Hyperspectral Imaging for Process and Quality Control in Recycling Plants of Polyolefin Flakes

Serranti, Silvia; Gargiulo, Aldo; Bonifazi, Giuseppe

doi:10.1255/jnirs.1016

Cited by 55 publications

(28 citation statements)

References 24 publications

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“…It is significant to eliminate the unnecessary wavelengths among the redundant data and select the most representative wavelengths for building simplified models. Principal component analysis (PCA) is widely used for dimensionality reduction, loss data compression and feature extraction . The first few principal components resulting from PCA usually made a large contribution to all the original data.…”

Section: Methodsmentioning

confidence: 99%

“…The loadings of PCA were the weighting coefficients of each wavelength, the wavelengths with higher absolute loading value having a greater contribution. Thus we selected the peaks and valleys of the loading plot as the optimal wavelengths . Extraction of spectral data from the ROIs and PCA analysis were performed using the software ENVI 4.7 (ITT Visual Information Solutions, Boulder, CO, USA).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Discrimination of nitrogen fertilizer levels of tea plant (Camellia sinensis) based on hyperspectral imaging

Wang

Hou

et al. 2018

J Sci Food Agric

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Discrimination of nitrogen fertilizer levels of tea plant (Camellia sinensis) based on hyperspectral imaging

Wang

Hou

et al. 2018

J Sci Food Agric

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show abstract

“…Therefore, a reliable quality control technique is needed in the recycling industry in order to monitor each step of the process [6,7]. In order to check the correct separation of plastics after a recycling process, a quality control system is thus mandatory.…”

Section: Introductionmentioning

confidence: 99%

Short wave infrared hyperspectral imaging for recovered post-consumer single and mixed polymers characterization

2015

Self Cite

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Postconsumer plastics from packing and packaging represent about the 60% of the total plastic wastes (i.e. 23 million of tons) produced in Europe. The EU Directive (2014/12/EC) fixes as target that the 60%, by weight, of packaging waste has to be recovered, or thermally valorized. When recovered, the same directive established that packaging waste has to be recycled in a percentage ranging between 55% (minimum) and 60% (maximum). The non-respect of these rules can produce that large quantities of end-of-life plastic products, specifically those utilized for packaging, are disposed-off, with a strong environmental impact. The application of recycling strategies, finalized to polymer recovery, can represent an opportunity to reduce: i) not renewable raw materials (i.e. oil) utilization, ii) carbon dioxide emissions and iii) amount of plastic waste disposed-off. Aim of this work was to perform a full characterization of different end-of-life polymers based products, constituted not only by single polymers but also of mixtures, in order to realize their identification for quality control and/or certification assessment. The study was specifically addressed to characterize the different recovered products as resulting from a recycling plant where classical processing flow-sheets, based on milling, classification and separation, are applied. To reach this goal, an innovative sensing technique, based on the utilization of a HyperSpectral Imaging (HSI) device working in the SWIR region (1000-2500 nm), was investigated. Following this strategy, single polymers and/or mixed polymers recovered were correctly recognized. The main advantage of the proposed approach is linked to the possibility to perform "on-line" analyses, that is directly on the different material flow streams, as resulting from processing, without any physical sampling and classical laboratory "off-line" determination

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“…HyperSpectral Imaging (HSI) based approaches are thus investigated to develop characterization, inspection and quality control actions in the waste recycling sector, with particular reference to PO separation and recovery from complex wastes (ASR, B&CW, HW and WEEE) [12][13][14]. Particular attention was addressed to the problem arising when such an approach has to be applied to realize analytical architectures able to perform a real time analysis finalized to solve two specific problems, linked to PO separation and recovery, that is: i) feed stream quality control and final recovered products (PE and PP) quality certification [15].…”

Section: Introductionmentioning

confidence: 99%

A new hyperspectral imaging based device for quality control in plastic recycling

Bonifazi

D'Agostini²,

Dall'Ava³

et al. 2013

Optical Sensors 2013

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The quality control of contamination level in the recycled plastics stream has been identified as an important key factor for increasing the value of the recycled material by both plastic recycling and compounder industries. Existing quality control methods for the detection of both plastics and non-plastics contaminants in the plastic waste streams at different stages of the industrial process (e.g. feed, intermediate and final products) are currently based on the manual collection from the stream of a sample and on the subsequent off-line laboratory analyses. The results of such analyses are usually available after some hours, or sometimes even some days, after the material has been processed. The laboratory analyses are time-consuming and expensive (both in terms of equipment cost and their maintenance and of labour cost).Therefore, a fast on-line assessment to monitor the plastic waste feed streams and to characterize the composition of the different plastic products, is fundamental to increase the value of secondary plastics. The paper is finalized to describe and evaluate the development of an HSI-based device and of the related software architectures and processing algorithms for quality assessment of plastics in recycling plants, with particular reference to polyolefins (PO). NIR-HSI sensing devices coupled with multivariate data analysis methods was demonstrated as an objective, rapid and non-destructive technique that can be used for on-line quality and process control in the recycling process of POs. In particular, the adoption of the previous mentioned HD&SW integrated architectures can provide a solution to one of the major problems of the recycling industry, which is the lack of an accurate quality certification of materials obtained by recycling processes. These results could therefore assist in developing strategies to certify the composition of recycled PO products

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Hyperspectral Imaging for Process and Quality Control in Recycling Plants of Polyolefin Flakes

Cited by 55 publications

References 24 publications

Discrimination of nitrogen fertilizer levels of tea plant (Camellia sinensis) based on hyperspectral imaging

Discrimination of nitrogen fertilizer levels of tea plant (Camellia sinensis) based on hyperspectral imaging

Short wave infrared hyperspectral imaging for recovered post-consumer single and mixed polymers characterization

A new hyperspectral imaging based device for quality control in plastic recycling

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