Asbestos technological properties and its relatively low cost was the main reason, in the past, for its wide utilization in many industrial sectors. Among the sectors, building and construction ones utilized a lot of asbestos containing materials (ACM). During the construction and demolition waste (C&DW) recycling process, ACM must be collected and separated from the other wastes. C&DW materials includes, but are not limited to, bricks, concrete, masonry materials, roofing materials, soil, rock, wood, wood products, wall or floor coverings, plaster, drywall, plumbing fixtures, electrical wiring, electrical components, etc. The aim of recycling industry, when C&DW reutilization aor dumping actions are applied, was to minimise hazardous materials (i.e. asbestos) contamination risk. Control methodologies are thus necessary to evaluate presence and quality of ACM. In many countries, legislation identifies asbestos as the asbestiform varieties of chrysotile (i.e. serpentine), crocidolite (i.e. riebeckite), amosite (i.e. cummingtonite/grunerite) and anthophyllite. The identification of contaminants inside demolition waste with rapid and non-destructively technique is crucial for a correct reuse and/or storage of C&DW. Hyperspectral imaging (HSI) based sensing devices allow to detect and characterize C&DW materials. HSI quality control approach is based on the utilization of a platform working in the Short-Wave Infrared Range (SWIR: 1000–2500 nm). Hyperspectral images were analysed applying different chemometric methods: Principal Component Analysis (PCA), for data exploration, and Partial Least Square Discriminant Analysis (PLS-DA) to build classification models. Results showed that it is possible, inside a C&DW flow stream, to recognize different materials (i.e. bricks, gypsum, plastics, wood, foam, aggregates, etc.) from hazardous ones (i.e. ACM). Adopting the proposed strategies, a complete recycling process control, including the inspection of incoming loads (i.e. C&DW fed to the recycling plant), ACM and other “polluting” material identification, can be realized. The recognition is automatic, nondestructive and it does not require the presence of ACM specialized personnel.
ASBESTOS RECOGNITION IN CONSTRUCTION AND DEMOLITION WASTE BY HYPERSPECTRAL IMAGING / Bonifazi, Giuseppe; Capobianco, Giuseppe; Serranti, Silvia. - (2018), pp. 1-9. ((Intervento presentato al convegno International conference on industrial and hazardous waste management - tenutosi a Chania – Crete – Greece.
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|Titolo:||ASBESTOS RECOGNITION IN CONSTRUCTION AND DEMOLITION WASTE BY HYPERSPECTRAL IMAGING|
|Data di pubblicazione:||2018|
|Citazione:||ASBESTOS RECOGNITION IN CONSTRUCTION AND DEMOLITION WASTE BY HYPERSPECTRAL IMAGING / Bonifazi, Giuseppe; Capobianco, Giuseppe; Serranti, Silvia. - (2018), pp. 1-9. ((Intervento presentato al convegno International conference on industrial and hazardous waste management - tenutosi a Chania – Crete – Greece.|
|Appartiene alla tipologia:||04d Abstract in atti di convegno|