Date of Submission
Master of Science in Mechanical Engineering
Mechanical and Industrial Engineering
Dr. Ravi Gorthala
Dr. Maria-Isabel Carnasciali
Dr. Cheryl Li
Automated fault detection and diagnosis (AFDD), HVAC&R systems, Rooftop units (RTU's)
Heating and ventilation, Air conditioning, Refrigeration and refrigerating machinery
In today’s building sector, human thermal comfort is one of the top requirements. Some form of heating, ventilation, air-conditioning, and refrigeration (HVAC&R) systems can be found in every supermarket, office building, home, and automobile. In commercial buildings alone, rooftop units (RTU’s) make up more than 60% of the cooling systems. The unfortunate reality, however, is that although they are supposed to be efficient, most if not all units have at least one or more faults such as incorrect refrigerant charge, valve leakage, fouled condenser/evaporator, and expansion valve faults, to name a few. To make matters worse, these faults are often never detected or not detected until a major malfunction or equipment failure occurs. One solution is implementing automated fault detection and diagnosis (AFDD) tools. AFDD serves as a monitoring tool that constantly monitors a HVAC unit’s performance variables and detects anomalies in the sensed data which are then processes and sent to building owners as “faults” with potential diagnosis. FDD tools incorporate both retro-commissioning and continuous commissioning to be able to detect problems within a system early, and therefore increase the life and health of an RTU while decreasing energy consumption. Previous studies have determined that the HVAC sector has 24% potential savings, ranking it second after lighting for equipment energy savings. Additionally, a report done by TIAX has shown that annual energy savings as high as 140 trillion BTU can be achieved by AFDD for RTU’s alone. There has been a push to implement these tools in order to achieve net zero energy buildings. Several commercial AFDD technologies exist and are available on the market. However, their technical performance has not been verified in the field. Additionally, utility companies that offer incentives for energy efficient technologies aren’t equipped to evaluate and support these AFDD technologies. This thesis serves as the first ever largescale field testing and evaluation of AFDD tools for determining their technical performance. The scope of this includes the development of a specification for the evaluation and selection of AFDD products to be verified, the development of a site selection criteria to assist with site host requirements, the development of a measurement and verification plan, installation, and baseline evaluation of AFDD products at 5 demonstration sites.
Hacker, Annika, "Field Testing of Automated Fault Detection And Diagnosis (AFDD) Tools For Commercial Rooftop Heating, Ventilation, Air-conditioning, and Refrigeration Systems" (2019). Master's Theses. 174.
Available for download on Saturday, January 15, 2022
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