基于多点真温及光谱发射率自适应反演的面温重建算法研究

For the developing of multi-wavelength radiation temperature measurement technology, we will expolore a inversion algorithm of point true temperature and surface temperature field based on multi-wavelength emissivity adaptive mthod. The multispectral radiation temperature measurement data processing will be combined with underdetermined equations solving method, it will realize points true temperature and spectral emissivity meausrement of tested objective surface at the same time.The proposed algorithm need not assumption of emissivity model, meet the goals of continuous spectral radiant, greatly enhance multi-spectral radiation temperature measurement data processing accuracy and efficiency. Using the obtained multi-point true temperature, combined the priciple of cross temperature measurement, curve of cross temperature will be acquired by interpolation method,then harmonizing the thermal physical property parameters of the target under test, through neural network method to reconstruct the surface temperature field. With the widely application of multi-wavelength radiation temperature meausrement technology in high temperature test field, it shows the more importance for automated identification of spectral emissivity and surface temperature field of fast reconstruction increasingly. Especially, with the development of new type burner, the true temperature measurement of the special position and real-time monitoring the whole surface temperature field is particularly important. Temperature field reconstruction technique based on multispectral radiation due to the advantages in true temperature measurement, is expected to become the powerful tool in the fields of the rocket jet flame diagnosis, marine supercharged boiler furnace flame combustion parameters optimization, the furnace flame temperature field reconstruction of large coal-fired power stations..

为了发展多光谱辐射测温技术，我们设计了基于多光谱辐射测温理论的发射率自适应点温及面温反演算法。将多光谱辐射测温数据处理过程与欠定方程组求解方法相结合，实现待测目标表面多点真温及光谱发射率的同时测量，算法无需假设发射率模型、适合于任何连续光谱辐射目标，增强了多光谱辐射测温数据处理算法的精度和效率；根据已获得的若干点真温，结合十字测温原理，利用插值法获取十字测温曲线，再融合待测目标的热物性参数，通过神经网络方法重建待测表面温度场。随着多光谱辐射测温技术在高温测量领域的不断应用，光谱发射率的自动识别和表面温度场快速重建的重要性日益凸显，特别是随着新型燃烧器的发展，对特殊位置的真温测量及整体表面温度场的实时监测变得尤为重要。基于多光谱辐射的温度场重建技术由于在真温测量方面的优势，有望成为火箭尾喷焰诊断、船用增压锅炉炉膛火焰燃烧参数优化、大型燃煤电站炉膛火焰温度场重建等领域的有力工具之一。

多光谱辐射测温技术是在一台仪器中制成多个光谱通道，利用同时获得待测目标点的多光谱辐射亮度测量信息，经数据处理，得到目标的真实温度和光谱发射率。这种方法对被测对象无特殊要求，因而特别适合于高温、甚高温目标的真温及材料发射率的同时测量。本项目旨在探索基于多光谱辐射的无需发射率假设模型多点真温及发射率自适应数据处理方法，从而进一步开展由点温及面温的多光谱辐射表面温度场重建算法研究，为实现基于多光谱辐射测温理论的温度场测量技术奠定理论基础。经过三年的研究，将多光谱辐射真温和发射率反演问题转换为约束优化问题，提出了基于约束优化的无需任何假设发射率模型的多光谱辐射测温反演算法，利用内点罚函数算法实现了可适合于任何目标的多光谱辐射真温反演，对六种不同光谱发射率材料进行仿真，结果表明在真温1800K及加入5%自由噪声的情况下，温度的不确定度为1800±10K，对火箭发动机尾喷焰采集的多光谱数据处理结果表明，在设计温度2490K的情况下，反演的温度不确定度为2490±25K（Optics Express 2017,25（24）：30506）。在面温重建算法方面，利用多点真温结合CCD获得的像素亮度信息，实现了基于多光谱辐射温度场的测量，丁烷喷枪和某型火箭尾喷焰实验也证明了基于多点真温结合图像处理技术可以实现温度场的测量。

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