3D Sensing System for Laser-Induced Breakdown Spectroscopy-Based Metal Scrap Identification

Abstract

Laser-induced breakdown spectroscopy (LIBS) is an analysis technique that determines the elemental composition of a target material. Metal scraps have a range of shapes and are contaminated with other substances such as paint or dirt. This makes it difficult to recognize each piece of metal scrap accurately and to obtain clear LIBS emission spectra of the target metals. In this study, two image processing algorithms are proposed to measure the three-dimensional shapes of metal scraps and to calculate the optimized (i.e., relatively clean and flat) surface areas of metal scraps. It was confirmed that 25% higher maximum classification accuracy was achieved when LIBS spectra were acquired from optimized rather than non-optimized (i.e., contaminated) surfaces.