Search

This paper presents a method to invert the two-dimensional distribution of a temperature and volume concentration of soot particles from color images. By using numerical simulation, the temperature field and particle volume-concentration field of a non-uniform soot flame are simultaneously reconstructed using the wide-response spectrum of a color CCD camera without adding monochromatic filters. The influence of number of cameras, error of camera position angle, measurement noise and different reconstruction algorithms on measurement accuracy are analyzed. The numerical-simulation results demonstrate that camera-position angle errors play a crucial role in the reconstruction accuracy. In addition, increasing the number of cameras can improve the reconstruction result accuracy. Compared with the least squares algorithm, the Tikhonov-regularization algorithm has a stronger anti-noise ability and can resist 39 dB of noise. The conclusions obtained in this paper are helpful to guide following experimental studies. [ABSTRACT FROM AUTHOR]

Abstract: The paper presents the inversion of two-dimensional (2-D) distributions of temperature and soot volume fraction from visible flame images. Experimental investigation was conducted in an axisymmetric, co-flow, ethylene/air laminar diffusion flame. A color digital camera was used to capture the flame image in visible spectrum. With consideration of the broad response spectrum of R, G, and B bands of the camera, the directional emissive power of R and G bands were calibrated and used to reconstruct 2-D distributions of temperature and soot volume fraction in the flame. The profiles of temperature and soot volume fraction reconstructed in this paper are both in good agreement with those obtained by multi-wavelength emission technique. The preliminary results showed that this technique is reliable and effective to diagnose combustion processes of sooting flames. [Copyright &y& Elsevier]