Combustion stability monitoring through flame imaging and stacked sparse autoencoder based deep neural network

•A novel deep learning model is established for predicting combustion stability.•Automatic generation of combustion stability label is achieved.•Quantitative and qualitative evaluation of combustion stability are presented.•Generalization and robustness of the model are verified. Combustion instabil...

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Bibliographic Details
Published in:	Applied energy Vol. 259; p. 114159
Main Authors:	Han, Zhezhe, Hossain, Md. Moinul, Wang, Yuwei, Li, Jian, Xu, Chuanlong
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.02.2020
Subjects:	combustion combustion efficiency Combustion stability emissions Flame imaging furnaces Gaussian mixture model image analysis Innovative loss function monitoring pollutants prediction regression analysis Stacked sparse autoencoder Innovative loss function Stacked sparse autoencoder Combustion stability Flame imaging Gaussian mixture model
ISSN:	0306-2619, 1872-9118
Online Access:	Get full text
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