期刊
CHEMICAL ENGINEERING SCIENCE
卷 64, 期 1, 页码 9-19出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ces.2008.09.007
关键词
Particulate processes; Particle size; Imaging; Multivariate statistics; Segmentation; Signature curve
Crystal size estimation from in situ images has received attention recently as a means to estimate product properties in real-time. In this paper, an automated image analysis strategy that combines classical image analysis techniques with multivariate statistics has been developed for online analysis of in situ images from crystallization process. The strategy introduces a novel image segmentation step based on information extracted from multivariate statistical models. Experimental results for batch cooling crystallization of monosodium glutamate show that the strategy effectively extracts crystal size and shape information from in situ images. The robustness and efficiency of the method has been established by comparing its performance with those obtained by manual analysis of the images. The method yields reasonably good estimates of particle length and is also fast enough to provide online measurements for the purpose of online optimization and control of a typical crystallization process. (c) 2008 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据