| 基于主元分析法的冷水机组传感器故障检测效率分析 |
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| 引用本文： | 胡云鹏,陈焕新,周诚,杨小双,徐荣吉.基于主元分析法的冷水机组传感器故障检测效率分析[J].化工学报,2012,0(Z2):85-88. |
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| 作者姓名： | 胡云鹏 陈焕新 周诚 杨小双 徐荣吉 |
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| 作者单位： | 1. 华中科技大学环境科学与工程学院, 湖北 武汉 430074;
2. 北京建筑工程学院 供热供燃气通风及空调工程北京市重点实验室, 北京 100044 |
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| 基金项目： | “十一五”国家科技支撑计划项目(2008BAJ12B03);供热供燃气通风及空调工程北京市重点实验室研究基金资助课题(NR2012K06);2010年度湖北省建设科技项目;2011年度湖北省建设科技项目~~ |
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| 摘 要： | 冷水机组是一个高度非线性的复杂系统,其自控系统传感器故障会导致冷水机组的运行偏离正常状态和能耗浪费。采用冷水机组正常运行数据,通过多元统计方法中的主元分析法建立训练矩阵,利用平方预测误差进行故障分析工作。引入不同程度故障,分析主元分析法的检测效率。结果表明,主元分析法故障检测效果明显,但对于不同传感器的不同程度故障,故障检测的误判率存在一定的差异。
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| 关 键 词： | 冷水机组 故障检测 主元分析 检测效率 |
| 收稿时间： | 2012-09-29 |
| 修稿时间： | 2012-10-11 |
Analysis of sensor fault detection in chiller based on PCA method |
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| HU Yunpeng,CHEN Huanxin,ZHOU Cheng,YANG Xiaoshuang,XU Rongji.Analysis of sensor fault detection in chiller based on PCA method[J].Journal of Chemical Industry and Engineering(China),2012,0(Z2):85-88. |
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| Authors: | HU Yunpeng CHEN Huanxin ZHOU Cheng YANG Xiaoshuang XU Rongji |
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| Affiliation: | 1. School of Environmental Science and Engineering, Huazhong University of Science & Technology, Wuhan 430074, Hubei, China;
2. Beijing Key Laboratory of Heating, Gas Supply, Ventilating and Air Conditioning Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China |
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| Abstract: | Chiller is a highly nonlinear complex system.The sensor fault in the automation system of chiller will cause it to operate in unmoral situation and waste energy.Based on the principal component analysis(PCA)method,one of the analytical methods in multivariate statistics,the data in normal condition have been used to establish the train matrix.The square prediction error(SPE)has been used to analyze the sensor fault.The detection efficiency has been analyzed by the PCA method with introducing different level faults into the chiller.The result shows that PCA-based fault detection method works well,but the fault detection efficiencies of different sensors with different level faults are inconsistent. |
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| Keywords: | chiller fault detection principal component analysis detection efficiency |
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