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首页> 外文期刊>Journal of near infrared spectroscopy >A feasibility study on using near infrared spectroscopy to classify straw-coal blends
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A feasibility study on using near infrared spectroscopy to classify straw-coal blends

机译:利用近红外光谱法对秸秆与煤炭混合物进行分类的可行性研究

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摘要

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.
机译:对生物质,煤炭和生物质-煤混合气进行快速分类,对于制定适用于中国的生物质共燃发电的补贴政策和方法非常重要。在这项研究中,探索了使用近红外反射(NIR)光谱对秸秆,煤炭和秸秆煤混合物进行分类的方法。制备了81个秸秆样品,9个煤样品,81个秸秆含量为91%至99%(掺合物1)的秸秆煤混合物样品和90个秸秆含量为1%至30%(掺合物2)的秸秆煤混合物样品,分为校准集和外部预测集。用傅立叶变换-NIR光谱仪扫描光谱。将样品的原始光谱平均居中并使用判别分析进行比较。总体而言,秸秆,混合物1,混合物2和煤样品的正确分类百分比分别为98.8%,90.1%,83.3%和66.7%。结果表明,近红外技术可以为秸秆和煤炭之间提供良好的分类。秸秆含量低于98%的秸秆煤混合物的光谱可以根据基于纯秸秆的标定值准确分类,秸秆含量大于20%的秸秆煤混合物的光谱可以根据基于纯煤的标定值很好地分类。结论是,近红外光谱法是一种对秸秆,煤和秸秆煤混合物进行快速分类的可行方法。

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