Laser-induced breakdown spectroscopy (LIBS) is a new technology suitable for classification of various materials. This paper proposes a hybrid classification scheme for coal, municipal sludge and biomass by using LIBS combined with K-means and support vector machine (SVM) algorithm. In the study, 10 samples were classified in 3 groups without supervision by K-means clustering, then a further supervised classification of 6 kinds of biomass samples by SVM was carried out. The results show that the comprehensive accuracy of the hybrid classification model is over 98%. In comparison with the single SVM classification model, the hybrid classification model can save 58.92% of operation time while guaranteeing the accuracy. The results demonstrate that the hybrid classification model is able to make an efficient, fast and accurate classification of coal, municipal sludge and biomass, furthermore, it is precise for the detection of various kinds of biomass fuel.

The combustion kinetic characteristics of wood powder and pellet were investigated within thermogravimetric analyser (TGA) and tube furnace system. The kinetic parameters of these two different forms of woody fuel were measured and derived by double-step-and-double-equal and isothermal method, respectively. The results showed that the combustion mechanisms of wood powder kept consistent through the whole process, while the combustion mechanisms of wood pellet differed significantly between the volatile and char combustion stages. The most probable mechanism functions of the two different forms of woody fuel were not the same due to the differences in internal heat and mass transfer properties. In addition, activation energy values varied from 92.33 kJ·mol−1 for wood powder to 71.20 kJ·mol−1 for wood pellet, while the preexponential factor value of wood powder (2.55×108 s−1) was far greater than the one of the wood pellet (78.55 s−1) by seven orders of magnitude.

Abstract. Some specific bamboo pellets were combusted in a tube furnace individually in different constant air flow rates (3,4 and 5 L/min) and at various temperatures (800, 900, 1000, 1100 and 1200℃), in order to investigate the dynamic emission characteristics during various respective combustion processes. The results indicate that the increase of carbon monoxide(CO) amounts in 3 L/min air flow rate was caused by kinetic controlled combustion at 800 ℃ and by diffusion controlled combustion at 1100 and 1200 ℃. The yield and concentration of nitric oxide(NO) reach the maximums at 900 ℃, as well as the conversion rate from fuel-N to NO (9.17%). As combustion temperature increases, the yield and concentration of NO decline from the peak, and the conversion rate (from fuel-N to NO) falls to the lowest value (3.90%) at 1200 ℃ in 3 L/min air flow rate. When a bamboo pellet burns sufficiently almost none sulfur dioxide(SO 2 ) was released , while the S element can be kept in the ash or discharged in high-temperature flue gas in the form of sulfate which is converted from fuel-S. In oxy-lean atmosphere, SO 2 generates from the decomposition or oxidation of organic S during early devolatilisation, wheares more fuel-S probably are released in the forms of H 2 S and CaS.

The thermal characteristics and kinetics of teak sawdust (TS), sewage sludge (SS), and their blends were evaluated during combustion by thermogravimetric analysis (TGA). The samples were prepared as pure fuel, TS and SS; blends, where TS was mixed with SS at the ratios of 75:25, 50:50, and 25:75; and as fuels with additives, where the fuels above were mixed with activated carbon (AC), CaO, MgO, and ZnO individually at a proportion of 5 wt%. Some characteristic values of combustion were evaluated, such as Ti, Tb, and Mf, and the combustion behaviors of the fuels were compared. The difference between measurement and weighted calculation of the weight left proportion (∆M), weight loss rate (∆DTG), and activation energy (∆E) were introduced for analysis. Blending with teak sawdust improved the combustion performance of sewage sludge. As the content of the sewage sludge increased, the pre-exponential factor varied from 1.76 x 105 s-1(100T) to 1.01 x 101 s-1(100S), while the global activation energy decreased from 74 kJ/mol (100T) to 38 kJ/mol (100S). Sewage sludge burned more completely when blended with teak sawdust at ratios of greater than 50 wt%. All four additives inhibited the oxidation of the blends around the ignition point.