Detalle Publicación

A novel method for error analysis in radiation thermometry with application to industrial furnaces
Autores: Martínez, I. (Autor de correspondencia); Otamendi, U.; Olaizola, I. G.; Solsona, R.; Maiza, M.; Viles Díez, Elisabeth; Fernández, A.; Arzúa, I.
Título de la revista: MEASUREMENT
ISSN: 0263-2241
Volumen: 190
Páginas: 110646
Fecha de publicación: 2022
Lugar: WOS
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 techniques, such as the uncertainty in the emissivity of the target surface, reflected radiation from surrounding objects, or atmospheric absorption and emission, to name a few. Undesired contributions to measured radiation can be isolated using measurement models, also known as error-correction models. This paper presents a methodology for budgeting significant sources of error and uncertainty during temperature measurements in a petrochemical furnace scenario. A continuous monitoring system is also presented, aided by a deep-learning-based measurement correction model, to allow domain experts to analyze the furnace's operation in real-time. To validate the proposed system's functionality, a real-world application case in a petrochemical plant is presented. The proposed solution demonstrates the viability of precise industrial furnace monitoring, thereby increasing operational security and improving the efficiency of such energy-intensive systems.