The increasing demand for recycled wood to produce particleboard and MDF panels has resulted in the need to improve the cleaning process of post-consumer material, eliminating in a more effective and efficient way plastic impurities. We have developed a new method based on the NIR diffuse reflectance spectral analysis for the identification of different classes of materials that can be used in the selection process. We have investigated the diffuse reflected light in the range 1100 - 2500 nm of a wide sample of materials including plastics, ceramics, tiles, woods and laminates as representative of garbage dump materials. We have considered the typical features of the different classes of materials and looked for those spectral regions that present some difference among the classes. We have studied the correlation among the various features characterizing the spectra of each class and identifying the spectral bands potentially most effective in the discrimination process. Accordingly, six indices able to distinguish different materials have been defined. The results show that the near infrared spectral analysis can be used as an efficient analytical technique to identify different objects facilitating rapid separation process.

Near infrared technology for material identification and selection

CESETTI, MARY;NICOLOSI, PIERGIORGIO
2015

Abstract

The increasing demand for recycled wood to produce particleboard and MDF panels has resulted in the need to improve the cleaning process of post-consumer material, eliminating in a more effective and efficient way plastic impurities. We have developed a new method based on the NIR diffuse reflectance spectral analysis for the identification of different classes of materials that can be used in the selection process. We have investigated the diffuse reflected light in the range 1100 - 2500 nm of a wide sample of materials including plastics, ceramics, tiles, woods and laminates as representative of garbage dump materials. We have considered the typical features of the different classes of materials and looked for those spectral regions that present some difference among the classes. We have studied the correlation among the various features characterizing the spectra of each class and identifying the spectral bands potentially most effective in the discrimination process. Accordingly, six indices able to distinguish different materials have been defined. The results show that the near infrared spectral analysis can be used as an efficient analytical technique to identify different objects facilitating rapid separation process.
2015
IET Conference Publications
978-1-78561-068-4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3240490
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