Identification and prediction of the dynamic properties of resistance temperature sensors

• Software was developed to identify and predict the resistance temperature sensors’ dynamic properties.
• An optimization problem is solved to determine the optimum transfer function of the sensor.
• A Pt100 sensor was tested using the plunge test and the self-heating test methods.
• The sensor's dynamic properties for the plunge test were successfully predicted.

The plunge test method and the self-heating test method represent two experimental techniques for identifying the dynamic properties of temperature sensors. The dynamic behaviour of a resistance temperature sensor can be described using transfer functions, which differ for the two test methods. It is possible to predict the sensor's dynamic properties for the plunge test with a proper transformation of the identified model for the self-heating test. The main contribution of the presented research work is the software, based on virtual instrumentation, developed to identify and predict the dynamic properties of resistance temperature sensors. The excitation signal and the sensor's response are utilized to identify its transfer function. The number of parameters for the approximation model is determined as a result of an optimization problem. The software was validated and then applied to identify and predict the dynamic properties of a commercial-grade Pt100 sensor. In this case study, the plunge test and the self-heating test were performed with a step change of the surrounding temperature and the supplied electrical power, respectively, under laboratory conditions. The relative difference between the predicted and the identified sensor's time constants for the plunge test equals -7.4%, which is within the acceptance interval of ±10%. The tested resistance temperature sensor was therefore experimentally validated as being suitable for dynamic testing using the self-heating method.