Yang Wenhang, Cao Chen, Huang Pujiang, Bai Jindong, Zhao Bangjian, Zhu Shouzheng, Jin Haijun, Jin Ke, He Xin, Li Chunlai, Wang Jianyu, Liu Shijie, Qi Hongxing
Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China.
Sensors (Basel). 2024 Mar 6;24(5):1707. doi: 10.3390/s24051707.
High-precision temperature control of large-area blackbodies has a pivotal role in temperature calibration and thermal imaging correction. Meanwhile, it is necessary to correct the temperature difference between the radiating (surface of use) and back surfaces (where the temperature sensor is installed) of the blackbody during the testing phase. Moreover, large-area blackbodies are usually composed of multiple temperature control channels, and manual correction in this scenario is error-prone and inefficient. At present, there is no method that can achieve temperature-automated calibration for a large-area blackbody radiation source. Therefore, this article is dedicated to achieving temperature-automated calibration for a large-area blackbody radiation source. First, utilizing two calibrated infrared thermometers, the optimal temperature measurement location was determined using a focusing algorithm. Then, a three-axis movement system was used to obtain the true temperature at the same measurement location on a large-area blackbody surface from different channels. This temperature was subtracted from the blackbody's back surface. The temperature difference was calculated employing a weighted algorithm to derive the parameters for calibration. Finally, regarding experimental verification, the consistency error of the temperature measurement point was reduced by 85.4%, the temperature uniformity of the surface source was improved by 40.4%, and the average temperature measurement deviation decreased by 43.8%. In addition, this system demonstrated the characteristics of strong environmental adaptability that was able to perform temperature calibration under the working conditions of a blackbody surface temperature from 100 K to 573 K, which decreased the calibration time by 9.82 times.
大面积黑体的高精度温度控制在温度校准和热成像校正中起着关键作用。同时，在测试阶段有必要校正黑体辐射面（使用表面）和背面（安装温度传感器的位置）之间的温差。此外，大面积黑体通常由多个温度控制通道组成，在这种情况下手动校正容易出错且效率低下。目前，尚无能够实现大面积黑体辐射源温度自动校准的方法。因此，本文致力于实现大面积黑体辐射源的温度自动校准。首先，利用两个经过校准的红外温度计，使用聚焦算法确定最佳温度测量位置。然后，使用三轴移动系统从不同通道获取大面积黑体表面同一测量位置的真实温度。将该温度从黑体背面温度中减去。采用加权算法计算温差以得出校准参数。最后，通过实验验证，温度测量点的一致性误差降低了85.4%，表面源的温度均匀性提高了40.4%，平均温度测量偏差降低了43.8%。此外，该系统表现出强大的环境适应性，能够在黑体表面温度为100 K至573 K的工作条件下进行温度校准，校准时间缩短了9.82倍。
