红外测温仪器的精度和被测物体表面的发射率对测量物体红外辐射特性的准确性影响很大。为了提高物体表面发射率的计算精度, 先通过标准黑体对红外热像仪进行标定。然后, 利用标定好的红外热像仪测量温度, 计算出被测物体表面的发射率。将基于神经网络的红外热像仪标定方法应用到目标发射率的求解方法中, 有效地消除了热像仪的系统误差。测试装置简单, 测试结果准确。同时, 温度和发射率的精确测量为红外隐身材料的研制奠定了基础。

The precision of infrared temperature measurement instruments and the surface emissivity of the tested object have a great influence on the accuracy of infrared radiation measurement. In order to improve the calculation accuracy of surface emissivity, an infrared thermal imager is calibrated through a standard blackbody. Then, the temperature is measured with the calibrated infrared thermal imager, and the surface emissivity of the object to be tested is calculated. By using the calibration method of the infrared thermal imager based on neural network to calculate the target emissivity, the system error of the infrared thermal imager is effectively eliminated. The measuring equipment is simple and its measurement result is accurate.At the same time, the precise measurement of the temperature and emissivity has laid the basis for the development of infrared stealth materials.