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Development of an Online Expert Rule Based Automated fault Detection and Diagnostic (AFDD) Tool for Air Handling Units: Beta Test Results
Date
2013Metadata
Show full item recordAbstract
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.
Citation
Bruton, K.; Coakley, D.; O'Donovan, P.; Keane, M.; O'Sullivan, D. (2013). Development of an Online Expert Rule Based Automated fault Detection and Diagnostic (AFDD) Tool for Air Handling Units: Beta Test Results. Energy Systems Laboratory (http://esl.tamu.edu); Texas A&M University (http://www.tamu.edu). Available electronically from https : / /hdl .handle .net /1969 .1 /151438.