Du Yue, Zhang Zhijie, Yin Wuliang, Zhu Shuang, Chen Ziqi, Xu Hanyang
School of Instrument and Electronics, North University of China, Taiyuan 030051, China.
School of Electrical and Electronic Engineering, University of Manchester, Manchester M60 1QD, UK.
Sensors (Basel). 2020 May 3;20(9):2608. doi: 10.3390/s20092608.
Metallic waste classification benefits the environment, resource reuse and industrial economy. This paper provides a fast, non-contact and convenient method based on eddy current to classify metals. The characteristic phase to characterize different conductivity is introduced and extracted from mutual inductance in the form of amplitude and phase. This characteristic phase could offer great separation for non-tilting metals. Although it is hard to classify tilting metals by only using the characteristic phase, we propose the technique of phase compensation utilizing photoelectric sensors to obtain the rectified phase corresponding to the non-tilting situation. Finally, we construct a classification algorithm involving phase compensation. By conducting a test, a 95 % classification rate is achieved.
金属废物分类有利于环境、资源再利用和产业经济。本文提出了一种基于涡流的快速、非接触且便捷的金属分类方法。引入并从互感中以幅度和相位的形式提取用于表征不同电导率的特征相位。该特征相位可为非倾斜金属提供良好的区分效果。虽然仅使用特征相位难以对倾斜金属进行分类，但我们提出了利用光电传感器进行相位补偿的技术，以获得对应于非倾斜情况的校正相位。最后，我们构建了一种包含相位补偿的分类算法。通过测试，实现了95%的分类率。
