Feedback Control of Crystal Characteristics Based on Deep Learning Image Analysis

被引：0

作者：

Wang, Liang-Yong ^{[1
]}

Zhu, Yao-Long ^{[1
]}

Gan, Chen-Yang ^{[1
]}

机构：

[1] State Key Laboratory of Integrated Automation for Process Industry, Northeastern University, Shenyang,110819, China

来源：

Dongbei Daxue Xuebao/Journal of Northeastern University | 2022年 / 43卷 / 12期

关键词：

Cooling crystallization - Crystal characteristics - Crystal-size - Feedback control methods - Image-analysis - On-line controls - Online feedback - Online feedback control - Path tracking - Standard deviation;

D O I：

10.12068/j.issn.1005-3026.2022.12.003

中图分类号：

学科分类号：

摘要：

Aiming at the online control of crystal size expectation and standard deviation characteristics, an online feedback control method based on deep learning image analysis is proposed. Firstly, the crystal image analysis method using deep learning neural network is introduced to analyze the shape and size of crystals online. Then, mathematical statistical analysis is performed to obtain the size expectation and standard deviation of a certain batch of crystals. Finally, a feedback controller combining path tracking algorithm and PID algorithm is designed to deal with under-input characteristics, so that the target size expectation and standard deviation is obtained. The effectiveness and feasibility of the proposed method is verified by the alum cooling crystallization experiment. © 2022 Northeastern University. All rights reserved.

引用

页码：1688 / 1693

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