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Innovative recognition-sorting procedures applied to solid waste: the hyperspectral approach

机译：创新的识别排序程序适用于固体废物：高光谱法

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Waste materials characterization and recognition can be obtained through their surface spectral response. Such a goal can be reached adopting specialized devices that are able to develop acquisition strategies based on the collection of hyperspectral images. The analyses of the detected spectra can give useful information concerning the investigated material surface properties, status and physical-chemical attributes. This last aspect can be utilized to define and implement on-line procedures aimed to recognize different particulate solid waste as they result after specific processing/selection actions. The present study addressed the application of hyperspectral imaging approach for compost products characterization, in order to develop control strategies to be implemented at the plant scale. Reflectance spectra of selected compost samples have been acquired in the visible-near infrared field (VIS-NIR): 400-1000 nm. Correlations have been established between the physical-chemical characteristics of the different compost products and their detected reflectance spectral signature.
机译：废料表征和识别可以通过它们的表面光谱响应获得。可以采用这种专业设备来达到这样的目标，该设备能够根据高光谱图像的集合开发采集策略。检测到的光谱的分析可以提供有关所研究的材料表面性质，状态和物理化学属性的有用信息。该最后一个方面可用于定义和实现在线过程，该过程旨在识别不同的微粒固体废物，因为它们在特定的处理/选择动作之后导致。本研究解决了高光谱成像方法对堆肥产品表征的应用，以制定在植物规模处实施的控制策略。已经在可见的近红外场（Vis-Nir）中获得了所选堆叠样品的反射光谱：400-1000nm。在不同堆肥产品的物理化学特征与检测到的反射光谱签名之间建立了相关性。

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