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Volume and Mass Measurement of a Burning Wood Pellet by Image Processing

Author

Listed:
  • Sae Byul Kang

    (Energy Network Laboratory, Korea Institute of Energy Research, Daejeon 34129, Korea)

  • Bong Suk Sim

    (Research and Development Team, Doowon, Choongnam 336864, Korea)

  • Jong Jin Kim

    (Energy Network Laboratory, Korea Institute of Energy Research, Daejeon 34129, Korea)

Abstract

Wood pellets are a form of solid biomass energy and a renewable energy source. In 2015, the new and renewable energy (NRE) portion of wood pellets was 4.6% of the total primary energy in Korea. Wood pellets account for 6.2% of renewable energy consumption in Korea, the equivalent of 824,000 TOE (ton of oil equivalent, 10 million kcal). The burning phases of a wood pellet can be classified into three modes: (1) gasification; (2) flame burning and (3) charcoal burning. At each wood pellet burning mode, the volume and weight of the burning wood pellet can drastically change; these parameters are important to understand the wood pellet burning mechanism. We developed a new method for measuring the volume of a burning wood pellet that involves no contact. To measure the volume of a wood pellet, we take pictures of the wood pellet in each burning mode. The volume of a burning wood pellet can then be calculated by image processing. The difference between the calculation method using image processing and the direct measurement of a burning wood pellet in gasification mode is less than 8.8%. In gasification mode in this research, mass reduction of the wood pellet is 37% and volume reduction of the wood pellet is 7%. Whereas in charcoal burning mode, mass reduction of the wood pellet is 10% and volume reduction of the wood pellet is 41%. By measuring volume using image processing, continuous and non-interruptive volume measurements for various solid fuels are possible and can provide more detailed information for CFD (computational fluid dynamics) analysis.

Suggested Citation

  • Sae Byul Kang & Bong Suk Sim & Jong Jin Kim, 2017. "Volume and Mass Measurement of a Burning Wood Pellet by Image Processing," Energies, MDPI, vol. 10(5), pages 1-13, May.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:5:p:603-:d:97290
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    References listed on IDEAS

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    Cited by:

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    2. Pierdicca, Roberto & Balestra, Mattia & Micheletti, Giulia & Felicetti, Andrea & Toscano, Giuseppe, 2022. "Semi-automatic detection and segmentation of wooden pellet size exploiting a deep learning approach," Renewable Energy, Elsevier, vol. 197(C), pages 406-416.
    3. Stolarski, Mariusz J. & Stachowicz, Paweł & Dudziec, Paweł, 2022. "Wood pellet quality depending on dendromass species," Renewable Energy, Elsevier, vol. 199(C), pages 498-508.
    4. Kamal Baharin, Nur Syahirah & Koesoemadinata, Vidya Cundasari & Nakamura, Shunsuke & Yahya, Wira Jazair & Muhammad Yuzir, Muhamad Ali & Md Akhir, Fazrena Nadia & Iwamoto, Koji & Othman, Nor’azizi & Id, 2020. "Conversion and characterization of Bio-Coke from abundant biomass waste in Malaysia," Renewable Energy, Elsevier, vol. 162(C), pages 1017-1025.
    5. Mejdi Jeguirim & Lionel Limousy, 2017. "Biomass Chars: Elaboration, Characterization and Applications," Energies, MDPI, vol. 10(12), pages 1-7, December.
    6. Xiaoming Zhang & Hui Yin, 2019. "A Monocular Vision-Based Framework for Power Cable Cross-Section Measurement," Energies, MDPI, vol. 12(15), pages 1-26, August.

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