第 49 卷 第 3 期 化工自动化及仪表 307
Clas Blocken B,Stathopoulos T,Carmeliet J J
39~44. Simulation of the Atmospheric Boundary Layer:Wall
[7] Radford A,Metz L,Chintala Represen- Function Problems [J].Atmospheric Environment,
tation Learning with Deep Convolutional Generative 2007,41(2):238~252.
Adversarial Networks[J/OL]..
06434,2022-03-06. (收稿日期:2022-03-06,修回日期:2022-05-10)
The infoGAN-based Temperature Field Prediction
Method for Industrial Heating Furnace
SUN Quan-sheng
(Equipment Institute, Sinopec Tianjin Branch Co.)
Abstract The temperature field’s uneven distribution of the industrial heating furnace and the furnace tube’s
local overtemperature may result in accidents. The CCD imaging-based online temperature field visualization
system was designed and basing on the mutual information generative adversarial network adopted, a expanded
channel model-based temperature field prediction model was established, and Matlab software was adopted to
visualize output results of the model so
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