Optimized Control System Based on Artificial Neural Networks for Gas Suspension Calcination of Aluminum Hydroxide

刘代飞; 李劼; 陈湘涛; 丁凤其; 邹忠

您当前的位置：

首页 >

文章列表页 >

Optimized Control System Based on Artificial Neural Networks for Gas Suspension Calcination of Aluminum Hydroxide

更新时间：2026-09-14

- Optimized Control System Based on Artificial Neural Networks for Gas Suspension Calcination of Aluminum Hydroxide
- 基于神经网络的氢氧化铝焙烧优化控制系统
- Issue 2, Pages: 125-130(2008)
- 作者机构：
  
  1. 中南大学冶金科学与工程学院
  2. 中南大学信息科学与工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2008
- 稿件说明：
移动端阅览
刘代飞, 李劼, 陈湘涛, et al. Optimized Control System Based on Artificial Neural Networks for Gas Suspension Calcination of Aluminum Hydroxide[J]. 2008, (2): 125-130.
DOI：

刘代飞, 李劼, 陈湘涛, et al. Optimized Control System Based on Artificial Neural Networks for Gas Suspension Calcination of Aluminum Hydroxide[J]. 2008, (2): 125-130. DOI：

摘要

采用OPC(OLE for Process Control)技术架构了三层模式的过程优化控制系统

实现了优化控制系统与现有PLC系统的数据通讯、信息共享.优化控制系统由FLUENT仿真分析、过程智能建模、流程理论分析和优化控制四大模块组成.主要模块采用神经网络架构

实现复杂炉况的系统辩识以及工艺参数的优化计算.生产应用表明:该系统具有很好的指导性

能稳定生产、优化操作

为节能和降废的整体优化提供了新手段和途径.

Abstract

A three-layer optimized control system is constructed with OLE for process control(OPC) technology

by which the communication and information share between the optimization system and the existing PLC system are realized.In the optimization system

there are four parts of FLUENT simulating analysis

intelligent modeling

mass and energy balance analysis and optimized control.The system uses artificial neural networks(ANN) to identify the complex furnace conditions and to optimize process parameters.Applications indicate that the optimized system can stabilize production

optimize operation

save energy and reduce exhaust emission.

关键词

Keywords

references

梅炽,殷志云,周萍,等.现代炉窑的全息仿真[J].中南工业大学学报,1999,30(6):592-596.Mei Chi,Yin Zhiyun,Zhou Ping,et al.The hologram simulation of modern industrial furnace and kilns[J].Journalof Central South University of Technology,1999,30(6):592-596.(in Chinese)

暴瑞卿,李增录.OPC规范在现代煤矿应用中的程序实现[J].工矿自动化,2006(4):81-84.Pu Ruiqing,Li Zenglu.The program of OPC specification in modern coalmine application[J].Industry and MineAutomation,2006(4):81-84.(in Chinese)

Liu Honglin.A hybrid AI optimization method applied to industrial processes[J].Chemometrics and IntelligentLaboratory Systems,1999,45:101-104.

Simon Haykin.Neural Networks:A Comprehensive Foundation,2nd Edition[M].BEIJING:China Machine Press,2004.

雷鸣,尹申明,杨叔子.神经网络自适应学习研究[J].系统工程与电子技术,1994(3):19-27.Lei Ming,Yin Shenming,Yang Shuzi.The learning algorithm study of adaptive neural[J].System Eengineering andElectronics,1994(3):19-27.(in Chinese)

王耀南.模糊神经网络在炉温控制中的应用[J].系统工程与电子技术,1997(12):72-77.Wang Yaonan.Fuzzy neural network control for kiln temperature[J].Systems Engineering and Electronics,1997(12):72-77.(in Chinese)

Views

197

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Rule-Based Energy Management Strategy for Hybrid Electric Vehicles

Research on High⁃Precision Filtering Algorithm of Radiation Dosimeter

基于FLUENT的轮式两栖车辆航行阻力数值模拟

基于FLUENT的实尺度两栖车辆航行阻力的数值模拟

基于遗传算法的异步电机调速系统PID参数优化

Related Author

DENG Jichen

WANG Yaoxun

GUAN Quancai

LIU Yutao

WANG Yanhua

YAO Shuncai

WANG Jianfei

ZHANG Yanfei

Related Institution

School of Energy and Power Engineering， North University of China

China Research Institute of Radiation Protection

School of Electrical and Control Engineering, North university of China

中北大学机电工程学院

沈阳理工大学装备工程学院

⁰