones; they are insensitive to the flame reaction and have different spatial structures for different fuels. We deduce that the combustion product particles cause endogenic polarized scattering, and that the DOLP images represent the flame recombination zone. This study focuses on the combustion mechanisms, such as the formation of combustion products and quantitative flame composition and structure.

A Self-Reference Interference Sensor Based on Coherence Multiplexing

Interferometry has been widely used in biosensing due to its ability to acquire molecular affinity and kinetics in real-time. However, interferometric-based sensors are susceptible to environmental disturbances, including temperature and non-specific binding of target molecules, which reduces their detection robustness. To address this shortcoming, this paper proposes a self-referencing interference sensor based on coherence multiplexing to resist environmental disturbances. The proposed sensor can address temperature and non-specific binding, but it is not limited only to these types of disturbances. In the proposed sensor design, each sensor signal is encoded using a specific optical path difference determined by the optical thickness of a sensor chip. In addition, two sensor signals for disturbances tracking and biomolecule detection are detected simultaneously without additional cost to the second spectrometer and then differenced to achieve real-time self-reference. The temperature fluctuations experiments and specific binding experiments of protein A to IgG are performed to verify the performance of the proposed sensor. The results demonstrate that the proposed sensor can eliminate non-specific binding and temperature disturbances in real-time during biomolecule detection, achieving higher detection robustness. The proposed sensor is suitable for applications that require large-scale testing of biomolecular interactions, such as drug screening.

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.

Tomographic imaging using multi-simultaneous measurements (TIMes) for flame emission reconstructions

The method of tomographic imaging using multi-simultaneous measurements (TIMes) for flame emission reconstructions is presented. Measurements of the peak natural CH* chemiluminescence in the flame and luminescence from different vaporised alkali metal salts that were seeded in a multi-annulus burner were used. An array of 29 CCD cameras around the Cambridge-Sandia burner was deployed, with 3 sets of cameras each measuring a different colour channel using bandpass optical filters. The three-dimensional instantaneous and time-averaged fields of the individual measured channels were reconstructed and superimposed for two new operating conditions, with differing cold flow Reynolds numbers. The contour of the reconstructed flame front followed the interface between the burnt side of the flame, where the alkali salt luminescence appears, and the cold gas region. The increased mixing between different reconstructed channels in the downstream direction that is promoted by the higher levels of turbulence in the larger Reynolds number case was clearly demonstrated. The TIMes method enabled combustion zones originating from different streams and the flame front to be distinguished and their overlap regions to be identified, in the entire volume.

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.

Computed tomography of chemiluminescence for the measurements of flames confined within a cylindrical glass

Computed tomography of chemiluminescence (CTC) is one kind of volumetric tomography which can recover 3D flame structures and has found extensive applications for spatiotemporally resolved measurements of flames. However, the existing CTC techniques rely on the pinhole model and fail when the flames are confined within a cylindrical glass due to image distortion caused by the refraction on both the internal and external surfaces of the glass. In this work, a refined camera model was developed by combining the pinhole camera model with Snell's laws using a reverse ray-tracing method to incorporate the effects of refraction. A proof-of-concept demonstration of CTC based on the refined camera model was conducted on a swirl flame confined within a 20-mm-thick K9 glass. The results proved the superiority of such technique against the existing version in terms of reconstruction accuracy. This work is expected to be especially useful for the study of combustion phenomena such as combustion instability for which the flames are typically confined within cylindrical combustors.

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.

