Deep Learning-Based Surface Temperature Prediction for a Porous Radiant Burner Using Thermocouple-Calibrated Thermal Infrared Images

Deep Learning-Based Surface Temperature Prediction for a Porous Radiant Burner Using Thermocouple-Calibrated Thermal Infrared Images

This paper presents an artificial intelligence (AI)-based method for surface temperature prediction, applying a hybrid convolutional neural network and LASSO regression (CNN-LASSO) to thermocouple-calibrated thermal infrared (IR) images of a large cylindrical top-dome hollow porous radiant burner fo...

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Bibliographic Details
Main Authors: Hao-Yu Hsieh, Shenqyang Shy, Wei-Wun Wang, Yung-Chien Chou
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Porous radiant burner
convolutional neural network
deep learning analyses
infrared thermal image
surface temperature prediction
thermocouple calibration
Online Access:https://ieeexplore.ieee.org/document/11050381/
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