乔海晔.基于模糊神经网络的液体灌装自校正控制系统[J].包装工程,2018,39(3):206-210.
QIAO Hai-ye.Liquid Filling Self-tuning Control System Based on Fuzzy Neural Network[J].Packaging Engineering,2018,39(3):206-210. |
| 基于模糊神经网络的液体灌装自校正控制系统 |
| Liquid Filling Self-tuning Control System Based on Fuzzy Neural Network |
| 投稿时间：2017-09-04 修订日期：2018-02-10 |
| DOI：10.19554/j.cnki.1001-3563.2018.03.039 |
| 中文关键词: 微量灌装 二次补灌 模糊RBF神经网络 PLC ARM |
| 英文关键词: micro-filling secondary re-filling fuzzy RBF neural network PLC ARM |
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| 中文摘要: |
| 目的 为提高微量液体灌装精度，以补灌工序为研究对象，设计一种自校正控制系统。方法 介绍灌装机的基本结构、工艺流程以及自动补灌基本原理。基于模糊RBF神经网络设计一种二次补灌控制器，阐述神经网络结构和学习算法。基于PLC和ARM搭建相应控制系统，其中PLC为主控制器负责传感器信号检测以及各工序执行，ARM为从控制器负责二次补灌控制，最后进行试验研究。结果 对比结果表明，在自校正补灌的条件下，灌装精度得到明显提高，误差占比可控制在1%以下。结论 所述控制系统可最大程度地减小生产过程误差，满足灌装工艺要求。 |
| 英文摘要: |
| The work aims to improve the micro-liquid filling accuracy and design a self-tuning control system with re-filling process as research object. The basic structure, technological process as well as automatic re-filling principle of filling machine were introduced. A secondary re-filling controller based on fuzzy RBF neural network was designed. The neural network structure and learning algorithm were also expounded. A corresponding control system was constructed based on PLC and ARM. The PLC was main controller, and it was responsible for sensor signal detection and working procedure implementation. The ARM was subordinate controller, and it was responsible for secondary re-filling control. Finally, the experimental research was done. Comparison results showed that the filling accuracy was improved obviously and the error ratio could be controlled below 1%. The described control system can minimize the production process error and meet the technological requirements of the filling. |
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