The most meaningful spectral components in laser-induced fluorescence (LIF) spectra for several different commercial plastics have been individuated and used to automatically discriminate among different plastic materials and between plastics and complex organic materials, such as woods. Starting from LIF measurements on known samples, a number of significant wavelengths have been identified by principal component analysis (PCA). These have been used to produce intensity ratios functional to the discrimination. Threshold values for such ratios have been individuated in order to obtain an automatic recognition of plastics. The work done has been preparatory to the design and development of a multispectral imaging LIF system for fast detection of plastic debris in a post-blast scene. © The Author(s) 2016.

Characterization and discrimination of plastic materials using laser-induced fluorescence

Colao, F.;Caneve, L.;Spizzichino, V.
2016

Abstract

The most meaningful spectral components in laser-induced fluorescence (LIF) spectra for several different commercial plastics have been individuated and used to automatically discriminate among different plastic materials and between plastics and complex organic materials, such as woods. Starting from LIF measurements on known samples, a number of significant wavelengths have been identified by principal component analysis (PCA). These have been used to produce intensity ratios functional to the discrimination. Threshold values for such ratios have been individuated in order to obtain an automatic recognition of plastics. The work done has been preparatory to the design and development of a multispectral imaging LIF system for fast detection of plastic debris in a post-blast scene. © The Author(s) 2016.
cluster analysis;polymers;principal component analysis (PCA);plastics;Laser-induced fluorescence (LIF)
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12079/1399
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