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dc.creatorQin, J.
dc.creatorWang, S.
dc.creatorChan, C.
dc.creatorXiao, F.
dc.date.accessioned2007-05-07T20:46:39Z
dc.date.available2007-05-07T20:46:39Z
dc.date.issued2006
dc.identifier.otherESL-IC-06-11-186
dc.identifier.urihttp://hdl.handle.net/1969.1/5333
dc.description.abstractThis paper presents a fault detection and diagnosis (FDD) strategy based on system knowledge, qualitative states and object-oriented statistical process control (SPC) models for typical pressure-independent variable air volume (VAV) air-conditioning systems. Eight FDD schemes are built to detect the eleven pre-defined VAV faults using the qualitative and quantitative FDD approaches within the strategy at two steps. The ten hard faults, which would affect the system operation, are analyzed at Step 1. The soft fault, which would not affect the basic system operation but would impact the supervisory controls, is analyzed at Step 2. The strategy is tested and validated on typical VAV systems involving multiple faults, both in simulation and in-situ tests. A software package is developed as a BMS-assisted automatic commissioning tool based on the FDD strategy. Off-line tests were conducted in both the simulated building and the real building.en
dc.format.extent273942 bytesen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherEnergy Systems Laboratory (http://esl.tamu.edu)
dc.publisherTexas A&M University (http://www.tamu.edu)
dc.subjectfault detection and diagnosisen
dc.subjectvariable air volumeen
dc.subjectstatistical process controlen
dc.subjectqualitative and quantitative reasoningen
dc.titleCommissioning and Diagnosis of VAV Air-Conditioning Systemsen


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