A novel method for error analysis in radiation thermometry with application to industrial furnaces

• Published in: Measurement : journal of the International Measurement Confederation Vol. 190; p. 110646
• Main Authors: Martinez, Iñigo, Otamendi, Urtzi, Olaizola, Igor G., Solsona, Roger, Maiza, Mikel, Viles, Elisabeth, Fernandez, Arturo, Arzua, Ignacio
• Format: Journal Article
• Language: English
• Published: London Elsevier Ltd 28.02.2022; Elsevier Science Ltd
• Subjects: Atmospheric models; Chemical industry; Continuous furnaces; Deep learning; Emissions; Error analysis; Error correction; Furnaces; Infrared imagery; Measurement; Monitoring; Monitoring system; Petrochemical industry; Petrochemicals; Radiation; Radiation thermometry; Real time operation; Surrogate model; Thermometers; Thermometry; Uncertainty; Monitoring system; Deep learning; Petrochemical industry; Radiation thermometry; Error analysis; Surrogate model; Infrared imagery

Accurate temperature measurements are essential for the proper monitoring and control of industrial furnaces. However, measurement uncertainty is a risk for such a critical parameter. Certain instrumental and environmental errors must be considered when using spectral-band radiation thermometry tech...