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Proceedings Paper

Innovative hyperspectral imaging (HSI) based techniques applied to end-of-life concrete drill core characterization for optimal dismantling and materials recovery
Author(s): Giuseppe Bonifazi; Nicoletta Picone; Silvia Serranti
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Paper Abstract

The reduction of EOL concrete disposal in landfills, together with a lower exploitation of primary raw materials, generates a strong interest to develop, set-up and apply innovative technologies to maximize Construction and Demolition Waste (C&DW) conversion into useful secondary raw materials. Such a goal can be reached starting from a punctual in-situ efficient characterization of the objects to dismantle in order to develop demolition actions aimed to set up innovative mechanical-physical processes to recover the different materials and products to recycle. In this paper an innovative recycling-oriented characterization strategy based on HyperSpectral Imaging (HSI) is described in order to identify aggregates and mortar in drill core samples from end-of-life concrete. To reach this goal, concrete drill cores from a demolition site were systematically investigated by HSI in the short wave infrared field (1000-2500 nm). Results obtained by the adoption of the HSI approach showed as this technology can be successfully applied to analyze quality and characteristics of C&DW before dismantling and as final product to reutilise after demolition-milling-classification actions. The proposed technique and the related recognition logics, through the spectral signature detection of finite physical domains (i.e. concrete slice and/or particle) of different nature and composition, allows; i) to develop characterization procedures able to quantitatively assess end-of-life concrete compositional/textural characteristics and ii) to set up innovative sorting strategies to qualify the different materials constituting drill core samples.

Paper Details

Date Published: 27 February 2015
PDF: 13 pages
Proc. SPIE 9405, Image Processing: Machine Vision Applications VIII, 94050X (27 February 2015); doi: 10.1117/12.2081174
Show Author Affiliations
Giuseppe Bonifazi, Univ. degli Studi di Roma La Sapienza (Italy)
Nicoletta Picone, Univ. degli Studi di Roma La Sapienza (Italy)
Silvia Serranti, Univ. degli Studi di Roma La Sapienza (Italy)


Published in SPIE Proceedings Vol. 9405:
Image Processing: Machine Vision Applications VIII
Edmund Y. Lam; Kurt S. Niel, Editor(s)

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