基于多波长激光吸收光谱技术的气体浓度与温度二维分布遗传模拟退火重建研究

Gas concentration and temperature reconstruction by genetic simulated annealing algorithm based on multi-wavelengths diode laser absorption spectroscopy

利用可调谐半导体激光吸收光谱技术实现气体浓度温度二维分布重建.设计了气体浓度温度二维分布重建测量系统,采用四路波分复用技术以减少投影光路布置数量和增加气体吸收测量信息.针对于图像重建过程中建立的非线性投影方程组,将遗传算法与模拟退火算法相结合进行求解,在实现全局最优搜索基础上提高算法搜索效率.建立燃烧环境下H2O浓度温度二维分布模型,借助于近红外波段1.3—1.5μm范围内4条H2O气体吸收谱线,利用数值模拟计算方法进行了气体分布重建,重建结果与模型符合得很好.通过在投影数据中添加不同比例的随机误差,考察其对气体分布重建结果的影响.研究表明,气体浓度分布重建结果对于投影误差不敏感,而增加投影误差幅值将导致温度分布重建均方误差增大。

Gas concentration and temperature distribution reconstruction is realized based on tunable diode laser absorption spectroscopy.A measurement system using wavelength multiplexing technology with four absorption transitions is designed to reduce the number of projections and enrich the gas absorption measurement data.According to the nonlinear system established,a hybrid algorithm based on genetic algorithm and simulated annealing algorithm is introduced to obtain the global optimization and improve the search efficiency.A model for H2O concentration and temperature distribution in combustion is assumed,and numerical simulation is utilized to reconstruct the images with the transitions within 1.3—1.5 μm range.Both concentration and temperature distribution reconstruction results are in agreement with the model.The influence of random errors in projections on reconstruction is also analyzed.The increased error in projection would lead to larger mean square error of temperature reconstruction results,but little affect the concentration reconstruction results.