Abstract
Biomass pellets are required as a source of energy because of their abundant and high energy. The rapid measurement of pellets is used to control the biomass quality during the production process. The objective of this work was to use near infrared (NIR) hyperspectral images for predicting the properties, i.e., fuel ratio (FR), volatile matter (VM), fixed carbon (FC), and ash content (A), of commercial biomass pellets. Models were developed using either full spectra or different spatial wavelengths, i.e., interval successive projections algorithm (iSPA) and interval genetic algorithm (iGA), wavelengths and different spectral preprocessing techniques. Their performances were then compared. The optimal model for predicting FR could be created with second derivative (D2) spectra with iSPA-100 wavelengths, while VM, FC, and A could be predicted using standard normal variate (SNV) spectra with iSPA-100 wavelengths. The models for predicting FR, VM, FC, and A provided R2 values of 0.75, 0.81, 0.82, and 0.87, respectively. Finally, the prediction of the biomass pellets’ properties under color distribution mapping was able to track pellet quality to control and monitor quality during the operation of the thermal conversion process and can be intuitively used for applications with screening.
Highlights
The world requirement for renewable energy has increased [1]
The high negative peaks observed in the D2 relative reflectance values were found to be 940 nm, and the spectra changed with the type of pellet, which is the structure of the C-H third overtone and is associated with C-H and CH2 [38]
The results showed that the optimal model for predicting fuel ratio (FR) could be developed using D2 spectra and the selected 100 wavelengths
Summary
The world requirement for renewable energy has increased [1]. In 2020, the use of renewable energy increased to 3.9% from the previous year [2]. Biomass is considered a renewable energy source because it is recycled and reused [3]. Biomass is obtained from dedicated energy crops, agricultural crop residues, forestry residues, wood processing residues, municipal waste, and wet waste [5]. This means that biomass materials differ in their physical properties, energy content, and chemical content. It is combusted to generate electricity as a source of thermal energy for an industrial purpose [6]
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