Monitoring of combustion regimes based on the visualization of the flame and machine learning

M. P. Tokarev, S. S. Abdurakipov, O. A. Gobyzov, A. V. Seredkin, V. M. Dulin

Результат исследования: Научные публикации в периодических изданияхстатья по материалам конференциирецензирование

2 Цитирования (Scopus)


Development of modern intelligent monitoring and control systems in energy, allowing reducing the level of harmful emissions and energy intensity production is relevant. In the scientific literature usage of new efficient machine learning techniques for automatic extraction of features for the classification of combustion regimes is insufficiently covered. In this paper we describe a method for determining combustion regimes based on images of flames. To determine the combustion regimes, a convolutional neural network is trained using labeled data. It is shown that in the gas flame colour images the accuracy of the classification of regimes is up to 98%. Results of the convolutional neural network are compared to classification results of various linear models.

Язык оригиналаанглийский
Номер статьи012138
Число страниц6
ЖурналJournal of Physics: Conference Series
Номер выпуска1
СостояниеОпубликовано - 7 дек. 2018
Событие3rd All-Russian Scientific Conference Thermophysics and Physical Hydrodynamics with the School for Young Scientists, TPH 2018 - Yalta, Crimea, Украина
Продолжительность: 10 сент. 201816 сент. 2018


Подробные сведения о темах исследования «Monitoring of combustion regimes based on the visualization of the flame and machine learning». Вместе они формируют уникальный семантический отпечаток (fingerprint).