A Software Improvement Technique for Platinum Resistance Thermometers

Abstract

Temperature measurement is essential in industries. The advantages of resistance temperature detectors (RTDs) are high sensitivity, repeatability, and long-term stability. The measurement performance of this thermometer is of concern. The connection between RTDs and a novel microprocessor system provides a new method to improve the performance of RTDs. In this study, the adequate piecewise sections and the order of polynomial calibration equations were evaluated. Systematic errors were found when the relationship between temperature and resistance for PT-1000 data was expressed using the inverse Callendar-Van Dusen equation. The accuracy of these calibration equations can be improved significantly with two piecewise equations in different temperature ranges. Two datasets of the resistance of PT-1000 sensors in the range from 0 °C to 50 °C were measured. The first dataset was used to establish adequate calibration equations with regression analysis. In the second dataset, the prediction temperatures were calculated by these previously established calibration equations. The difference between prediction temperatures and the standard temperature was used as a criterion to evaluate the prediction performance. The accuracy and precision of PT-1000 sensors could be improved significantly with adequate calibration equations. The accuracy and precision were 0.027 °C and 0.126 °C, respectively. The technique developed in this study could be used for other RTD sensors and/or different temperature ranges.