Experimental and Numerical Based Defect Detection in a Model Combustion Chamber through Machine Learning

被引：0
|
作者：
von der Haar, Henrik [1 ]
Ignatidis, Panagiotis [1 ]
Dinkelacker, Friedrich [1 ]
机构：
[1] Institute of Technical Combustion, Leibniz Universität Hannover, An der Universität 1, Garbsen, 30823, Germany
来源：
International Journal of Gas Turbine, Propulsion and Power Systems | 2021年 / 12卷 / 04期
关键词：
Automatic defect detections - Combustion pro-cess - Combustion state - Defect detection - Down time - Internal flows - Machine-learning - Resource management - Species distributions - Support vector machines algorithms;
D O I：
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页码：1 / 9
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