Affiliation of Author(s):University of Connecticut

Journal:in Proceedings of 2013 IEEE Conference on Automation Science and Engineering

Funded by:Innovations in Emerging Frontiers of School of Engineering of University of Connecticut

Key Words:HVAC, fault detection, SPC, unscented Kalman filter, model error

Abstract:Buildings account for about 40% of energy
consumption in the U.S. The Heating, Ventilation and Air
Conditioning (HVAC) systems account for 57% of energy used
in commercial and residential buildings in the U.S., and between
4% and 20% of HVAC energy is wasted because of sudden faults
and component degradation. To reduce energy consumption and
improve occupancy comfort, HVAC fault detecting is important.
In our recent work, a synergistic integration of Kalman Filter
and Statistical Process Control (SPC) was used for fault
detection of chillers based on a gray-box model. This paper
builds on that

All the Authors:Biao Sun,Peter B. Luh

First Author:Ying Yan

Indexed by:Journal paper

Discipline:Engineering

First-Level Discipline:Control Science and Engineering

Document Type:C

Translation or Not:no

Date of Publication:2013-05-07

Included Journals:SCI

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