Combustion Regime Monitoring by Flame Imaging and Machine Learning


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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.

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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