基于光场成像技术的散射性火焰温度场重建

光场成像是一项新兴的非接触式测温技术，针对传统辐射成像温度场重构效率低的问题，开展了基于光场成像的散射性火焰温度场重建研究。在火焰光场成像模型的基础上，以广义源项多流法为正问题模型，利用Landweber算法重构吸收散射性火焰的三维温度场，同时引入最小二乘QR（LSQR）分解算法作为对比以衡量Landweber算法的性能。分析了测量误差对于重建精度的影响，重建结果表明，即使在添加5%测量误差的情况下温度场的平均重建相对误差也仅为0.91%和0.92%，重建结果仍然是合理的。Landweber算法和LSQR算法具有相当的计算精度，但Landweber算法的计算时间是LSQR算法的1/10，其计算效率明显优于LSQR算法。 

Temperature field reconstruction of scattering flame based on light-field imaging

Light field imaging technology is an emerging non-contact temperature measurement technology. Aiming at the important role of light field imaging reconstruction algorithm for flame temperature field measurement, the flame temperature field reconstruction algorithm based on light field imaging was studied. A flame temperature field reconstruction method based on the light-field imaging technique is proposed, the generalized sourced multi-flux method is used as the calculation method of direct problem, and Landweber algorithm is applied to reconstruct the 3D temperature field of absorbing and scattering flame based on the flame light-field imaging model. The Least-Square QR (LSQR) decomposition algorithm is also introduced to our study as a comparison to verify the performance of Landweber algorithm. Effect of measurement errors on the computational accuracy is studied. The reconstruction results demonstrate that the temperature field can be reconstructed reasonably by these two methods, and even with 5% measurement error, the mean reconstruction relative errors are 0.91% and 0.92% respectively, which are acceptable. The comparative results show that the Landweber algorithm has the similar calculation precision as LSQR algorithm, but the calculation time of the Landweber algorithm is one tenth of that of LSQR algorithm, and thus the Landweber algorithm is much more efficient than LSQR algorithm.