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| 基于聚类的超闭球CMAC混煤燃烧污染物析出软测量模型 | |
| 引用本文： | 李慧,段培永,王桂荣,魏建平.基于聚类的超闭球CMAC混煤燃烧污染物析出软测量模型[J].仪器仪表学报,2011,32(5). |
| 作者姓名： | 李慧 段培永 王桂荣 魏建平 |
| 作者单位： | 1. 山东建筑大学可再生能源建筑利用技术省部共建教育部重点实验室,济南,250101 2. 山东建筑大学信息与电气工程学院,济南,250101 3. 山东建筑大学山东省建筑节能技术重点实验室,济南,250101 |
| 基金项目： | 国家自然科学基金面上项目，山东省自然科学基金项目，山东省科技攻关项目 |
| 摘 要： | 针对CMAC神经网络的网络节点随输入维数的增大呈几何级数增加的问题,基于模糊聚类提出一种改进的超闭球CMAC神经网络算法,用于电站锅炉混煤燃烧污染物析出软测量模型的建立.以电站锅炉实际运行工况的煤质特性数据和炉内燃烧条件为输入参数,通过软测量实现大型电站锅炉混煤燃烧硫、氮污染物生成浓度的精确预估和在线测量,用于指导电厂运行人员进行锅炉燃烧调整,以控制污染物的超标排放.与超闭球CMAC算法比较,提出的改进算法可以大大降低高维神经网络节点数并提高神经网络软测量精度,实验结果表明该方法的有效性和可行性. |
| 关 键 词： | 燃烧 污染物析出 CMAC神经网络 软测量 学习 混煤 |
Hyperball CMAC soft measuring model based on clustering for pollutant release from blended coal combusting |
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| Li Hui,Duan Peiyong,Wang Guirong,Wei Jianping.Hyperball CMAC soft measuring model based on clustering for pollutant release from blended coal combusting[J].Chinese Journal of Scientific Instrument,2011,32(5). | |
| Authors: | Li Hui Duan Peiyong Wang Guirong Wei Jianping |
| Affiliation: | Li Hui1,Duan Peiyong2,Wang Guirong3,Wei Jianping3(1 Key Laboratory of Renewable Energy Utilization Technologies in Buildings,Ministry of Education,Shandong Jianzhu University,Jinan 250101,China,2 School of Information and Electrical Engineering,3 Shandong Key Laboratory of Building Energy-saving Technique,China) |
| Abstract: | To overcome the drawback that CMAC neural network node number increases with the increasing of input dimensions exponentially,an improved hyperball CMAC neural network algorithm based on clustering is proposed to establish the soft measuring model for pollutant release from blended coal combusting in the boiler in power plant.The characteristic data of coal quality in practical boiler operating situation and the combusting condition in the furnace are taken as the input parameters.The soft measuring model w... |
| Keywords: | combustion pollutant release CMAC neural network soft measurement learning blended coal |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |