Study On Inversion Method Of Aerosol Particle Dynamic Light Scattering Measurement

Dynamic light scattering(DLS)is an effective method to measure the size of submicron and nano particles,which has been developed and applied in the measurement of flowing aerosols.In the inversion process,the Fredholm integral equation of the first kind needs to be solved,which is a typical ill-conditioned problem.The scattered light intensity of the flowing aerosol is simultaneously affected by the Brownian motion and the uniform translational motion.Its inversion is more complex,which is affected not only by noise,but also by flow velocity.Particle size inversion of flowing aerosol is the key and difficult point in dynamic light scattering measurement.In order to improve the stability and accuracy of the inversion results,this paper studies the inversion algorithm.The main research contents include:1.For aerosol particles retrieval,the second-order Tikhonov regularization and truncated singular value regularization(TSVD)are used to compare and study,and the characteristics and applicability of each method are obtained.After the analysis of influencing factors of noise and velocity,the results show that: for unimodal small aerosol particles,in the case of low flow velocity,the inversion errors of TSVD are smaller than those of second-order Tikhonov.For unimodal large particles with low flow velocity and unimodal particles with high flow velocity,the increase of flow velocity will weaken the particle size information of DLS measurement,which becomes another factor affecting particle size distribution inversion besides noise.In addition,truncation of singular values further results in loss of particle size information.The inversion accuracy of TSVD decreases obviously.second-order Tikhonov corrects the small singular value and retains a certain particle size information.In this case,second-order Tikhonov is more suitable.For bimodal aerosol particles,the resolution of the DLS particle sizing measurement is limited by the noise mixed in the intensity autocorrelation function data and the inherently lower information content of the data.On this basis,the influence of flow velocity will further cause the loss of data information.second-order Tikhonov has better performance indicators and stronger bimodal resolution.The experimental results are in good agreement with the simulation results.2.For TSVD,the influence of sampling points of particle size distribution on the inversion accuracy of dynamic light scattering is studied.If the number of sampling points is not selected properly,the accuracy of inversion results will be reduced or results will deviate seriously from the true value.To solve the problem,by studying the relationship between number of sampling points,relative error(RE)of PSD and number of autocorrelation function(ACF)channels,it is concluded that the upper limit of optimal sampling points is limited by the number of ACF channels.Under different sampling points,the study of RE of PSD and the residual(RES)of electric field ACF shows that there is a weak similarity between them.Then a criterion for determining the optimal number of sampling point is constructed.Finally,a non-negative constrained TSVD method for PSD adaptive sampling(PSDAS-NNTSVD)is proposed according to the upper limit condition of optimal number of sampling points and its determination criterion.Under different flow velocities and noise levels,PSDAS-NNTSVD and non negative TSVD with fixed sampling points of PSD(PSDF-NNTSVD)were used to inverse aerosol particle simulation data of unimodal distribution with 120 channels and bimodal distribution with 160 channels.The results show that,the peak position of PSDs inverted by PSDAS-NNTSVD is closer to the true value and the proposed method has better anti-noise ability.3.It is often affected by the high noise in the measurement data and the flow velocity when using traditional methods to invert flowing aerosol particles.And then the phenomenon of decreasing peak position,decreasing peak height and widening peak width occurs,which reduces the stability of the inversion methods.In order to alleviate the influence of the above factors,considering the robustness and high accuracy of GRNN and combining with second-order difference matrix Tikhonov regularization,a second-order Tikhonov GRNN method(SOT-GRNN)is proposed.This method establishes the GRNN(vi)network structure under different flow velocities to invert PSD,which significantly reduces the effect of flow velocity on the inversion results.Simulation and experimental results verified the reliability of the method.For the dynamic light scattering particle measurement technology,the inversion of particle size has always been the main factor that prevents improvement of the accuracy.By now,for the inversion of flowing aerosol particles,dynamic light scattering technology has been rarely studied and can not give satisfactory results.In this paper,the correlation inversion algorithm is studied to provide a reference for the subsequent dynamic light scattering flowing aerosol measurement.