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Quality assurance of torrefied biomass using RGB, visual and near infrared (hyper) spectral image data

机译:使用RGB,可见光和近红外(超)光谱图像数据对经过烘焙的生物质进行质量保证

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Visible and near infrared imaging techniques for analysing characteristics of torrefied biomass were evaluated for possible use in future online process control. The goal of such a control system is to identify products with the desired properties and reject products outside the specification. Two pushbroom hyperspectral cameras with different wavelength regions and a commercial digital colour camera were evaluated. The hyperspectral cameras, short wave infrared (SWIR) and visible-near infrared (VNIR), covered the ranges of 1000-2500nm and 400-1000nm, respectively. The biomass was produced according to an experimental design in a torrefaction pilot plant at different temperatures, residence times, and nitrogen and steam flow rates to obtain a wide range of different characteristics and qualities of torrefied material. Chemical characteristics, heating values and milling energy of the different torrefied materials were analysed or calculated using standardized procedures and were used for calibration. For the hyperspectral images, a principal-component analysis was performed on the absorbance spectra. The score plots and score images were used interactively to separate background, outlier pixels and shading effects from sample signal. Averaged spectra of individual torrefied woodchips were used. Partial least-squares regression was used to relate average spectra to heating values and chemical characteristics of the torrefied biomass. Owing to the small size of the data sets, cross-validation using leave-one-out validation was used for testing the models. The ratio of standard error of prediction to sample standard deviation (RPD) values were used for comparing the imaging techniques. For RGB images, all RPD values were 4 or lower. The RPD values for the VNIR technique were all below 5, while the SWIR images produced RPD values above 5 for eight of the 13 properties. The promising results of the SWIR technique strongly suggested that the torrefied biomass undergoes changes to chemical structures, which are not necessarily manifested as changes to the colour of the material.
机译:评估了可见和近红外成像技术,用于分析烘焙过的生物质的特性,以便将来在在线过程控制中使用。这种控制系统的目标是识别具有所需特性的产品,并剔除超出规格的产品。评估了两个具有不同波长区域的推扫式高光谱相机和一个商用数字彩色相机。高光谱摄像机短波红外(SWIR)和可见近红外(VNIR)分别覆盖1000-2500nm和400-1000nm的范围。根据实验设计,在烘焙中试设备中以不同的温度,停留时间以及氮气和蒸汽流速生产生物质,以获得广泛范围的不同特性和品质的烘焙材料。使用标准程序分析或计算了不同烘焙材料的化学特性,热值和研磨能,并将其用于校准。对于高光谱图像,对吸收光谱进行主成分分析。分数图和分数图像可以交互使用,以从样本信号中分离出背景,离群像素和阴影效果。使用了单个经过烘焙的木片的平均光谱。使用偏最小二乘回归将平均光谱与烘焙生物质的热值和化学特性相关联。由于数据集的大小,使用留一法验证的交叉验证用于测试模型。预测的标准误差与样品标准偏差(RPD)值的比率用于比较成像技术。对于RGB图像,所有RPD值均为4或更低。对于13种特性中的8种,VNIR技术的RPD值均低于5,而SWIR图像产生的RPD值均高于5。 SWIR技术的有希望的结果有力地表明,烘焙过的生物质经历了化学结构的变化,但不一定表现为材料颜色的变化。

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