The size distribution of aggregates has direct and important effects on fundamental properties of construction materials such as workability, strength and durability. The size distribution of aggregates from construction and demolition waste (C&D) is one of the parameters which determine the degree of recyclability and therefore the quality of such materials. Unfortunately, standard methods like sieving or laser diffraction can be either very time consuming (sieving) or possible only in laboratory conditions (laser diffraction). As an alternative we propose and evaluate the use of image analysis to estimate the size distribution of aggregates from C&D in a fast yet accurate manner. The effectiveness of the procedure was tested on aggregates generated by an existing C&D mechanical treatment plant. Experimental comparison with manual sieving showed agreement in the range 81% -- 85%. The proposed technique demonstrated potential for being used on on-line systems within mechanical treatment plants of C&D.

Quality assessment for recycling aggregates from construction and demolition waste: An image-based approach for particle size estimation

DI MARIA, Francesco;BIANCONI, Francesco
;
MICALE, CATERINA;BAGLIONI, STEFANO;
2016

Abstract

The size distribution of aggregates has direct and important effects on fundamental properties of construction materials such as workability, strength and durability. The size distribution of aggregates from construction and demolition waste (C&D) is one of the parameters which determine the degree of recyclability and therefore the quality of such materials. Unfortunately, standard methods like sieving or laser diffraction can be either very time consuming (sieving) or possible only in laboratory conditions (laser diffraction). As an alternative we propose and evaluate the use of image analysis to estimate the size distribution of aggregates from C&D in a fast yet accurate manner. The effectiveness of the procedure was tested on aggregates generated by an existing C&D mechanical treatment plant. Experimental comparison with manual sieving showed agreement in the range 81% -- 85%. The proposed technique demonstrated potential for being used on on-line systems within mechanical treatment plants of C&D.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1366895
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