This paper presents a reconstruction model of three-dimensional temperature distribution in furnace based on radiative energy images captured by charge-coupled device （CCD） cameras within the visible wavelength range. Numerical simulation case was used in this study and a zigzag eccentric temperature distribution was assumed to verify the model. Least square QR-factorization （LSQR） method was introduced to deal with reconstruction equation. It is found that the reconstructed temperature distributions in low-temperature areas had some fluctuations and high-temperature areas were reconstructed well. The whole reconstruction relative error was mainly due to errors in low-temperature areas and the relative error for highest-temperature reconstruction was quite small.
Laser-induced incandescence (LII) has received increasing attention as a potentially powerful technique for in-situ measuring of the volume fraction and primary size of soot particles in combustion systems. In this study, a 3D Monte Carlo simulation combined with a Mie equation was developed to analyze the influence of spectral absorption and scattering on the measured LII flux emitted by soot particles. This paper represents a first attempt to analyze soot measurement using the LII technique in coal combustion products. The combustion products of gases (CO2, N2), soot, and fly-ash particles, present between the location of laser-excited soot and the LII flux receiver. The simulation results indicated that an almost Beer-Lambert exponential decrease in LII flux occurred with an increase in the volume fraction of soot particles, while a nearly linear decrease occurred with an increase in the volume fraction of fly-ash particles. The results also showed that scattering effects of both soot and fly-ash particles on the LII flux could be neglected. Compared with the absorption of gases, a decrease of 20% of LII flux was observed with soot particles, and a decrease of 10% with fly-ash particles.
This paper presents a new approach to the on-line tracking of pulverized coal and biomass fuels through flame spectrum analysis.A flame detector containing four photodiodes is used to derive multiple signals covering a wide spectrum of the flame from visible,near-infrared and mid-infrared spectral bands as well as a part of far-infrared band.Different features are extracted in time and frequency domains to identify the dynamic "fingerprints" of the flame.Fuzzy logic inference techniques are employed to combine typical features together and infer the type of fuel being burnt.Four types of pulverized coal and five types of biomass are burnt on a laboratory-scale combustion test rig.Results obtained demonstrate that this approach is capable of tracking the type of fuel under steady combustion conditions.
利用CCD摄像机得到的火焰辐射能图像进行炉膛三维火焰温度场重建,但温度重建矩阵方程是一个不适定方程组,从而重建问题是一个不适定问题.应用截断奇异值分解(truncated singular value decomposition,TSVD)的正则化方法对该不适定方程组进行求解,并且采用了L曲线法对正则化参数进行选取.结合重建算例,采用奇异值分解(singular value decomposition,SVD)与离散Picard条件对这个不适定问题进行了分析.重建结果表明,在不同的模拟测量误差下,TSVD能够成功得到合理的解,重建温度场较好的再现了原始假设温度场的特征.
