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An Innovation-Based Methodology for HVAC System Fault Detection
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1985
Year
Fault DiagnosisReliability EngineeringEngineeringFault EstimationSmart GridEnergy ManagementAir Handler UnitDiagnosisComputer EngineeringBuilding AutomationSystems EngineeringExtended Kalman FilterNonlinear Mathematical ModelInnovation-based MethodologyFault DetectionAutomatic Fault DetectionControl SystemsPower Systems
Although Energy Management and Control Systems (EMCS) have since the early 1970’s contributed significantly to the reduction (20-40 percent) of energy use in buildings without sacrificing occupants’ comfort, their full capabilities have not been completely realized. This is in part due to their inability to quickly detect and compensate for failures in the Heating, Ventilation and Air Conditioning (HVAC) system. In fact, no matter how good the control scheme for the HVAC system might be, the presence of undetected faults can completely offset any expected savings. This paper presents a methodology for detecting faults in an HVAC system using a nonlinear mathematical model and an extended Kalman filter. The technique was implemented in a computer program and successfully used to detect “planted” faults in simulations of the air handler unit of an HVAC system. Test results are presented to demonstrate the effectiveness of the methodology.