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本文研究了选取不同谱线组合对非均匀燃烧场分布重建精度的影响, 并针对传统模拟退火算法收敛速度慢、运行效率不高的问题, 提出了一种改进的模拟退火算法(ISA算法)用于燃烧流场的场分布重建. 通过改变算法的模型扰动及退火方式, 大大提高了算法的运行效率. 数值仿真模拟结果显示, 纳入更多的谱线有助于提高燃烧场重建的精度和降低重建对噪声的敏感性. 相较于传统模拟退火算法, 改进模拟退火算法在精度一致的前提下, 将运行效率提升了近40倍. 利用改进模拟退火算法在实验室平焰炉上重建了两种不同燃烧状态, 重建分布与原始分布基本一致. 通过数值仿真与实际实验, 验证了该方法的有效性, 对高光谱重建燃烧流场的温度浓度分布具有一定的指导意义.In this paper, a method of selecting the optimal transition lines’ combination is analyzed to measure the absorption spectrum of the non-uniform combustion flow field, which is used to solve the basic two-region distribution, and an improved simulated annealing algorithm (ISA) is proposed for reconstructing the field distribution of the combustion flow field, in order to solve the problems of slow convergence speed and low efficiency of the traditional simulated annealing algorithm. By modifying the model perturbation mode and annealing strategy, the efficiency of the algorithm and the chance to jump out of the local optimal space are further improved. According to the numerical simulation results, more transitions are helpful in improving the accuracy of combustion field reconstruction and making the reconstruction less sensitive to noise. It is worth noting that the optimal transitions’ combination is better than the non-optimal transitions’ combination with more transitions included. In this paper, three different combustion models are constructed to verify the effectiveness of the improved algorithm. A comparison between the reconstruction results of the traditional simulated annealing algorithm and the improved simulated annealing algorithm shows that both algorithms have the same precision but the latter algorithm has a higher operating efficiency, and a faster running time (nearly 40 times faster than the former algorithm). At the same time, the simulation results also show that the reconstruction accuracy will decrease slightly with the complication of combustion flow field. By building the TDLAS-HT measurement system in the laboratory and using 8 × 8 orthogonal optical path arrangement, the two different combustion states formed before and after placing the steel rod in the flat flame furnace are reconstructed, the results show that the reconstruction distribution is basically consistent with the original distribution, and the reconstructed distribution well shows the combustion characteristics of the original distribution of the flame field. The effectiveness of the proposed method is verified by numerical simulation and verification tests. Under the condition of the same reconstruction accuracy as the reconstruction accuracy of the traditional simulated annealing algorithm, the higher operating efficiency is helpful in reconstructing the rapidly changing turbulent field, which has some guiding significance for the hyperspectral reconstruction of temperature and concentration distribution in the combustion flow field.
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Keywords:
- combination of transition lines/
- field distribution reconstruction/
- simulated annealing algorithm/
- hyperspectral
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${\nu _0}/{\rm{c}}{{\rm{m}}^{ - 1}}$ $S({T_0})/({\rm{c} }{ {\rm{m} }^{ - 2} } \!\cdot\! {\rm{at} }{ {\rm{m} }^{ - 1} })$ $E''$ 7294.12 0.4041 23.7944 7306.75 0.4463 79.4964 7327.68 0.4612 136.7617 7343.85 0.3298 173.3658 7368.41 0.1731 447.2523 7381.61 0.0999 586.2435 7393.85 0.0516 744.1626 7405.11 0.0247 920.1680 7416.05 0.0142 1114.4030 7426.14 0.0042 1327.1096 7444.35 0.0005 1774.7503 7452.41 0.0002 2073.5139 Noise level Simulated annealing algorithm Improved Simulated annealing algorithm 5 optimal transitions 8 optimal transitions 5 optimal transitions 8 optimal transitions 0% 8704 s 12379 s 231 s 364 s 0.5% 8346 s 12265 s 242 s 372 s 1% 9213 s 12403 s 237 s 384 s 1.5% 9001 s 12608 s 217 s 379 s 2% 8945 s 12337 s 230 s 342 s 3% 8573 s 13151 s 225 s 356 s 4% 8733 s 12726 s 240 s 351 s 5% 8667 s 12516 s 235 s 347 s ${\nu _0}/{\rm{c}}{{\rm{m}}^{ - 1}}$ $S({T_0})/({\rm{c}}{{\rm{m}}^{ - 2}} \cdot {\rm{at}}{{\rm{m}}^{ - 1}})$ $E''$ 7467.77 1.093 E-5 2551.48 7444.36 1.100 E-3 1790.04 7185.60 1.905 E-2 1045.06 7179.75 5.814 E-3 1216.19 6807.83 6.032 E-7 3319.45 -
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