实时预测颗粒流动特性的虚拟传感器的研制。

Rexonni B Lagare, Mariana Araujo da Conceicao, Ariana Camille Acevedo Rosario, Katherine Leigh Young, Yan-Shu Huang, M Ziyan Sheriff, Clairmont Clementson, Paul Mort, Zoltan Nagy, Gintaras V Reklaitis
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引用次数: 2

摘要

我们报告了一项正在进行的开发流动性虚拟传感器的工作进展,这是实现造粒线实时过程监控的关键工具。该传感器基于相机成像来测量湿造粒产生的颗粒的大小和形状分布。然后,使用统计方法将其与流动性测量(如环剪试验、排水休止角、动态休止角和攻丝密度)相关联。虚拟传感器解决了流动性测量的问题,这些测量基于离线表征方法,可能需要数小时才能完成。通过基于实时测量方法的虚拟传感器,颗粒流动性的预测变得更快,从而可以及时做出有关过程控制和供应链的决策。
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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Development of a Virtual Sensor for Real-Time Prediction of Granule Flow Properties.

We report progress of an ongoing work to develop a virtual sensor for flowability, which is a critical tool for enabling real time process monitoring in a granulation line. The sensor is based on camera imaging to measure the size and shape distribution of granules produced by wet granulation. Then, statistical methods were used to correlate them with flowability measurements such as ring shear tests, drained angle of repose, dynamic angle of repose, and tapped density. The virtual sensor addresses the issue with these flowability measurements, which are based on off-line characterization methods that can take hours to perform. With a virtual sensor based on real-time measurement methods, the prediction of granule flowability become faster, allowing for timely decisions regarding process control and the supply chain.

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