论文标题
使用粒子群优化算法在无校准波长调制光谱系统中浓度检索
Concentration retrieval in a calibration-free wavelength modulation spectroscopy system using particle swarm optimization algorithm
论文作者
论文摘要
本文根据粒子群优化（PSO）算法开发了光谱拟合技术，该算法应用于无校准的波长调制光谱系统以实现浓度检索。与基于Levenberg-Marquardt（LM）算法的其他光谱拟合技术相比，该技术相对较弱地依赖于激光参数的预示率化。通过使用PSO算法将模拟光谱拟合到测量光谱中来计算气体浓度。我们用LM算法和PSO算法验证了目标气体C2H2的模拟。结果表明，当拟合精度保持不变时，基于PSO算法的光谱拟合技术的收敛速度比LM算法快63倍。在5秒钟内，PSO算法可以产生通常与预期值一致的发现。
This paper develops a spectral fitting technology based on the particle swarm optimization (PSO) algorithm, which is applied to a calibration-free wavelength modulation spectroscopy system to achieve concentration retrieval. As compared with other spectral fitting technology based on the Levenberg-Marquardt (LM) algorithm, this technology is relatively weakly dependent on the pre-characterization of the laser parameters. The gas concentration is calculated by fitting the simulated spectra to the measured spectra using the PSO algorithm. We validated the simulation with the LM algorithm and PSO algorithm for the target gas C2H2. The results showed that the convergence speed of the spectral fitting technique based on the PSO algorithm was about 63 times faster than the LM algorithm when the fitting accuracy remained the same. Within 5 seconds, the PSO algorithm can produce findings that are generally consistent with the values anticipated.
