Vision system and three-dimensional modeling techniques for quantification of the morphology of irregular particles

Lyndon N. Smith; Melvyn L. Smith

doi:10.1117/12.403785

11 October 2000 Vision system and three-dimensional modeling techniques for quantification of the morphology of irregular particles

Lyndon N. Smith, Melvyn L. Smith

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Proceedings Volume 4197, Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision; (2000) https://doi.org/10.1117/12.403785
Event: Intelligent Systems and Smart Manufacturing, 2000, Boston, MA, United States

Abstract

Particulate materials undergo processing in many industries, and therefore there are significant commercial motivators for attaining improvements in the flow and packing behavior of powders. This can be achieved by modeling the effects of particle size, friction, and most importantly, particle shape or morphology. The method presented here for simulating powders employs a random number generator to construct a model of a random particle by combining a sphere with a number of smaller spheres. The resulting 3D model particle has a nodular type of morphology, which is similar to that exhibited by the atomized powders that are used in the bulk of powder metallurgy (PM) manufacture. The irregularity of the model particles is dependent upon vision system data gathered from microscopic analysis of real powder particles. A methodology is proposed whereby randomly generated model particles of various sized and irregularities can be combined in a random packing simulation. The proposed Monte Carlo technique would allow incorporation of the effects of gravity, wall friction, and inter-particle friction. The improvements in simulation realism that this method is expected to provide would prove useful for controlling powder production, and for predicting die fill behavior during the production of PM parts.

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Lyndon N. Smith and Melvyn L. Smith "Vision system and three-dimensional modeling techniques for quantification of the morphology of irregular particles", Proc. SPIE 4197, Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision, (11 October 2000); https://doi.org/10.1117/12.403785

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KEYWORDS

Particles

Monte Carlo methods

3D modeling

Optical spheres

Visual process modeling

Computer simulations

Phase modulation

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