Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8673
Title: A fault detection and diagnosis strategy of VAV air-conditioning systems for improved energy and control performances
Authors: Qin, J
Wang, S 
Keywords: Commissioning
Fault detection and diagnosis
Principal component analysis
Variable air volume system
VAV terminal
Issue Date: 2005
Publisher: Elsevier
Source: Energy and buildings, 2005, v. 37, no. 10, p. 1035-1048 How to cite?
Journal: Energy and buildings 
Abstract: This paper presents the results of a site survey study on the faults in variable air volume (VAV) terminals and an automatic fault detection and diagnosis (FDD) strategy for VAV air-conditioning systems using a hybrid approach. The site survey study was conducted in a commercial building. 20.9% VAV terminals were ineffective and 10 main faults were identified in the VAV air-conditioning systems. The FDD strategy adopts a hybrid approach utilizing expert rules, performance indexes and statistical process control models to address these faults. Supported by a pattern recognition method, expert rules and performance indexes based on system physical characteristics are adopted to detect 9 of the 10 faults. Two pattern recognition indexes are introduced for fault isolation to overcome the difficulty in differentiating damper sticking and hysteresis from improper controller tuning. A principal component analysis (PCA)-based method is developed to detect VAV terminal flow sensor biases and to reconstruct the faulty sensors. The FDD strategy is tested and validated on typical VAV air-conditioning systems involving multiple faults both in simulation and in situ tests.
URI: http://hdl.handle.net/10397/8673
ISSN: 0378-7788
EISSN: 1872-6178
DOI: 10.1016/j.enbuild.2004.12.011
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