Paper
17 October 2006 Hyperspectral imaging based techniques in fluff characterization
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Abstract
Light fractions produced after vehicles dismantling are conventionally defined as "fluff" or Automotive Shredder Residue (ASR). They represent about the 25% of the weight of a car and are usually constituted by materials characterized by intrinsic low specific gravity (i.e. plastics, rubber, synthetic foams, etc.). Fluff is usually polluted by metal contaminants (i.e. copper, aluminum, brass, iron, etc.), that strongly affect, especially in the final fractions, the possibility to utilize such material as fuel in co-combustion process, reducing the waste disposal and increasing at the same time energy production. In this paper, innovative selection-control architectures, based on hyperspectral imaging, in the visible- near infrared (VIS-NIR) field, have been investigated. In order to define suitable inspection strategies for the recognition and separation between useful (fluff) and polluting (metals) materials, samples of light and heavy plastics and metals have been collected in a recycling plant. Reflectance spectra have been acquired in the VIS-NIR field (400-1000 nm). Results showed as the different materials are characterized by different spectral signatures and that recognition of plastics and metals can be obtained adopting a wavelength ratio in the NIR (700-1000 nm) field.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Giuseppe Bonifazi and Silvia Serranti "Hyperspectral imaging based techniques in fluff characterization", Proc. SPIE 6377, Advanced Environmental, Chemical, and Biological Sensing Technologies IV, 63770O (17 October 2006); https://doi.org/10.1117/12.684661
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Cited by 14 scholarly publications and 1 patent.
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KEYWORDS
Metals

Hyperspectral imaging

Reflectivity

Particles

Glasses

Imaging systems

Near infrared

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