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废料分类:一种基于发光二极管的短波红外离散光源方法

Waste Material Classification: A Short-Wave Infrared Discrete-Light-Source Approach Based on Light-Emitting Diodes.

作者信息

Manakkakudy Anju, De Iacovo Andrea, Maiorana Emanuele, Mitri Federica, Colace Lorenzo

机构信息

Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, 00146 Rome, Italy.

出版信息

Sensors (Basel). 2024 Jan 26;24(3):809. doi: 10.3390/s24030809.

Abstract

Waste material classification is a challenging yet important task in waste management. The realization of low-cost waste classification systems and methods is critical to meet the ever-increasing demand for efficient waste management and recycling. In this paper, we demonstrate a simple, compact and low-cost classification system based on optical reflectance measurements in the short-wave infrared for the segregation of waste materials such as plastics, paper, glass, and aluminium. The system comprises a small set of LEDs and one single broadband photodetector. All devices are controlled through low-cost and low-power electronics, and data are gathered and managed via a computer interface. The proposed system reaches accuracy levels as high as 94.3% when considering seven distinct materials and 97.0% when excluding the most difficult to classify, thus representing a valuable proof-of-concept for future system developments.

摘要

废料分类是废料管理中一项具有挑战性但又很重要的任务。实现低成本的废料分类系统和方法对于满足对高效废料管理和回收利用不断增长的需求至关重要。在本文中,我们展示了一种基于短波红外光反射测量的简单、紧凑且低成本的分类系统,用于分离塑料、纸张、玻璃和铝等废料。该系统由一小组发光二极管(LED)和一个单一的宽带光电探测器组成。所有设备均通过低成本、低功耗的电子器件进行控制,数据通过计算机接口进行收集和管理。当考虑七种不同材料时,所提出的系统准确率高达94.3%,排除最难分类的材料时准确率为97.0%,因此为未来系统的发展提供了有价值的概念验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7883/10857375/1d89abc6aaa0/sensors-24-00809-g001.jpg

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