High spatial resolution computed tomography of chemiluminescence with densely sampled parallel projections

Computed tomography of chemiluminescence (CTC) is an effective tool for combustion diagnostics by using optical detectors to capture the projections of luminescence from multiple views and realizing the three-dimensional (3D) reconstruction by computed tomography (CT) theories. In the existing CTC, ordinary commodity lenses were employed in the system for imaging, the imaging effects complicate the projection model and the low sampling rate decreases the spatial resolution and reconstruction accuracy. In classical CT techniques, parallel projection based on 2D Radon transform is the simplest model, which has been widely used in CT applications. In this work, double telecentric lens is introduced in CTC to realize the acquisition of parallel projection with high sampling rate. Despite the parallel projection CT theories have been well studied, there are still a few theoretical and technological drawbacks need to be solved when utilizing double telecentric lens in CTC. Firstly, a simple method based on bilinear interpolation is studied to improve the calculation accuracy of the weight matrix. Secondly, the exact reconstruction condition for parallel projections is studied based on the discrete Radon transform theory. It establishes the theoretical relationship of the reconstruction quality and the sampling rate of the projections, the number of views, the range and the spatial resolution of the reconstructed region. In experiment, camera calibration technique for double telecentric lens is studied, and the results of which are used for projection correction. The tomographic reconstructions of an axisymmetric flame demonstrate the feasibility and accuracy of the studies.

3D particle field reconstruction method based on convolutional neural network for SAPIV

Synthetic aperture particle image velocimetry (SAPIV) provides a non-invasive means of revealing the physics of complex flows using a compact camera array to resolve the 3D flow field with high temporal and spatial resolution. Intensity-threshold-based methods of reconstructing the flow field are unsatisfactory in nonuniform illuminated fluid flows. This article investigates the characteristics of the focused particles in re-projected image stacks, and presents a convolutional neural network (CNN)-based particle field reconstruction method. The CNN architecture determines the likelihood of each area containing focused particles in the re-projected 3D image stacks. The structural similarity between the images projected by the reconstructed particle field and the images captured from the cameras is then computed, allowing in-focus particles to be extracted. The feasibility of our method is investigated through synthetic simulations and experiments. The results show that the proposed technique achieves remarkable performance, paving the way for non-uniformly illuminated particle field applications in 3D velocity measurements.

On the quantification of spatial resolution for three-dimensional computed tomography of chemiluminescence

Three-dimensional computed tomography of chemiluminescence (CTC) for combustion diagnostics is attracting a surged research interest due to recent progress in sensor technologies and reduced costs of high-speed cameras. For example, it has been applied to recover the 3D distributions of intermediate chemical species such as CH* and OH*, heat release rate, and flame topology. Although these applications were demonstrated to be successful, there are still a few drawbacks of this technique that have not be cured. For example, to the best of the authors' knowledge, all the imaging models that have been developed so far ignore the imperfections of cameras such as lens distortion and skewness. However, this will unavoidably introduce errors into the weight matrix. In addition, spatial resolution of a CTC system is a critical performance parameter. However, it has only been studied qualitatively and no quantitative quantification method is reported so far. This work aims to solve these problems by improving the imaging model and developing a method based on edge spread function for the quantification of spatial resolution. Although this work is conducted under the context of CTC for combustion diagnostics, it also provides useful insights for other tomographic modalities such as volumetric laser-induced fluorescence and tomographic laser-induced incandescence.

Demonstration of 3D computed tomography of chemiluminescence with a restricted field of view

Three-dimensional imaging techniques have experienced a surge in research interest during the past few years due to advancements in both hardware, i.e., the sensor arrays and data acquisition systems, and new imaging concepts, such as light field imaging and compressed sensing. Computed tomography of chemiluminescence (CTC) is an intriguing technique for combustion diagnostics due to its ease of implementation, as no excitation source is required in measurements. It has been applied extensively for the retrieval of intermediate species such as CH^*/OH^*, from which the flame topology can be obtained. However, all previous demonstrations or applications were performed under the assumption that a complete field of view is available for all projections. However, this prerequisite cannot be guaranteed for some practical scenarios, such as engine measurements, in which optical access is extremely limited and a portion of the field of view is unavoidably blocked, especially when a considerable number of projections are required. This work aims to develop an improved CTC modality that can handle projections with a restricted field of view, and to suggest the best strategy for tomographic reconstruction under such experimental conditions. Although this technique is discussed under the context of combustion diagnostics, it can also be useful and adapted for other tomographic areas, such as biomedical imaging.