Model based object recognition for particle size distribution

S. Priadarsini, S. Ganesan, C. Shanthi, N. Pappa
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引用次数: 1

Abstract

In Aerospace applications, Ammonium Nitrate, Ammonium dichromate [(NH4)2 Cr2 O7] and Hydroxy-Terminator PolyButadiene (HTPB) are used as solid propellants. Ammonium dichromate must be pulverized and used in rockets which play the major role to improve the burn rate of the fuel. Image Processing based techniques are used to measure the particle size of Ammonium dichromate. If the particle is overlapped its size or shape can't be accurately measured. Hence, overlap of the particle is determined and its size can be measured. This paper deals with the estimation of the area of Ammonium dichromate particles. An intimate approach to overcome overlap in the particles is done using the Gaussian process regression model. The prediction is done by using linear function of the observed values and these functions can be computed quickly using recursive formulas. Gaussian process regression model is employed to determine the multiple overlap of the particles.
基于模型的物体粒度分布识别
在航空航天应用中,硝酸铵,重铬酸铵[(NH4)2 Cr2 O7]和羟基终结者聚丁二烯(HTPB)被用作固体推进剂。重铬酸铵必须粉碎并用于火箭,这对提高燃料的燃烧速度起着重要作用。基于图像处理的技术被用于测量重铬酸铵的粒度。如果粒子重叠,其大小或形状就不能精确测量。因此,确定了粒子的重叠,并可以测量其大小。本文讨论了重铬酸铵粒子面积的估计问题。利用高斯过程回归模型,提出了一种克服粒子重叠的方法。利用观测值的线性函数进行预测,这些函数可以用递归公式快速计算。采用高斯过程回归模型确定粒子的多重重叠。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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