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This paper aims at introduction, design, and validation of a temperature estimation algorithm for an infrared dryer. The proposed algorithm estimates the temperature at one or some points in a thermal system (e.g., an infrared dryer) based on the measured temperature at a number of other points. In this research, the designed algorithm estimates the temperature of a single point; however, the methodology can be evidently extended to multiple points. Inspired by direct and inverse heat transfer models, a mathematical model is presented for this purpose. This model is developed and identified using artificial neural network (ANN) technique and laboratory experimental data. The proposed method exhibits excellent accuracy with no need to thermo-physical properties of the system. [ABSTRACT FROM AUTHOR]

This paper presents the idea of virtual temperature sensors for irradiative enclosures. Such a virtual sensor is an algorithm which receives the temperature of a number of points on surfaces of an enclosure and estimates the temperature of another point (or a number of other points) within enclosure. This paper proposes a data-driven method based on fuzzy inference systems to develop temperature virtual sensing algorithms. The proposed method is validated on an experimental setup exhibiting excellent estimation accuracy with no need to thermo-physical properties of the enclosure. In this research, the designed and validated algorithm estimates the temperature of a single point; however, the methodology can be evidently extended to multiple points. [ABSTRACT FROM AUTHOR]