Temperature estimation for a point of an infrared dryer using temperature of neighbouring points: An artificial neural network approach

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.