Automatic sorting of lightweight metal scrap by sensing apparent density and three-dimensional shape

Abstract

A new method for the automatic sorting of lightweight metal scrap has been developed to aid the recycling of scrap metal. The sorting system enables separation of relatively large metal pieces according to the differences in their apparent density and three-dimensional (3D) shape. Shape parameters such as width, height, volume, and projected area of irregular-shaped metal pieces moving along a conveyer are measured by means of a 3D imaging camera system consisting of a linear laser and camera with associated optics. The measured values of the weight and shape parameters are transferred to our own data-processing software that uses multivariate analysis. Mixed fragments of cast aluminum, wrought aluminum, and magnesium from an end-of-life vehicles shredder facility were sorted based on the output of the data-processing software. The results show that the developed automatic sorting system is a highly viable method that could replace conventional dense medium separation and manual sorting.