Fast flame temperature estimation using a point diffraction interferometer and non-negative least square method

Some of the interferometry methods proposed for flame temperature measurements from its projection could be complex and demand so much computing time. Assuming a circular symmetric and smooth flame temperature distribution, it is possible to use a linear combination of Gaussian functions with weights constrained to non-negative values

Simulation of flame temperature reconstruction through multi-plenoptic camera techniques

Due to the variety of burner structure and fuel mixing, the flame temperature distribution is not only manifold but also complex. Therefore, it is necessary to develop an advanced temperature measurement technique, which can provide not only the adequate flame radiative information but also reconstruct the complex temperature accurately. This paper presents a comprehensive simulation of flame temperature reconstruction through multi-plenoptic camera techniques. A novel multi-plenoptic camera imaging technique is proposed which is able to provide adequate flame radiative information only from two different directions and to reconstruct the three dimensional (3D) temperature of a flame. An inverse algorithm i.e., Non-negative Least Squares is used to reconstruct the flame temperature. To verify the reconstruction algorithm, two different temperature distributions such as unimodal axisymmetric and bimodal asymmetric are used. Numerical simulations are carried out to evaluate the performance of the technique. It has been observed that the reconstruction accuracy decreases with the increasing of signal-to-noise ratios. However, compared with the single plenoptic and conventional multi-camera techniques, the proposed method has the advantages of lower relative error and better reconstruction quality and stability even with the higher SNRs for both temperature distributions. Therefore, the proposed multi-plenoptic camera imaging technique is capable of reconstructing the complex 3-D temperature fields more accurately

Flame temperature reconstruction through multi-plenoptic camera technique

Due to the variety of burner structure and fuel mixing, the flame temperature distribution is not only irregular but also complex. Therefore, it is necessary to develop an advanced temperature measurement technique, which can provide not only adequate flame radiative information but also reconstruct complex flame temperature accurately. In this paper, a novel multi-plenoptic camera imaging technique is proposed which is not only provide adequate flame radiative information from two different directions but also reconstruct the complex flame temperature distribution accurately. An inverse algorithm i.e., Non-Negative Least Squares is used to reconstruct the flame temperature. The bimodal asymmetric temperature distribution is considered to verify the feasibility of the proposed system. Numerical simulations and experiments were carried out to evaluate the performance of the proposed technique. Simulation results demonstrate that the proposed system is able to provide higher reconstruction accuracy although the reconstruction accuracy decreases with the increase of noise levels. Meanwhile, compared with the single plenoptic and conventional multi-camera techniques, the proposed method has the advantages of lower relative error and better reconstruction quality even with higher noise levels. The proposed technique is further verified by experimental studies. The experimental results also demonstrate that the proposed technique is effective and feasible for the reconstruction of flame temperature. Therefore, the proposed multi-plenoptic camera imaging technique is capable of reconstructing the complex flame temperature fields more precisely

Three Dimensional Temperature Measurement of Combustion Flames using a Single Monochromatic CCD Camera

This paper presents an imaging-based instrumentation system for three-dimensional (3-D) temperature measurement of a combustion flame. A combination of image-processing techniques and two-color radiation thermometry is used to first reconstruct band-limited grayscale representations of the flame and then to determine its temperature distribution. The reconstruction process assumes rotational symmetry in the structure of the flame. A series of experiments has been conducted on a laboratory-scale combustion rig to evaluate the performance of the system. The results obtained demonstrate the capability of the system to determine flame temperature on a 3-D basis

