USE OF A SPECTROSCOPIC SENSOR TO MONITOR DROPLET SIZE DISTRIBUTION IN EMULSIONS USING NEURAL NETWORKS
USE OF A SPECTROSCOPIC SENSOR TO MONITOR DROPLET SIZE DISTRIBUTION IN EMULSIONS USING NEURAL NETWORKS
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DOI：
10.1002/cjce.21861
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发表时间：
2014-02-01
影响因子：
2.1
通讯作者：
Guardani, Roberto
中科院分区：
文献类型：
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作者：
Assenhaimer, Cristhiane;Machado, Leandro J.;Guardani, Roberto
在许多应用中，如食品和药品或乳液聚合过程中，乳液性质的监测是重要的，因为老化和破碎的乳液性能较差，并可能影响产品质量。本研究报告使用一个在线的浊度传感器加上神经网络模型来监测金属加工液乳液（MWF）的液滴尺寸分布，乳液老化影响产品质量的情况。来自传感器的数据用于拟合用于液滴尺寸分布估计的模型。该技术被应用于监测市售MWF的不稳定性，具有良好的准确性。
Monitoring of emulsion properties is important in many applications, like in foods and pharmaceutical products, or in emulsion polymerisation processes, since aged and broken' emulsions perform worse and may affect product quality. This study reports the use of an in-line' turbidity sensor coupled with a neural network model to monitor droplet size distributions of metal working fluid emulsions (MWF), a case where emulsion aging affects product quality. The data from the sensor were used to fit the model for droplet size distribution estimation. The technique was applied to monitor the destabilisation of commercially available MWF with good accuracy.