Signal and Image Centre, Royal Military Academy, Avenue de la Renaissance 30, B-1000 Brussels, Belgium.
Sensors (Basel). 2018 Nov 22;18(12):4087. doi: 10.3390/s18124087.
In this paper, we demonstrate an improvement in the accuracy of a low-cost smart temperature sensor, by measurement of the nonlinear curvature correction at multiple temperature references. The sensors were positioned inside a climate chamber and connected outside to a micro-controller via a network cable. The chamber temperature was increased systematically over a wide range from -20 °C to 55 °C. A set of calibration curves was produced from the best fitting second-order polynomial curves for the offset in temperature between the sensor and reference. An improvement in accuracy of ±0.15 °C is with respect to the mentioned temperature range, compared to the significantly higher value reported of ±0.5 °C by the manufacturer for similar conditions. In summary, we demonstrate a significant improvement in the calibration of a low-cost, smart sensor frequently used in research and academic projects over a useful range of temperatures.
在本文中，我们通过在多个温度参考点测量非线性曲率校正，提高了低成本智能温度传感器的精度。这些传感器被放置在气候室内，通过网络电缆与外部的微控制器相连。将室内温度从-20°C 到 55°C 范围内系统性地升高。对于传感器和参考之间的温度偏移，我们从最佳拟合的二阶多项式曲线中生成了一组校准曲线。与制造商在类似条件下报告的±0.5°C 相比，在提到的温度范围内，精度提高了±0.15°C。总之，我们证明了在有用的温度范围内，对研究和学术项目中常用的低成本智能传感器的校准有了显著的提高。
