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Utilization of Near Infrared (NIR) Spectrometry for Detection of Glass in the Waste-based Fuel
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-5341-3656
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-8466-356X
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0001-8191-4901
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0001-5480-0167
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2015 (English)In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 75, 734-741 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents the results of experimental measurements and multivariate statistical modeling concerning detection of soda-lime glass using near infrared (NIR) spectrometry technique. The purpose is to test if the glass is quantitatively detectable in a waste-based material and to assess what method of spectral data pretreatment is the most suitable in order to develop prediction models. The experiments were performed on six test samples containing a specific amount of glass distributed in background material. Pretreatment methods such as normalization and first and second derivatives were applied on the acquired absorbance spectral data. Principal component analysis (PCA) was employed in order to describe the relationship between pretreated data and the amount of glass in the test samples. Subsequently, principal component regression (PCR) was utilized for the development of prediction models. The results from the models show strong correlation between the pretreated data and the glass content. The most promising results were obtained from the model based on 1st derivative pretreatment when only absorbance spectral data from selected wavelengths are included. 

Place, publisher, year, edition, pages
2015. Vol. 75, 734-741 p.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-29321DOI: 10.1016/j.egypro.2015.07.502ISI: 000361030001029Scopus ID: 2-s2.0-84947065808OAI: oai:DiVA.org:mdh-29321DiVA: diva2:861084
Conference
7th International Conference on Applied Energy (ICAE), MAR 28-31, 2015, Abu Dhabi, U ARAB EMIRATES
Available from: 2015-10-15 Created: 2015-10-15 Last updated: 2017-03-21Bibliographically approved
In thesis
1. Near-Infrared Spectroscopy and Extractive Probe Sampling for Biomass and Combustion Characterization
Open this publication in new window or tab >>Near-Infrared Spectroscopy and Extractive Probe Sampling for Biomass and Combustion Characterization
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Biomass is characterized by highly variable properties. It can be converted to more valuable energy forms and products through a variety of conversion processes. This thesis focuses on addressing several important issues related to combustion and pulping.

Experimental investigations were carried out on a biomass-fired industrial fluidized-bed boiler. The observed combustion asymmetry was explained by an imbalance in the fuel feed. Increased levels of carbon monoxide were detected close to boiler walls which contribute significantly to the risk of wall corrosion.

Moreover, extensive literature analysis showed that near-infrared spectroscopy (NIRS) has a great potential to provide property information for heterogeneous feedstocks or products, and to directly monitor processes producing/processing biofuels in real-time. The developed NIRS-based models were able to predict characteristics such as heating value, ash content and glass content. A study focusing on the influence of different spectra acquisition parameters on lignin quantification was carried out. Spectral data acquired on moving woodchips were found to increase the representativeness of the spectral measurements leading to improvements in model performance.

The present thesis demonstrates the potential of developing NIRS-based soft-sensors for characterization of biomass properties. The on-line installation of such sensors in an industrial setting can enable feed-forward process control, diagnostics and optimization.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2017
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 224
National Category
Energy Systems Chemical Process Engineering
Research subject
Energy- and Environmental Engineering
Identifiers
urn:nbn:se:mdh:diva-35041 (URN)978-91-7485-317-9 (ISBN)
Public defence
2017-04-26, Pi, Mälardalens högskola, Västerås, 09:15 (English)
Opponent
Supervisors
Available from: 2017-03-20 Created: 2017-03-19 Last updated: 2017-04-18Bibliographically approved

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Skvaril, JanKyprianidis, KonstantinosAvelin, AndersOdlare, MonicaDahlquist, Erik
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