基于CNN视频的煤浮泡控制系统

1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI:10.1109/CNNA.1998.685362

L. Jeanmeure, W.B.J. Zimmerman

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引用次数: 6

摘要

研究了煤浮泡过程监控系统的设计。该系统基于阻力的流体动力学模型和一个由图像处理应用程序组成的反馈回路，该应用程序负责从泡沫的视频图像中提取相关参数。本文讨论了CNN技术在原型控制系统设计中的应用。给出了实现的低级图像处理方法的描述，并对使用细胞神经网络范例等新技术设计原型控制系统时遇到的问题进行了评论。

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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A CNN video based control system for a coal froth flotation

The design of a control system to monitor a coal froth flotation process is considered. This system is based upon a hydrodynamic model for the resistance and a feedback loop consisting of an image processing application that is responsible for extracting relevant parameters from a video image of the froth. This paper deals with the application of the CNN technology in the design of a prototype control system. A description of the low level image processing methods implemented is given as well as comments on the problems encountered during the design of a prototype control system using a new technology such as the cellular neural network paradigm.

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来源期刊

1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)

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