Department of Electrical Engineering, National Taiwan University, Taipei 10617, Taiwan.
Sensors (Basel). 2013 Dec 12;13(12):17084-97. doi: 10.3390/s131217084.
Thermocouples are the most frequently used sensors for temperature measurement because of their wide applicability, long-term stability and high reliability. However, one of the major utilization problems is the linearization of the transfer relation between temperature and output voltage of thermocouples. The linear calibration equation and its modules could be improved by using regression analysis to help solve this problem. In this study, two types of thermocouple and five temperature ranges were selected to evaluate the fitting agreement of different-order polynomial equations. Two quantitative criteria, the average of the absolute error values |e|(ave) and the standard deviation of calibration equation e(std), were used to evaluate the accuracy and precision of these calibrations equations. The optimal order of polynomial equations differed with the temperature range. The accuracy and precision of the calibration equation could be improved significantly with an adequate higher degree polynomial equation. The technique could be applied with hardware modules to serve as an intelligent sensor for temperature measurement.
热电偶因其适用性广、长期稳定性好和可靠性高,是最常用的温度传感器。然而,其主要应用问题之一是热电偶的温度与输出电压之间的传递关系的线性化。通过使用回归分析可以改进线性校准方程及其模块,以帮助解决这个问题。在这项研究中,选择了两种类型的热电偶和五个温度范围,以评估不同阶多项式方程的拟合一致性。使用两个定量标准,即平均绝对误差值 |e|(ave) 和校准方程的标准偏差 e(std),来评估这些校准方程的准确性和精密度。多项式方程的最佳阶数随温度范围而变化。通过使用足够高的阶多项式方程,可以显著提高校准方程的准确性和精密度。该技术可以与硬件模块一起应用,作为智能温度传感器。