Combustion Regime Monitoring by Flame Imaging and Machine Learning
- Autores: Abdurakipov S.S.1,2, Gobyzov O.A.1,2, Tokarev M.P.1,2, Dulin V.M.1,2
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Afiliações:
- Kutateladze Institute of Thermophysics, Siberian Branch
- Novosibirsk State University
- Edição: Volume 54, Nº 5 (2018)
- Páginas: 513-519
- Seção: Modeling in Physical and Technical Research
- URL: https://journals.rcsi.science/8756-6990/article/view/212588
- DOI: https://doi.org/10.3103/S875669901805014X
- ID: 212588
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Resumo
A method for automatic determination of combustion regimes using flame images on the basis of a convolutional neural network on labeled data is under consideration. It is shown that the accuracy of regime classification reaches 98% on the flame images of a gas burner. The results of the operation of the convolutional neural network and classification using different linear models are compared.
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Sobre autores
S. Abdurakipov
Kutateladze Institute of Thermophysics, Siberian Branch; Novosibirsk State University
Email: oleg.a.g.post@gmail.com
Rússia, pr. Akademika Lavrent’eva 1, Novosibirsk, 630090; ul. Pirogova 2, Novosibirsk, 630090
O. Gobyzov
Kutateladze Institute of Thermophysics, Siberian Branch; Novosibirsk State University
Autor responsável pela correspondência
Email: oleg.a.g.post@gmail.com
Rússia, pr. Akademika Lavrent’eva 1, Novosibirsk, 630090; ul. Pirogova 2, Novosibirsk, 630090
M. Tokarev
Kutateladze Institute of Thermophysics, Siberian Branch; Novosibirsk State University
Email: oleg.a.g.post@gmail.com
Rússia, pr. Akademika Lavrent’eva 1, Novosibirsk, 630090; ul. Pirogova 2, Novosibirsk, 630090
V. Dulin
Kutateladze Institute of Thermophysics, Siberian Branch; Novosibirsk State University
Email: oleg.a.g.post@gmail.com
Rússia, pr. Akademika Lavrent’eva 1, Novosibirsk, 630090; ul. Pirogova 2, Novosibirsk, 630090
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