APPLICATION OF A SPECTROSCOPIC INFRARED FOCAL-PLANE ARRAY SENSOR FOR ONLINE IDENTIFICATION OF PLASTIC WASTE

A spectroscopic near-infrared imaging system, using a focal plane arra y (FPA) detector, is presented for remote and on-line measurements on a macroscopic scale. On-line spectroscopic imaging requires high-speed sensors and short image processing steps. Therefore, the use of a foc al plane array detector in combination with fast chemometric software is investigated. As these new spectroscopic imaging systems generate s o much data, multivariate statistical techniques are needed to extract the important information from the multidimensional spectroscopic ima ges. These techniques include principal component analysis (PCA) and l inear discriminant analysis (LDA) for supervised classification of spe ctroscopic image data. Supervised classification is a tedious task in spectroscopic imaging, but a procedure is presented to facilitate this task and to provide more insight into and control over the compositio n of the datasets. The identification system is constructed, implement ed, and tested for a real-world application of plastic identification in municipal solid waste.