Abstract:
This paper presents the results of a study aimed at assessing the effects of temperature and thermal gradient on psychrometer readings, and at developing a calibration protocol that takes into account these effects. An intensive calibration programme was conducted at different temperatures (20-35 degrees C) and water potential levels (0.0 to similar to 7.0 MPa), for this purpose. The thermal gradient was expressed as the difference in temperature between wet and dry junctions in the thermocouple psychrometer sensor. The collected calibration data were used to build an artificial neural network psychrometer model. The developed model was able to simulate successfully the psychrometer output at different conditions, and was used to conduct a detailed parametric study to evaluate the influence of temperature and thermal gradient on thermocouple psychrometer measurements. The outcome of this study shows the importance of including the effects of temperature and thermal gradient in the standard calibration process. Moreover, it introduces a new, precise calibration protocol that takes advantage of the artificial neural network approach.