Classification of polyolefins from building and construction waste using NIR hyperspectral imaging system

Serranti, Silvia; Gargiulo, Aldo; Bonifazi, Giuseppe

doi:10.1016/j.resconrec.2012.01.007

Cited by 99 publications

(38 citation statements)

References 15 publications

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“…Therefore hyperspectral imaging is a sort of multivariate imaging where the variables are the wavelengths [10]. HSI technique has recently emerged and fast-grown in many industrial sectors as the recycling field [11][12][13][14][15][16] offering a huge amount of physical-chemical information from a sample, according to the different wavelengths of the source and the spectral sensitivity of the adopted device. HSI was thus applied to perform a full identification of different virgin polymers and three postconsumer plastics commonly utilized in mobile phones, in order to explore the possibility to use this technique to recognize different kind of plastic materials in the sorting/recycling process.…”

Section: Hyperspectral Imaging (Hsi)mentioning

confidence: 99%

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

2015

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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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Section: Hyperspectral Imaging (Hsi)mentioning

confidence: 99%

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

2015

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“…Images are acquired scanning the investigated sample, line by line. Sample image sequence is then utilized to extract spectral information, to select effective wavelengths and, finally, for classification purposes [6]. For these characteristics the NIR-HSI is an excellent approach to perform both quality control and classification actions on different types of materials; furthermore, for the intrinsic characteristics of the spectral data (i.e.…”

Section: A Acquisition Platformmentioning

confidence: 99%

FT-IR spectroscopy and Hyperspectral Imaging applied to post-consumer plastic packaging characterization and sorting

Bonifazi

Maio

Potenza

et al. 2014

IEEE SENSORS 2014 Proceedings

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Post-consumer plastic packaging waste represents one of the main source of recovered polymers. A big problem now arising is thus the need to certify, in a fast (i.e. "on-line") and reliable way, recovered plastic composition, as well as to assess polymer mixtures bulk characteristics, in order to partially, or totally, re-use them. The study is addressed to utilize a new technique, HyperSpectral Imaging (HSI) based, in order to identify polymers as resulting from a recycling process. This approach was specifically adopted to identify the presence of PolyVinyl Chloride (PVC) in the heavy fraction resulting from an industrial sink-float process. PVC detection is important because heavy fraction recovery is finalized to its further re-utilization as Solid Recovered Fuels (SRF). The presence of this polymer, in fact, for its chlorine content (i.e. dioxin production during combustion) negatively affects the thermal recovery of these products. The study demonstrated as the proposed HSI based approach, in the NIR range (1000-1700 nm), can successfully utilized to set up "real time" analytical/control strategies to perform a continuous monitoring of the composition of the different flow plastic waste streams obtained by from industrial processing, with particular reference to PVC identification.

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“…However, the increase of the number of wavebands will inevitably lead to increase the information redundancy and the complexity of data processing [9][10]. The preprocessing for raw hyper spectral data and the reduction and optimization for spectral feature space are the fundament of analysis of hyper spectral data, and it is also the emphasis and guarantee for accurately analyzing principal component of samples and setting the accurate prediction model.…”

Section: Extraction and Analysis Of Characteristic Spectrummentioning

confidence: 99%

Research on marine and freshwater fish identification model based on hyper-spectral imaging technology

Guo

Xiang

et al. 2013

SPIE Proceedings

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With the gradually mature of hyper spectral image technology, the application of the meat nondestructive detection and recognition has become one of the current research focuses. This paper for the study of marine and freshwater fish by the pre-processing and feature extraction of the collected spectral curve data, combined with BP network structure and LVQ network structure, a predictive model of hyper spectral image data of marine and freshwater fish has been initially established and finally realized the qualitative analysis and identification of marine and freshwater fish quality. The results of this study show that hyper spectral imaging technology combined with the BP and LVQ Artificial Neural Network Model can be used for the identification of marine and freshwater fish detection. Hyper-spectral data acquisition can be carried out without any pretreatment of the samples, thus hyper-spectral imaging technique is the lossless, high-accuracy and rapid detection method for quality of fish. In this study, only 30 samples are used for the exploratory qualitative identification of research, although the ideal study results are achieved, we will further increase the sample capacity to take the analysis of quantitative identification and verify the feasibility of this theory.

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Classification of polyolefins from building and construction waste using NIR hyperspectral imaging system

Cited by 99 publications

References 15 publications

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

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

FT-IR spectroscopy and Hyperspectral Imaging applied to post-consumer plastic packaging characterization and sorting

Research on marine and freshwater fish identification model based on hyper-spectral imaging technology

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