The development of an efficient system for demolition waste (DW) recycling, in order to recover concrete aggregates for high-value "green concrete" production, represents one of the main targets in the secondary raw materials sector. Moreover, the replacement of primary raw materials through end-of-life (EOL) concrete can contribute to secure ample supplies of concrete aggregates to the construction industry, limiting the new nonrenewable resources exploitation. Other related benefits can be thus reached: i) a strong reduction of the costs linked to transport and energy production, ii) the reduction of the environmental impacts linked to new exploitation activities, iii) the possibility to utilize materials that otherwise should be lost (i.e. land filled) and, finally iv) the land preservation. In this perspective, the realization, implementation and set-up of suitable on-line sensor technology able to detect different materials in the recycled DW streams can play an important role in order to control the quality of recycled products, maximizing DW conversion into secondary raw materials. To reach this goal, a hyperspectral imaging (HSI) based approach can be adopted in order to perform non-destructive, rapid and low cost analyses to check the quality of the output streams as resulting from a DW recycling plant. In this work an approach based on HSI sensors is investigated in order to implement an effective and reliable strategy for recognition of concrete aggregates and other materials considered as contaminants (i.e. plastics, gypsum, wood, brick, foam, etc.). The SWIR spectral range (1000-2500 nm) was investigated. Samples were acquired in the NIR wavelengths interval adopting a platform designed by DV srl (Padova, Italy). The detection architecture is constituted by a conveyor belt (width = 26 cm and length = 160 cm) with adjustable speed, a NIR Spectral Camera (Specim, Finland) equipped with an ImSpector N17E imaging spectrograph coupled with a Te-cooled InGaAs photodiode array sensor (320x240 pixels).The NIR acquisition system is controlled by a PC unit and a specifically developed software (Spectral Scanner™) is adopted for the spectra acquisition, collection and management. The utilized device for SWIR acquisitions is the SisuCHEMA XL™ Chemical Imaging workstation (Specim, Finland), equipped with Chemadaq™ software for spectra acquisition and collection. SisuCHEMA is provided with a SPECIM’s Spectral Camera consisting of an ImSpector N25E imaging spectrograph for the SWIR wavelength region and a cooled, temperature stabilized MCT detector. Acquired hyperspectral images were analyzed adopting the PLS_Toolbox (Eigenvector Research, Inc.) running into the Matlab® environment (The Mathworks, Inc.). Different chemometric methods were applied: Principal Component Analysis (PCA) for exploratory data approach and Partial Least Square-Discriminant Analysis (PLS-DA) to build classification models. Results showed that it is possible to recognize DW materials and to distinguish the recycled aggregates from contaminants (e.g. bricks, gypsum, plastics, wood and foam). Specifically 6 classes were defined (i.e. aggregates and 5 classes of contaminants). The developed procedure is not expensive, fast and reliable. For all these reasons it can be profitably utilized to set up on-line strategies finalized to improve recycling processes efficiency, reducing costs and improving the “final quality” of the recovered product.

Quality control based on SWIR and NIR hyperspectral imaging approaches: recovered aggregates from demolition waste recycling / Serranti, Silvia; Palmieri, Roberta; Bonifazi, Giuseppe. - STAMPA. - (2015), pp. 109-109. (Intervento presentato al convegno 17th International Conference on Near Infrared Spectroscopy tenutosi a Foz do Iguassu, Brazil nel 18-23 ottobre 2015).

Quality control based on SWIR and NIR hyperspectral imaging approaches: recovered aggregates from demolition waste recycling

SERRANTI, Silvia;PALMIERI, ROBERTA;BONIFAZI, Giuseppe
2015

Abstract

The development of an efficient system for demolition waste (DW) recycling, in order to recover concrete aggregates for high-value "green concrete" production, represents one of the main targets in the secondary raw materials sector. Moreover, the replacement of primary raw materials through end-of-life (EOL) concrete can contribute to secure ample supplies of concrete aggregates to the construction industry, limiting the new nonrenewable resources exploitation. Other related benefits can be thus reached: i) a strong reduction of the costs linked to transport and energy production, ii) the reduction of the environmental impacts linked to new exploitation activities, iii) the possibility to utilize materials that otherwise should be lost (i.e. land filled) and, finally iv) the land preservation. In this perspective, the realization, implementation and set-up of suitable on-line sensor technology able to detect different materials in the recycled DW streams can play an important role in order to control the quality of recycled products, maximizing DW conversion into secondary raw materials. To reach this goal, a hyperspectral imaging (HSI) based approach can be adopted in order to perform non-destructive, rapid and low cost analyses to check the quality of the output streams as resulting from a DW recycling plant. In this work an approach based on HSI sensors is investigated in order to implement an effective and reliable strategy for recognition of concrete aggregates and other materials considered as contaminants (i.e. plastics, gypsum, wood, brick, foam, etc.). The SWIR spectral range (1000-2500 nm) was investigated. Samples were acquired in the NIR wavelengths interval adopting a platform designed by DV srl (Padova, Italy). The detection architecture is constituted by a conveyor belt (width = 26 cm and length = 160 cm) with adjustable speed, a NIR Spectral Camera (Specim, Finland) equipped with an ImSpector N17E imaging spectrograph coupled with a Te-cooled InGaAs photodiode array sensor (320x240 pixels).The NIR acquisition system is controlled by a PC unit and a specifically developed software (Spectral Scanner™) is adopted for the spectra acquisition, collection and management. The utilized device for SWIR acquisitions is the SisuCHEMA XL™ Chemical Imaging workstation (Specim, Finland), equipped with Chemadaq™ software for spectra acquisition and collection. SisuCHEMA is provided with a SPECIM’s Spectral Camera consisting of an ImSpector N25E imaging spectrograph for the SWIR wavelength region and a cooled, temperature stabilized MCT detector. Acquired hyperspectral images were analyzed adopting the PLS_Toolbox (Eigenvector Research, Inc.) running into the Matlab® environment (The Mathworks, Inc.). Different chemometric methods were applied: Principal Component Analysis (PCA) for exploratory data approach and Partial Least Square-Discriminant Analysis (PLS-DA) to build classification models. Results showed that it is possible to recognize DW materials and to distinguish the recycled aggregates from contaminants (e.g. bricks, gypsum, plastics, wood and foam). Specifically 6 classes were defined (i.e. aggregates and 5 classes of contaminants). The developed procedure is not expensive, fast and reliable. For all these reasons it can be profitably utilized to set up on-line strategies finalized to improve recycling processes efficiency, reducing costs and improving the “final quality” of the recovered product.
2015
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/850579
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