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Classical imaging and digital imaging spectrophotometric techniques in cullets (glass fragments) sorting

机译:碎玻璃(玻璃碎片)分选中的经典成像和数字成像分光光度法

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Cullets optical sorting represents one of the oldest selection procedure applied to the field of solid waste recycling. From the original sorting strategies, mainly addressed to separate non-transparent elements (ceramics, stones, metal particles, etc.) from transparent ones (glass fragments), the attention was addressed to define procedures and actions able to separate the cullets according to their color characteristics and, more recently, to recognize transparent ceramic glass from glass. Cullets sorting is currently realized adopting , as detecting architecture, laser beam technology based devices. The sorting logic is mainly analogical. An "on-off' logic is applied. Detection is, in fact, based on the evaluation of the "characteristics" of the energy (transparent or non-transparent fragment) and the spectra (fragment color attributes) received by a detector after that cullets were crossed by a suitable laser beam light. Such an approach presents some limits related with the technology utilized and the material characteristics. The technological limits are linked to the physical dimension and the mechanical arrangement of the optics carrying out and in the signals, and with the pneumatic architectures enabling the modification of cullets trajectory to realize sorting, according to their characteristics (color and transmittance). Furthermore such devices are practically "blind" in the recognition of ceramic glasses, whose presence in the final selected material to melt, damage the full recycled glass fusion compromising the quality of the final product. In the following it will be described the work developed, and the results achieved, in order to design a full integrated classical digital imaging and spectrophotometric based approach addressed to develop suitable sorting strategies able to perform, at industrial recycling scale, the distinction of cullets both in terms of color and material typologies, that is "real glass" from "ceramic glass" fragments.
机译:碎玻璃光学分选代表了应用于固体废物回收领域的最古老的选择程序之一。从最初的分类策略开始,主要是将非透明元素(陶瓷,石头,金​​属颗粒等)与透明元素(玻璃碎片)分开,人们开始关注定义能够根据碎玻璃分离碎玻璃的程序和动作。颜色特性,以及最近从玻璃中识别出透明陶瓷玻璃的知识。目前,通过基于激光束技术的设备作为检测架构,实现了碎石分拣。排序逻辑主要是类推。应用“开-关”逻辑,检测实际上是基于对能量(透明或不透明碎片)的“特性”以及此后检测器接收到的光谱(碎片颜色属性)的评估碎玻璃被合适的激光束穿过,这种方法存在一些与所用技术和材料特性有关的限制,这些技术限制与执行和在信号中的光学器件的物理尺寸和机械布置有关,并且借助气动架构,可以根据碎玻璃的特性(颜色和透射率)修改碎玻璃的轨迹,从而实现分选;此外,这种设备在识别陶瓷玻璃时实际上是“盲目的”,陶瓷玻璃在最终选择的材料中会熔化,损坏完全回收的玻璃熔合会损害最终产品的质量,下面将介绍所开展的工作以及结果是,为了设计一种完全基于经典数字成像和分光光度法的集成方法,该方法旨在开发合适的分选策略,从而能够在工业回收规模上实现碎玻璃在颜色和材料类型方面的区别,即“真正的玻璃来自“陶瓷玻璃”的碎片。

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