Nonlinear Calibration of Thermocouple Sensor Based on Least Squares Support Vector Regression

DOI

10.2991/iccsae-15.2016.2How to use a DOI?

Keywords

nonlinear calibration, least squares support vector regression, sensor, power series

Abstract

Calibration is an important operation in the instrumentation industry for determining the relationship between the output(s) (or response) of a measuring instrument and the value of the input(s). This paper proposes a nonlinear calibration method based on least squares support vector regression (LS-SVR) with the output voltage of thermocouple sensor as input and the measured temperature output to eliminate the nonlinear errors in detection process. Firstly, the nonlinear calibrator, expressed by power series, was established based on the principle of inverse model. And then the parameters of the calibrator were identified by LS-SVR. Through this calibrator, the desired linear characteristics of thermocouple sensor could be obtained. Finally, platinum-rhodium 30– platinum-rhodium 6-thermocouple (B-type) was taken as an example, and experimental results show that the proposed calibration method is efficient in the temperature range from 400 to 1800 . And the method has an advantage of analytical expression of the calibration model.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shengbo Zhang
AU  - Qingling Dai
PY  - 2016/02
DA  - 2016/02
TI  - Nonlinear Calibration of Thermocouple Sensor Based on Least Squares Support Vector Regression
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 5
EP  - 10
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.2
DO  - 10.2991/iccsae-15.2016.2
ID  - Zhang2016/02
ER  -