RECONSTRUCTION OF BURNER FLAMES THROUGH DEEP LEARNING

This MSc thesis reports the design, implementation, and experimental evaluation of a deep learning-based system for the three-dimensional (3-D) reconstruction and visualisation of fossil-fired burner flames. A literature review is given to examine all existing techniques for 3-D visualisation and characterisation of flames. Methodologies and techniques for the 3-D reconstruction of burner flames using optical tomographic and deep learning (DL) techniques are presented, together with a discussion of their advantages and limitations in their applications. Technical requirements and existing problems of the reviewed techniques are discussed. A technical strategy, incorporating numerical simulations, DL, digital image processing and optical tomographic techniques is proposed for the reconstruction and visualisation of a flame. Based on this strategy, a 3-D flame reconstruction and visualisation system based on DL is developed. The system consists of a trained convolutional neural network (CNN) based network model and the use of a third-party software tool for visualisation. The system can use flame images acquired concurrently from eight different directions of a burner and perform a 3-D reconstruction of the flame. A numerical simulation is performed initially to examine the suitability of the DL algorithm proposed, ground truth data are generated using a mathematical model designed to mimic a flame structure and 2-D projection data are generated from each ground truth. A modified CNN model with a 1-D output dense layer is established and trained for the reconstruction of the 3-D Gaussian distribution. To determine the optimal network model architecture for this solution, various experiments were conducted using different network model parameters. A detailed description of a CNN-based network implemented for the numerical solutions is presented. A series of experiments was conducted using flame data obtained from a laboratory-scale combustion test rig to evaluate the performance of the established CNN model. These included implementing code to perform image processing routines to prepare the dataset collected from the laboratory-scale combustion test rig. Additional datasets were also generated using OpenCV morphological transformation operations to augment the original dataset. The obtained results have proven that the implemented and trained CNN network model can reconstruct the cross-sectional slices of a burner flame based on the images obtained under various combustion conditions. It was also possible to obtain a 3-D flame structure from the reconstructed cross-sectional flame data using a 3-D visualisation tool. Results from the experiments and the performance of the implemented 3-D flame reconstruction and visualisation system based on DL are presented and discussed

One-dimensional emission tomography of temperature profile in coal-fired boiler furnace by using radiation pyrometry

Predmet istraživanja ove doktorske disertacije su metode za istovremeno merenje temperaturnog profila plamena, položaja termalnog fokusa i koeficijenta prigušenja u ložištu kotla termoelektrane na ugalj. Opisan je novi merni postupak koji zajedno sa konstruisanim instrumentom za merenje temperature, predstavlja posebnu vrstu bezkontaktne metode. Novi instrument koji je korišćen u tu svrhu, predstavlja specijalan uređaj koji se zasniva na dvobojnom pirometru. Pirometar je u produžetku spojen sa dugačkom cevi koja ima poseban sistem hlađenja vodom, zbog čega je moguće izvršiti direktna merenja karakteristika plamena duboko u unutrašnjosti kotla. Na taj način su u svakom trenutku procesa sagorevanja dostupni podaci o temperaturnoj raspodeli, maksimalnoj i minimalnoj temperaturi, položaju termalnog fokusa, kao i vrednosti koeficijenta prigušenja...The objectives of the research of this doctoral dissertation are the methods for the simultaneous measurement of the temperature profile of the flame, the position of the thermal focus and the absorption coefficient in the coal-fired boiler of the thermal power plant. A new measuring procedure is described which, together with the constructed temperature measurement instrument, is a special type of contactless method. The new instrument used for this purpose is a device based on a two-color pyrometer. The pyrometer is connected in the extension with a long tube that has a water cooling system This enables direct measurements of the flame characteristics deep inside the boiler. Thus at each stage of the combustion process, temperature distribution data, maximum and minimum temperature, the position of the thermal focus, as well as values of the coefficient of attenuation are available..

Flame stability and burner condition monitoring through optical sensing and digital imaging

This thesis describes the design, implementation and experimental evaluation of a prototype instrumentation system for flame stability and burner condition monitoring on fossil-fuel-fired furnaces. A review of methodologies and technologies for the monitoring of flame stability and burner condition is given, together with the discussions of existing problems and technical requirements in their applications. A technical strategy, incorporating optical sensing, digital imaging, digital signal/image processing and soft computing techniques, is proposed. Based on this strategy, a prototype flame imaging system is developed. The system consists of a rigid optical probe, an optical-bearn-splitting unit, an embedded photodetector and signal-processing board, a digital camera, and a mini-motherboard with associated application software. Detailed system design, implementation, calibration and evaluation are reported. A number of flame characteristic parameters are extracted from flame images and radiation signals. Power spectral density, oscillation frequency, and a proposed universal flame stability index are used for the assessment of flame stability. Kernel-based soft computing techniques are employed for burner condition monitoring. Specifically, kernel principal components analysis is used for the detection of abnormal conditions in a combustion process, whilst support vector machines are used for the prediction of NO x emission and the identification of flame state. Extensive experimental work was conducted on a 9MW th heavy-oil-fired combustion test facility to evaluate the performance of the prototype system and developed algorithms. Further tests were carried out on a 660MWth heavy-oil-fired boiler to investigate the cause of the boiler vibration from a flame stability point of view. Results Obtained from the tests are presented and discussed

Three-dimensional visualisation and quantitative characterisation of fossil fuel flames using tomography and digital imaging techniques

