|本期目录/Table of Contents|

[1]徐洪华,田迎华.RBF神经网络在锅炉安全液位控制中的应用[J].中国安全生产科学技术,2011,7(8):170-174.
　XU Hong-hua,TIAN Ying-hua.Safety level control of industrial boiler on RBFNN[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2011,7(8):170-174.
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RBF神经网络在锅炉安全液位控制中的应用()
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
7
期数:
2011年8期
页码:
170-174
栏目:
职业安全卫生管理与技术
出版日期:
2011-08-30

文章信息/Info

Title:
Safety level control of industrial boiler on RBFNN
文章编号:
1673-193X(2011)-08-0170-05
作者:
徐洪华； 田迎华；
长春理工大学计算机科学技术学院；
Author(s):
XU Hong-hua; TIAN Ying-hua
School of Computer Science and Technology,Changchun University of Science and Technology,Changchun 130022,China
关键词:
锅炉;  安全;  鲁棒性;  自动控制;  神经网络
Keywords:
boiler;  safety;  robustness;  automatic control;  neural network
分类号:
X933.2
DOI:
-
文献标志码:
A
摘要:
锅炉是现代工业过程中不可缺少的动力设备,在工业锅炉的自动化控制过程中,蒸汽锅炉的给水调节是其控制过程的重要任务。结合锅炉安全液位控制过程的影响因素,文中分析了给水流量作用下的动态特性、蒸汽流量作用下的动态特性和炉膛热负荷作用下的动态特性,提出了基于径向基神经网络PID的分段式锅炉液位控制策略。控制策略中采用的高斯函数的径向基神经网络算法,实现了系统参数智能化自动调整;分段式控制方法有效地提高了系统的调节精度和响应速度。该控制策略的实际应用,对实现工业控制过程自动化,提高系统控制品质和保证生产过程安全具有重要意义。 更多还原
Abstract:
Boiler is indispensable power equipment in industrial process.During the automatic control process of industrial boiler,the water supply regulation of steam boiler is an important task in control process.With influential factors in the control process of boiler safety liquid level,this paper analyzes the dynamic features of feed-water flow,steam flow and furnace load and puts forward the segmentation boiler level PID control strategy based on neural network.Gaussian radial basis function neural network algorithm adopted in the control strategy realizes intelligently automatic regulation of parameters.Segmental control method can effectively increase the regulation accuracy of the system and its response speed.The actual application of the control strategy bears important meaning in realizing automatic control,in providing control quality and also in securing production safety. 更多

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期：2011-03-09
基金项目：吉林省科技支撑重点攻关项目(编号20090307)
更新日期/Last Update: