[1]吴 鹏,赵石磊,滕玉彬,等.一种改进型锅炉积灰监控模型[J].哈尔滨理工大学学报,2017,(05):30-34.[doi:10. 15938/j. jhust. 2017. 05. 006]
 WU Peng,ZHAO Shi-lei,TENG Yu-bin,et al.An Improved Monitoring Model of Boiler Ash Fouling[J].哈尔滨理工大学学报,2017,(05):30-34.[doi:10. 15938/j. jhust. 2017. 05. 006]
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一种改进型锅炉积灰监控模型()
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《哈尔滨理工大学学报》[ISSN:1007-2683/CN:23-1404/N]

卷:
期数:
2017年05期
页码:
30-34
栏目:
材料科学与工程
出版日期:
2017-12-30

文章信息/Info

Title:
An Improved Monitoring Model of Boiler Ash Fouling
文章编号:
1007-2683(2017)05-0030-05
作者:
吴 鹏 赵石磊 滕玉彬 潘启明 范长胜
1. 东北林业大学 机电工程学院,黑龙江 哈尔滨 150040; 2. 哈尔滨理工大学 软件学院,黑龙江 哈尔滨 150080
Author(s):
WU Peng ZHAO Shi-lei TENG Yu-bin PAN Qi-ming FAN Chang-sheng
1. College of Mechanical and Electronic Engineering,Northeast Forestry University,Harbin 150040,China; 2. School of Software,Harbin University of Science and Technology,Harbin 150080,China
关键词:
神经网络径向基函数递归正交最小二乘算法锅炉积灰
Keywords:
neural network radial basis function recursive orthogonal least squares boiler ash fouling
分类号:
TP391
DOI:
10. 15938/j. jhust. 2017. 05. 006
文献标志码:
A
摘要:
为改善锅炉吹灰的盲目性,基于改进的径向基函数神经网络递归正交最小二乘算法构建了工厂锅炉积灰预测的非线性模型,用来预测运行过程中锅炉各个受热面积灰程度。根据电厂锅炉实际运行情况,确定了多个特征变量来决定锅炉的工作状况。Matlab 仿真实验证明通过所建立的非线性模型,能有效预测出锅炉工作时受热面清洁状况下的吸热量,因此能够实时的反映受热面的积灰程度。
Abstract:
To improve the blindness of the boiler soot blowing,the nonlinear model of boiler ash fouling prediction based on improvement of radial basis function neural network (RBF NN) recursive orthogonal least squares (ROLS) algorithm was presented to predict the extent of the boiler heating area during operation. According to the actual operation of power plant boiler,multiple characteristic variables were determined to decide the boiler operating conditions. The Matlab simulation experiment proves the presented model can predict the heat absorption of the heat surface cleaning effectively,which can reflect the degree of the ash fouling of the heating surface in real time.

相似文献/References:

[1]周淼,陈孝明,黄海舟,等.电机电磁场问题的改进区域分解配点法求解[J].哈尔滨理工大学学报,2012,(03):10.
 ZHOU Miao,CHEN Xiao-ming,HUANG Hai-zhou,et al.Solving the Problem of Electromagnetic Fields Using Improved Domain Decomposition Combined RBF Mesh-free Method[J].哈尔滨理工大学学报,2012,(05):10.

更新日期/Last Update: 2017-11-15