Moroni Monica, Mei Alessandro, Leonardi Alessandra, Lupo Emanuela, Marca Floriana La
DICEA-Sapienza University of Rome, via Eudossiana 18, 00184 Rome, Italy.
CNR-Institute of Atmospheric Pollution Research, Area della Ricerca di Roma1, Via Salaria Km 29,300 Monterotondo, I-00015 Rome, Italy.
Sensors (Basel). 2015 Jan 20;15(1):2205-27. doi: 10.3390/s150102205.
Traditional plants for plastic separation in homogeneous products employ material physical properties (for instance density). Due to the small intervals of variability of different polymer properties, the output quality may not be adequate. Sensing technologies based on hyperspectral imaging have been introduced in order to classify materials and to increase the quality of recycled products, which have to comply with specific standards determined by industrial applications. This paper presents the results of the characterization of two different plastic polymers--polyethylene terephthalate (PET) and polyvinyl chloride (PVC)--in different phases of their life cycle (primary raw materials, urban and urban-assimilated waste and secondary raw materials) to show the contribution of hyperspectral sensors in the field of material recycling. This is accomplished via near-infrared (900-1700 nm) reflectance spectra extracted from hyperspectral images acquired with a two-linear-spectrometer apparatus. Results have shown that a rapid and reliable identification of PET and PVC can be achieved by using a simple two near-infrared wavelength operator coupled to an analysis of reflectance spectra. This resulted in 100% classification accuracy. A sensor based on this identification method appears suitable and inexpensive to build and provides the necessary speed and performance required by the recycling industry.
传统用于从均质产品中分离塑料的方法利用材料的物理特性（例如密度）。由于不同聚合物特性的变化区间较小，产出质量可能无法达到要求。为了对材料进行分类并提高回收产品的质量（这些产品必须符合工业应用确定的特定标准），基于高光谱成像的传感技术已被引入。本文展示了对两种不同塑料聚合物——聚对苯二甲酸乙二酯（PET）和聚氯乙烯（PVC）——在其生命周期的不同阶段（初级原材料、城市及城市同化废物和二级原材料）进行表征的结果，以说明高光谱传感器在材料回收领域的作用。这是通过从使用双线性光谱仪设备获取的高光谱图像中提取的近红外（900 - 1700纳米）反射光谱来实现的。结果表明，通过使用一个简单的双近红外波长算子并结合反射光谱分析，可以快速且可靠地识别PET和PVC。这实现了100%的分类准确率。基于这种识别方法的传感器似乎适合构建且成本低廉，并提供了回收行业所需的必要速度和性能。
