Temperature gradient is an important performance indicator of a stirred liquid bath. Its evaluation requires measuring the temperature differences between different bath positions. A common way to do that is to place two SPRTs at two positions and measure their resistances against a standard resistor (R SPRT1/R S and R SPRT2/R S) sequentially (the sequential method). A drawback of this method is the existence of a time gap between the two measurements rendering the results susceptible to temporal temperature variation. The instantaneous comparisons method offers a better solution by measuring the resistance ratio of two SPRTs directly (R SPRT1/R SPRT2) and deriving their temperature difference at the same moment eliminating the time gap. To implement this method at the Standards and Calibration Laboratory (SCL) of Hong Kong, the resistance ratio of SPRT1 to a standard resistor (R SPRT1/R s) is firstly measured to determine the initial bath temperature. After that, the resistance ratios of SPRT1 to SPRT2 (R SPRT1/R SPRT2) are measured with the two SPRTs placed at different positions and immersion depths in the bath. This paper describes the derivation of the temperature difference from the SPRT resistance ratio using the ITS-90 reference equations and the estimation of the measurement uncertainties. The potential of reducing the uncertainties of measured temperature gradient by leveraging the correlation of the two SPRTs calibrated at the same set of temperature fixed points is discussed. The paper also compares the calibration results obtained by the instantaneous comparisons method and the sequential method.

Traditionally, thermometers are calibrated by comparison with reference thermometers, such as standard platinum resistance thermometers in liquid baths. The process is time consuming and costly since an operator is required to adjust the bath temperature and take the readings of the thermometers. The Standards and Calibration Laboratory (SCL), Hong Kong Special Administrative Region recently developed a fully automated calibration system for thermometer calibration which does not require the attention of an operator. The system makes use of a computer to control the bath temperature and take the thermometer readings by using pattern recognition techniques. Optical Character Recognition (OCR) and Liquid Level Recognition (LLR) techniques are employed to take the readings of the digital and liquid-in-glass thermometers respectively. The reading process starts with taking pictures of the display of the thermometer under test by a smart video camera. The images are analyzed by Labview based programmes to find the thermometer readings. The system can be trained to recognize various display formats of the thermometers under test. The images of the display readings are retained for proof checking when a report is produced.