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Mandatory Fields
Reviews
Bruton, K;Raftery, P;Kennedy, B;Keane, MM;O'Sullivan, DTJ
2014
April
Review of automated fault detection and diagnostic tools in air handling units
Published
1
Optional Fields
HVAC SYSTEMS DECISION-SUPPORT ENERGY-CONSUMPTION MONITORING-SYSTEM BUILDING SYSTEMS DATA RECOVERY MODEL PART INFORMATION PROGNOSTICS
Studies have indicated that 20-30 % HVAC system energy savings are achievable by recommissioning air handling units (AHU) to rectify faulty operation. Studies have also demonstrated that on-going 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 be used to assist the commissioning process at multiple stages. This article presents a review of the research work that has been carried out on the use of AFDD tools in improving the efficiency of AHUs. This updates and expands upon the most recent literature review in this area, published in 2005. The article offers a comparative analysis of the FDD techniques currently in use and offers an opinion as to which show most potential for widespread adoption as part of the on-going commissioning process. It then details the issues which have impeded the adoption of existing AFDD tools for AHUs to date before concluding with an appraisal of current and recommended areas for future research to overcome the barriers to the widespread adoption of AFDD tools in AHUs.
DORDRECHT
SPRINGER
1570-646X
335
351
10.1007/s12053-013-9238-2
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