Conference Publication Details
Mandatory Fields
Bruton, K.; Coakley, D.; O'Donovan, P.; Keane, M.; O'Sullivan, D.
ICEBO - International Conference for Enhanced Building Operations
Development of an Online Expert Rule Based Automated fault Detection and Diagnostic (AFDD) Tool for Air Handling Units: Beta Test Results
Optional Fields
Heating Ventilation and Air Conditioning (HVAC) system energy consumption accounts for an average of 40% of an industrial sites energy consumption. Studies have indicated that 20 - 30% energy savings are achievable by recommissioning Air Handling Units (AHU) in HVAC systems to rectify faulty operation. Studies have also demonstrated that continuous commissioning of building systems for optimum efficiency can yield savings of an average of over 20% of total energy cost. Automated Fault Detection and Diagnosis (AFDD) is a process concerned with automating the detection of faults and their causes in physical systems. AFDD can help support multiple stages in the commissioning process. This paper outlines the development of an AFDD tool for AHU's using expert rules then details the results of its beta testing phase on twenty-six AHU's across six large commercial & manufacturing sites. To date, validated energy savings of over 157,000 have been identified by the AFDD tool.
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