Metal Identification Based on Laser-induced Breakdown Spectroscopy and BP Neural Network

Abstract

For sorting scrap metal materials, the ultimate goal is to separate some scrap metal from other scrap metal materials completely. In this paper, Laser-Induced Breakdown Spectroscopy (LIBS) is used to take sample data from cooked aluminum, aluminum, magnesium, stainless steel, iron, copper, and zinc 7 metal samples seven scrap metal samplings with principal component analysis methods of data reduction. And BP neural network is used to the classification of aluminum and non-aluminum metals, Experiment results show that the classification accuracy up to 93.40% . These results provide a method for sorting scrap metal and reference data with BP neural network and LIBS technique, which make online scrap metal sorting get better result.