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	A diagnostic tool for online sensor health monitoring in air-conditioning systems
	Xiao, Fu ; Wang, Shengwei ; Zhang, Jianping
	2010-05-11 ; 2010-05-11
关键词	sensor fault fault detection fault diagnosis principal component analysis air-handling unit building automation system PRINCIPAL COMPONENT ANALYSIS FAULT-DIAGNOSIS PCA Construction & Building Technology Engineering, Civil
中文摘要	Healthy sensors are essential for the reliable monitoring and control of building automation systems (BAS). This paper presents a diagnostic tool to be used to assist building automation systems for online sensor heath monitoring and fault diagnosis of air-handling units. The tool employs a robust sensor fault detection and diagnosis (FDD) strategy based on the Principal Component Analysis (PCA) method. Two PCA models are built corresponding to the beat balance and pressure-flow balance of an air-handling process. Sensor faults are detected using the Q-statistic and diagnosed using an isolation-enhanced PCA method that combines the Q-contribution plot and knowledge-based analysis. The PCA models are updated using a condition-based adaptive scheme to follow the normal shifts in the process due to changing operating conditions. The sensor FDD strategy, the implementation of the diagnostic tool and experimental results in an existing building are presented in this paper. (C) 2005 Elsevier B.V. All rights reserved.
语种	英语 ; 英语
出版者	ELSEVIER SCIENCE BV ; AMSTERDAM ; PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/27121]
专题	清华大学
推荐引用方式 GB/T 7714	Xiao, Fu,Wang, Shengwei,Zhang, Jianping. A diagnostic tool for online sensor health monitoring in air-conditioning systems[J],2010, 2010.
APA	Xiao, Fu,Wang, Shengwei,&Zhang, Jianping.(2010).A diagnostic tool for online sensor health monitoring in air-conditioning systems..
MLA	Xiao, Fu,et al."A diagnostic tool for online sensor health monitoring in air-conditioning systems".(2010).

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