Armin Hooman
Experimental analysis of fault impacts in AHU and development of a fault detection and diagnosis data-driven process.
Rel. Alfonso Capozzoli, Marco Savino Piscitelli. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Edile, 2024
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Abstract
The building sector accounts for up to 40% of the global energy demand and contributes 15 to 33% of greenhouse gas emissions globally, while HVAC systems comprise almost half of the buildings’ energy consumption and 10–20% of total energy consumption. Furthermore, it is estimated that HVAC systems could increase the consumption of these sectors by 15% ~ 30%. Ensuring fault-free operation of HVAC systems is difficult due to the complexity of the systems, complex interactions between HVAC systems, buildings and occupants, lack of proper maintenance, failure of components, or incorrect installation. In this context, Fault Detection and Diagnosis (FDD) approaches allow for the identification of faults or anomalous operational patterns in HVAC system components and the diagnosis of their root causes.
FDD is then crucial for promptly identifying and correcting faults that in complex systems such as AHUs, can lead to significant energy waste, shorter equipment life, occupant discomfort, poor indoor air quality (IAQ), and increased operating costs
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