This thesis describes the design, implementation and experimental evaluation of a prototype instrumentation system for the three-dimensional (3-D) visualisation and quantitative characterisation of fossil fuel flames. A review of methodologies and technologies for the 3-D visualisation and characterisation of combustion flames is given, together with a discussion of main difficulties and technical requirements in their applications. A strategy incorporating optical sensing, digital image processing and tomographic reconstruction techniques is proposed. The strategy was directed towards the reconstruction of 3-D models of a flame and the subsequent quantification of its 3-D geometric, luminous and fluid dynamic parameters. Based on this strategy, a flame imaging system employing three identical synchronised RG B cameras has been developed. The three cameras, placed equidistantly and equiangular on a semicircle around the flame, captured six simultaneous images of the flame from six different directions. Dedicated computing algorithms, based on image processing and tomographic reconstruction techniques have been developed to reconstruct the 3-D models of a flame. A set of geometric, luminous and fluid dynamic parameters, including surface area, volume, length, circularity, luminosity and temperature are determined from the 3-D models generated. Systematic design and experimental evaluation of the system on a gas-fired combustion rig are reported. The accuracy, resolution and validation of the system were also evaluated using purpose-designed templates including a high precision laboratory ruler, a colour flat panel and a tungsten lamp. The results obtained from the experimental evaluation are presented and the relationship between the measured parameters and the corresponding operational conditions are quantified. Preliminary investigations were conducted on a coal-fired industry-scale combustion test facility. The multi-camera system was reconfigured to use only one camera due to the restrictions at the site facility. Therefore the property of rotational symmetry of the flame had to be assumed. Under such limited conditions, the imaging system proved to provide a good reconstruction of the internal structures and luminosity variations inside the This thesis describes the design, implementation and experimental evaluation of a prototype instrumentation system for the three-dimensional (3-D) visualisation and quantitative characterisation of fossil fuel flames. A review of methodologies and technologies for the 3-D visualisation and characterisation of combustion flames is given, together with a discussion of main difficulties and technical requirements in their applications. A strategy incorporating optical sensing, digital image processing and tomographic reconstruction techniques is proposed. The strategy was directed towards the reconstruction of 3-D models of a flame and the subsequent quantification of its 3-D geometric, luminous and fluid dynamic parameters. Based on this strategy, a flame imaging system employing three identical synchronised RG B cameras has been developed. The three cameras, placed equidistantly and equiangular on a semicircle around the flame, captured six simultaneous images of the flame from six different directions. Dedicated computing algorithms, based on image processing and tomographic reconstruction techniques have been developed to reconstruct the 3-D models of a flame. A set of geometric, luminous and fluid dynamic parameters, including surface area, volume, length, circularity, luminosity and temperature are determined from the 3-D models generated. Systematic design and experimental evaluation of the system on a gas-fired combustion rig are reported. The accuracy, resolution and validation of the system were also evaluated using purpose-designed templates including a high precision laboratory ruler, a colour flat panel and a tungsten lamp. The results obtained from the experimental evaluation are presented and the relationship between the measured parameters and the corresponding operational conditions are quantified. Preliminary investigations were conducted on a coal-fired industry-scale combustion test facility. The multi-camera system was reconfigured to use only one camera due to the restrictions at the site facility. Therefore the property of rotational symmetry of the flame had to be assumed. Under such limited conditions, the imaging system proved to provide a good reconstruction of the internal structures and luminosity variations inside the This thesis describes the design, implementation and experimental evaluation of a prototype instrumentation system for the three-dimensional (3-D) visualisation and quantitative characterisation of fossil fuel flames. A review of methodologies and technologies for the 3-D visualisation and characterisation of combustion flames is given, together with a discussion of main difficulties and technical requirements in their applications. A strategy incorporating optical sensing, digital image processing and tomographic reconstruction techniques is proposed. The strategy was directed towards the reconstruction of 3-D models of a flame and the subsequent quantification of its 3-D geometric, luminous and fluid dynamic parameters. Based on this strategy, a flame imaging system employing three identical synchronised RG B cameras has been developed. The three cameras, placed equidistantly and equiangular on a semicircle around the flame, captured six simultaneous images of the flame from six different directions. Dedicated computing algorithms, based on image processing and tomographic reconstruction techniques have been developed to reconstruct the 3-D models of a flame. A set of geometric, luminous and fluid dynamic parameters, including surface area, volume, length, circularity, luminosity and temperature are determined from the 3-D models generated. Systematic design and experimental evaluation of the system on a gas-fired combustion rig are reported. The accuracy, resolution and validation of the system were also evaluated using purpose-designed templates including a high precision laboratory ruler, a colour flat panel and a tungsten lamp. The results obtained from the experimental evaluation are presented and the relationship between the measured parameters and the corresponding operational conditions are quantified. Preliminary investigations were conducted on a coal-fired industry-scale combustion test facility. The multi-camera system was reconfigured to use only one camera due to the restrictions at the site facility. Therefore the property of rotational symmetry of the flame had to be assumed. Under such limited conditions, the imaging system proved to provide a good reconstruction of the internal structures and luminosity variations inside the flame. Suggestions for future development of the technology are also reported

Bayesian Methods for Gas-Phase Tomography

Gas-phase tomography refers to a set of techniques that determine the 2D or 3D distribution of a target species in a jet, plume, or flame using measurements of light, made around the boundary of a flow area. Reconstructed quantities may include the concentration of one or more species, temperature, pressure, and optical density, among others. Tomography is increasingly used to study fundamental aspects of turbulent combustion and monitor emissions for regulatory compliance. This thesis develops statistical methods to improve gas-phase tomography and reports two novel experimental applications. Tomography is an inverse problem, meaning that a forward model (calculating measurements of light for a known distribution of gas) is inverted to estimate the model parameters (transforming experimental data into a gas distribution). The measurement modality varies with the problem geometry and objective of the experiment. For instance, transmittance data from an array of laser beams that transect a jet may be inverted to recover 2D fields of concentration and temperature; and multiple high-resolution images of a flame, captured from different angles, are used to reconstruct wrinkling of the 3D reacting zone. Forward models for gas-phase tomography modalities share a common mathematical form, that of a Fredholm integral equation of the first-kind (IFK). The inversion of coupled IFKs is necessarily ill-posed, however, meaning that solutions are either unstable or non-unique. Measurements are thus insufficient in themselves to generate a realistic image of the gas and additional information must be incorporated into the reconstruction procedure. Statistical inversion is an approach to inverse problems in which the measurements, experimental parameters, and quantities of interest are treated as random variables, characterized by a probability distribution. These distributions reflect uncertainty about the target due to fluctuations in the flow field, noise in the data, errors in the forward model, and the ill-posed nature of reconstruction. The Bayesian framework for tomography features a likelihood probability density function (pdf), which describes the chance of observing a measurement for a given distribution of gas, and prior pdf, which assigns a relative plausibility to candidate distributions based on assumptions about the flow physics. Bayes’ equation updates information about the target in response to measurement data, combining the likelihood and prior functions to form a posterior pdf. The posterior is usually summarized by the maximum a posteriori (MAP) estimate, which is the most likely distribution of gas for a set of data, subject to the effects of noise, model errors, and prior information. The framework can be used to estimate credibility intervals for a reconstruction and the form of Bayes’ equation suggests procedures for improving gas tomography. The accuracy of reconstructions depends on the information content of the data, which is a function of the experimental design, as well as the specificity and validity of the prior. This thesis employs theoretical arguments and experimental measurements of scalar fluctuations to justify joint-normal likelihood and prior pdfs for gas-phase tomography. Three methods are introduced to improve each stage of the inverse problem: to develop priors, design optimal experiments, and select a discretization scheme. First, a self-similarity analysis of turbulent jets—common targets in gas tomography—is used to construct an advanced prior, informed by an estimate of the jet’s spatial covariance. Next, a Bayesian objective function is proposed to optimize beam positions in limited-data arrays, which are necessary in scenarios where optical access to the flow area is restricted. Finally, a Bayesian expression for model selection is derived from the joint-normal pdfs and employed to select a mathematical basis to reconstruct a flow. Extensive numerical evidence is presented to validate these methods. The dissertation continues with two novel experiments, conducted in a Bayesian way. Broadband absorption tomography is a new technique intended for quantitative emissions detection from spectrally-convolved absorption signals. Theoretical foundations for the diagnostic are developed and the results of a proof-of-concept emissions detection experiment are reported. Lastly, background-oriented schlieren (BOS) tomography is applied to combustion for the first time. BOS tomography employs measurements of beam steering to reconstruct a fluid’s optical density field, which can be used to infer temperature and density. The application of BOS tomography to flame imaging sets the stage for instantaneous 3D combustion thermometry. Numerical and experimental results reported in this thesis support a Bayesian approach to gas-phase tomography. Bayesian tomography makes the role of prior information explicit, which can be leveraged to optimize reconstructions and design better imaging systems in support of research on fluid flow and combustion dynamics