This paper presents an experimental investigation, visualization and validation in the three-dimensional (3D) reconstruction of flame temperature and emissivity distributions by using optical tomographic and two-colour pyrometric techniques. A multi-camera digital imaging system comprising eight optical imaging fibres and two RGB charged-couple device (CCD) cameras are used to acquire two-dimensional (2D) images of the flame simultaneously from eight equiangular directions. A combined logical filtered back-projection (LFBP) and simultaneous iterative reconstruction and algebraic reconstruction technique (SART) algorithm is utilized to reconstruct the grey-level intensity of the flame for the two primary colour (red and green) images. The temperature distribution of the flame is then determined from the ratio of the reconstructed grey-level intensities and the emissivity is estimated from the ratio of the grey level of a primary colour image to that of a blackbody source at the same temperature. The temperature measurement of the system was calibrated using a blackbody furnace as a standard temperature source. Experimental work was undertaken to validate the flame temperature obtained by the imaging system against that obtained using high-precision thermocouples. The difference between the two measurements is found no greater than ±9%. Experimental results obtained on a laboratory-scale propane fired combustion test rig demonstrate that the imaging system and applied technical approach perform well in the reconstruction of the 3D temperature and emissivity distributions of the sooty flame.

This paper presents the design, implementation and evaluation of an instrumentation system for the stability monitoring and characterization of combustion flames. The system, incorporating optical sensing, image processing and spectral analysis techniques, is designed to monitor a range of flame characteristic parameters. The stability of the flame is assessed through statistical analysis of the flame parameters obtained. Embedded computer techniques are employed to ensure the compactness and robustness of the system. Experiments were conducted on a gas-fired combustion test rig to evaluate the system. The impact of equivalence ratio on the stability of the gaseous flame is investigated. Further trials were carried out on a 9 MWth heavy-oil-fired combustion test facility. The impact of the swirl vane angle of tertiary air on the oil-fired flames is studied. The results demonstrate the effectiveness of the system for the monitoring and characterization of the flame stability.

This paper investigates experimentally two generalized methods, i.e., a simple universal index and oscillation frequency, for the quantitative assessment of flame stability at fossilfuel-fired furnaces. The index is proposed to assess the stability of flame in terms of its color, geometry, and luminance. It is designed by combining up to seven characteristic parameters extracted from flame images. The oscillation frequency is derived from the spectral analysis of flame radiation signals. The measurements involved in these two methods do not require prior-knowledge about fuel property, burner type and other operation conditions. They can therefore be easily applied for flame stability assessment without costly and complex adaption. Experiments were carried out on a 9MWth heavy-oil-fired combustion test rig over a wide range of combustion conditions including variations in swirl vane position of tertiary air, swirl vane position of secondary air, and ratio of primary air to total air. The impact of these burner parameters on the stability of heavy oil flames is investigated by using the index and oscillation frequency proposed. The experimental results obtained demonstrate the effectiveness of the methods and the importance of maintaining a stable flame for reduced NOx emissions. It is envisaged that such methods can be easily transferred to existing flame CCTV (Closed-Circuit Television) systems and flame failure detectors in power stations for flame stability monitoring.

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The characteristics of reacting radicals in a flame are crucial for an in-depth understanding of the formation process of combustion emissions. This paper presents an algorithm for the prediction of NOx (NO and NO 2 ) emissions in flue gas through flame radical imaging, flame temperature monitoring and application of Neural Network techniques. Radiation images of flame radicals OH*, CN*, CH* and C 2 * are captured using an intensified multi-wavelength imaging system. Flame temperature is determined using a spectrometer and two-color pyrometry. Based on these images, the characteristic values of the flame radicals are extracted. These characteristic values, together with the flame temperature, are then used to predict NOx emissions. Experimental results from a laboratory-scale gas-fired combustion rig have shown the effectiveness of the proposed method for the prediction of NOx emissions.