LAPSE:2020.1003
Published Article
LAPSE:2020.1003
Image-Based Model for Assessment of Wood Chip Quality and Mixture Ratios
Thomas Plankenbühler, Sebastian Kolb, Fabian Grümer, Dominik Müller, Jürgen Karl
September 23, 2020
This article focuses on fuel quality in biomass power plants and describes an online prediction method based on image analysis and regression modeling. The main goal is to determine the mixture fraction from blends of two wood chip species with different qualities and properties. Starting from images of both fuels and different mixtures, we used two different approaches to deduce feature vectors. The first one relied on integral brightness values while the latter used spatial texture information. The features were used as input data for linear and non-linear regression models in nine training classes. This permitted the subsequent prediction of mixture ratios from prior unknown similar images. We extensively discuss the influence of model and image selection, parametrization, the application of boosting algorithms and training strategies. We obtained models featuring predictive accuracies of R2 > 0.9 for the brightness-based model and R2 > 0.8 for the texture based one during the validation tests. Even when reducing the data used for model training down to two or three mixture classes—which could be necessary or beneficial for the industrial application of our approach—sampling rates of n < 5 were sufficient in order to obtain significant predictions.
Keywords
Biomass, biomass power plant, fuel quality, image analysis, Machine Learning, regression modeling
Suggested Citation
Plankenbühler T, Kolb S, Grümer F, Müller D, Karl J. Image-Based Model for Assessment of Wood Chip Quality and Mixture Ratios. (2020). LAPSE:2020.1003
Author Affiliations
Plankenbühler T: Chair of Energy Process Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Fürther Straße 244f, D-90429 Nürnberg, Germany [ORCID]
Kolb S: Chair of Energy Process Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Fürther Straße 244f, D-90429 Nürnberg, Germany [ORCID]
Grümer F: Independent Researcher, D-90439 Nürnberg, Germany
Müller D: Chair of Energy Process Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Fürther Straße 244f, D-90429 Nürnberg, Germany
Karl J: Chair of Energy Process Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Fürther Straße 244f, D-90429 Nürnberg, Germany
Journal Name
Processes
Volume
8
Issue
6
Article Number
E728
Year
2020
Publication Date
2020-06-23
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr8060728, Publication Type: Journal Article
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LAPSE:2020.1003
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doi:10.3390/pr8060728
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Sep 23, 2020
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CC BY 4.0
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Sep 23, 2020
 
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Sep 23, 2020
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Original Submitter
Calvin Tsay
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