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基于PCA的火电厂湿法烟气脱硫系统的传感器故障诊断
引用本文:张丽萍,黄飞群,田丽玲,林心光.基于PCA的火电厂湿法烟气脱硫系统的传感器故障诊断[J].福州大学学报(自然科学版),2011,39(2):240-244.
作者姓名:张丽萍  黄飞群  田丽玲  林心光
作者单位:福州大学机械工程与自动化学院;华能福州电厂;
基金项目:福建省发改委产业技术开发资助项目(0803119)
摘    要:提出一种基于主元分析(PCA)的故障诊断方法,用于解决火电厂湿法烟气脱硫系统的传感器故障诊断问题.该方法利用PCA建立故障诊断模型,通过计算平方预报误差、传感器识别指数、故障重构值,对传感器故障进行检测、识别及恢复.利用华能福州电厂湿法烟气脱硫系统的采集数据进行传感器的完全失效、偏差、漂移与精度等级下降等4种类型故障的...

关 键 词:湿法烟气脱硫系统  传感器  故障诊断  主元分析  故障重构

Study on sensor fault diagnosis of wet flue gas desulfurization system in thermal power plant based on PCA
ZHANG Li-ping,HUANG Fei-qun,TIAN Li-ling,LIN Xin-guang.Study on sensor fault diagnosis of wet flue gas desulfurization system in thermal power plant based on PCA[J].Journal of Fuzhou University(Natural Science Edition),2011,39(2):240-244.
Authors:ZHANG Li-ping  HUANG Fei-qun  TIAN Li-ling  LIN Xin-guang
Institution:ZHANG Li-ping1,HUANG Fei-qun1,TIAN Li-ling1,LIN Xin-guang2(1.College of Mechanical Engineering and Automation,Fuzhou University,Fuzhou,Fujian 350108,China,2.Huaneng Fuzhou Power Plant,Fujian 350200,China)
Abstract:A fault diagnosis method using principal component analysis(PCA) is proposed to solve sensor fault diagnosis of wet flue gas desulfurization system in thermal power plant.Based on PCA model,the sensor faults are detected,identified and recovered by calculating square prediction error,sensor validation index,reconstruction index.Employing the actual data from wet flue gas desulfurization system of Huaneng Fuzhou power plant,the PCA model is proved effectively enough to detect and identify the complete invali...
Keywords:wet flue gas desulfurization system  sensor  fault diagnosis  principal component analysis  fault reconstruction  
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