ISSN:
1013-9826
Source:
Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
This paper presents a high precision temperature measurement instrument based on quartztuning-fork temperature sensor (QTTS) using Artificial Neural Networks (ANN). The advantage ofQTTS is a great sensitivity which makes possible to determine the temperature with the accuracy of0.01 °C , but the QTTS based temperature measurement instrument often appears as erroneoustemperature reading when using standard polynomial calibration techniques over a large temperaturerange. For high precision temperature measurement, a new method is presented to compensatenon-linearity of QTTS based instrument using non-linearity compensation model using ANN byLevenberg-Marquardt algorithm to settle its non-linear problem. The hardware and software parts ofthe system are integrated in a PC-based instrument used for operation and calibration. ANN basedmodelling and correction technique has been evaluated experimentally, followed by experimentalresults obtained by applying the method to QTTS calibration
Type of Medium:
Electronic Resource
URL:
http://www.tib-hannover.de/fulltexts/2011/0528/01/57/transtech_doi~10.4028%252Fwww.scientific.net%252FKEM.381-382.477.pdf
