高精度光散射气溶胶质量浓度测量系统的信号处理研究

气溶胶质量浓度是评价大气环境变化的关键参数，光散射法是测量该参数的有效方法。但现有反演模型多采用散射光信号积分量反演质量浓度，导致颗粒物细化信息丢失，且未考虑颗粒形貌因素。针对上述问题，本文提出了一种采用散射光信号幅度分布反演气溶胶质量浓度的分形模型，充分利用了颗粒散射光的信号幅度信息与数目信息，有效提高了反演精度。实验结果表明：对于烟尘和空气样品，分形模型质量浓度反演值与实际测量值吻合，拟合直线斜率与1的绝对差为0.034和0.016，相关系数高于0.999，实验平均相对误差均小于7.7%，而电压积分量反演的质量浓度平均相对误差则在18.7%以内。该研究为光散射法应用于在线监测气溶胶质量浓度提供了一种新的精确反演方法。

Research on Signal Processing of High-Precision Light-Scattering Measurement Systems for Aerosol Mass Concentrations

Aerosol mass concentration is a critical parameter for evaluating the changes in the atmospheric environ?ment,and the light scattering method is an effective method to measure this parameter on-line. However,the inte?grated optical signal is commonly utilized to inverse aerosol mass concentration in the currently existing inversion models,which makes the optical information of aerosols loss. Meanwhile,the factor of particle shape has not been considered. To solve these problems,this paper proposes a fractal model for aerosol mass concentration by using the pulse signal amplitude distribution of scattering light from aerosols. This model takes full advantage of the informa?tion of the signal amplitude and the corresponding number of signals,which can effectively improve the inversion ac?curacy. The experimental results indicate that the mass concentrations based on the fractal model are in agreement with the actual measured values for the dust and air samples. The absolute errors between the slope of the fitted line and 1 are 0.034 and 0.016,the correlation coefficients are above 0.999,and the average relative errors are less than 7.7%. But the average relative errors of mass concentrations inversed through the integrated optical signal are less than 18.7%. The study provides a new accurate method for the online monitoring of the aerosol mass concentration based on the light scattering.