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Assessing the Reliability of Particle Number Density Measurements Obtained by Image Analysis
Author(s) -
Larsen Paul A.,
Rawlings James B.
Publication year - 2009
Publication title -
particle and particle systems characterization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 56
eISSN - 1521-4117
pISSN - 0934-0866
DOI - 10.1002/ppsc.200701130
Subject(s) - dimensionless quantity , estimator , reliability (semiconductor) , particle (ecology) , particle number , particle density , enhanced data rates for gsm evolution , image (mathematics) , sampling (signal processing) , statistics , mathematics , algorithm , computer science , artificial intelligence , physics , computer vision , mechanics , thermodynamics , geology , power (physics) , oceanography , filter (signal processing) , volume (thermodynamics)
Particle number density measurements obtained by image analysis are biased by edge effects and particle overlap. This paper presents an estimator for particle number density that accounts for both edge effects and particle overlap. Using the output of advanced image analysis applied to artificial images, the estimator is shown to enable effective estimation of particle number density for monodisperse particulate systems at high densities. This paper also proposes a single dimensionless number that correlates with the reliability of the inferred PSD based on the likely number of overlaps per particle. As this dimensionless group becomes large, the degree of overlap and occlusion in the images makes image analysis difficult and unreliable. This parameter can aid practitioners in finding the proper sampling conditions to obtain accurate PSD measurements.