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Non-Spherical 2-Dimensional Particle Size Analysis from Chord Measurements using Bayers' Theorem

机译:基于贝叶斯定理的弦测量的非球形二维粒度分析

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摘要

A method of deconvoluting 2-dimensional particle size distributions chord size data is presented and evaluated. This is the probability Apportioning Method (PAM3). It assumes that the particles (or droplets) can be represented by super quadrics and are cut randomly by a sensor to give a chord measurement. Starting from an assumed uniform particle distribution. Bayes' theorem is used to calculate hit probabilities for each particle type and the population is then recalculated. The process is then repeated until there its there is no significant further change in the calculated distribution. Using numerical simulations PAM3 is shown to be quite accurate and robust for a number of different types of particle shapes provided there is a sufficient number of accurate measurements.
机译:提出并评估了二维颗粒尺寸分布弦尺寸数据的卷积方法。这是概率分配方法(PAM3)。假设粒子(或液滴)可以用超二次曲面表示,并被传感器随机切割以进行和弦测量。从假定的均匀颗粒分布开始。贝叶斯定理用于计算每种粒子类型的命中概率,然后重新计算总体。然后重复该过程,直到计算出的分布没有明显的进一步变化为止。使用数字模拟显示,PAM3对于许多不同类型的颗粒形状非常准确且稳定,只要有足够数量的精确测量即可。

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