Development of a mass model in estimating weight-wise particle size distribution using digital image processing

Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.

On-line full scan inspection of particle size and shape using digital image processing

An on-line full scan inspection system is developed for particle size analysis. A particle image is first obtained through optical line scan technology and is then analyzed using digital image processing. The system is composed of a particle separation module, an image acquisition module, an image processing module, and an electric control module. Experiments are carried out using non-uniform 0.1 mm particles. The main advantage of this system consists of a full analysis of particles without any overlap or miss, thus improving the Area Scan Charge Coupled Device （CCD） acquisition problems. Particle size distribution, roundness, and sphericity can be obtained using the system with a deviation of repeated precision of around ±1%. The developed system is shown to be also convenient and versatile for any particle size and shape for academic and industrial users.

Effect of atmospheric parameters on fine particulate concentration in suburban Shanghai

A study was conducted on the effect of atmospheric parameters, including temperature, wind speed, and relative humidity, on fine particulate mass concentrations measured in Jiading District of Shanghai, China, during the period from January 2009 to January 2010. A sensitivity analysis was applied to investigate the interaction between atmospheric parameters and particulate mass concentration. The experiment revealed that the concentration of particulates increased with particle size from 0.1 to 1.0 μm, and decreased with the increase of particle size from 1.0 to 2.5 μm. The effects of atmospheric parameters on fine mass concentrations were significantly particle size-dependent. The PM1.0-2.5 may come from the size increase of smaller particulates after moisture absorption, And the variation of concentrations of PM0.1-l.0 was mainly attributed to the accumulation of PM0.1. The ventilation index and dilution index were calcu- lated on the basis of data collected in December 2009. A correlation analysis indicated that there was a significant relation between these two indexes and the particulate concentration by examining the three particle size ranges, 0.0-0.1, 0.1-1.0, and 1,0-2.5 μm. The Spearman correlation coefficients that related the ventilation index to the concentration for the three particle size ranges were -0.45, -0.56 and -0.47, respectively, while the coefficients that related the dilution index to the concentration were -0.36, -0.42 and -0.45, respectively.