Development of a High-Precision Temperature Measurement Instrument Based on Quartz Tuning-Fork Temperature Sensor
This paper presents a high precision temperature measurement instrument based on quartz tuning-fork temperature sensor (QTTS) using Artificial Neural Networks (ANN). The advantage of QTTS is a great sensitivity which makes possible to determine the temperature with the accuracy of 0.01 °C , but the QTTS based temperature measurement instrument often appears as erroneous temperature reading when using standard polynomial calibration techniques over a large temperature range. For high precision temperature measurement, a new method is presented to compensate non-linearity of QTTS based instrument using non-linearity compensation model using ANN by Levenberg-Marquardt algorithm to settle its non-linear problem. The hardware and software parts of the system are integrated in a PC-based instrument used for operation and calibration. ANN based modelling and correction technique has been evaluated experimentally, followed by experimental results obtained by applying the method to QTTS calibration.
Wei Gao, Yasuhiro Takaya, Yongsheng Gao and Michael Krystek
J. Xu et al., "Development of a High-Precision Temperature Measurement Instrument Based on Quartz Tuning-Fork Temperature Sensor", Key Engineering Materials, Vols. 381-382, pp. 477-480, 2008