A Feasibility Study on Using near Infrared Spectroscopy to Classify Straw-Coal Blends

Abstract

Rapid classification of biomass, coal and biomass-coal blends is very important for developing appropriate subsidy policies and methods for biomass co-firing power generation in China. The use of near infrared reflectance (NIR) spectroscopy to classify straw, coal and straw-coal blends was explored in this study. Eighty-one straw samples, 9 coal samples, 81 straw-coal blends samples with straw content from 91% to 99% (blends1) and 90 straw-coal blends samples with straw content from 1% to 30% (blends2) were prepared and separated into a calibration set and an external prediction set. Spectra were scanned by a Fourier transform-NIR spectrometer. Raw spectra of the samples were mean centred and compared using discriminant analysis. Overall, the correct classification percentages for straw, blends1, blends2 and coal samples were 98.8%, 90.1%, 83.3% and 66.7%, respectively. The results show that the NIR technique could provide excellent classification between straw and coal. The spectra of straw-coal blends with straw content less than 98% can be classified exactly from calibrations based on pure straw and the spectra of straw-coal blends with straw content greater than 20% can be well classified from calibrations based on pure coal. It is concluded that NIR is a feasible method for rapid classification of straw, coal and straw-coal blends.

Keywords

near infrared spectroscopy NIR co-firing biomass straw coal renewable energy

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