摘要
The real-time retrieval of submicron aerosol size distributions is of major interest for applications. Based on the Mie theory,the spectral extinction method offers a simple measurement principle and a convenient optical arrangement. In contrast to the relative simplicity of the experimental measurement the retrieval of the particles size distribution and particle concentration from the spectral extinction method is difficult. Mie scattering Equation is a Fredholm Integral Equation of the First Kind. This paper develops a hybrid iterative model-dependent algorithm for on-line particle sizing from extinction spectra which is both computationally efficient and accurate. Applying the refined Mie diagnostic iterative procedures within some candidate solutions can identify the unique result accurately and rapidly enough for real time measurement. With the addition of added Gaussian noise,an average tolerance up to 5% of noise level is kept for particle size from submicron to micrometer under moderate polydispersity.
The real-time retrieval of submicron aerosol size distributions is of major interest for applications. Based on the Mie theory,the spectral extinction method offers a simple measurement principle and a convenient optical arrangement. In contrast to the relative simplicity of the experimental measurement the retrieval of the particles size distribution and particle concentration from the spectral extinction method is difficult. Mie scattering Equation is a Fredholm Integral Equation of the First Kind. This paper develops a hybrid iterative model-dependent algorithm for on-line particle sizing from extinction spectra which is both computationally efficient and accurate. Applying the refined Mie diagnostic iterative procedures within some candidate solutions can identify the unique result accurately and rapidly enough for real time measurement. With the addition of added Gaussian noise,an average tolerance up to 5% of noise level is kept for particle size from submicron to micrometer under moderate polydispersity.