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Title: | INVESTIGATING ENERGY EFFICIENCY GAINS WITH FAULT DETECTION IN FAN COIL UNITS THROUGH PREDICTIVE AND PREVENTIVE MAINTENANCE | Authors: | RENA LEONG | Keywords: | Energy Efficiency Fault Detection Diagnostics (FDD) Air-conditioning and Mechanical Ventilation (ACMV) systems Fan Coil Units (FCU) Predictive Maintenance Energy Simulation and Building Analysis Smart Energy Management System EnergyPlus Design Builder |
Issue Date: | 2024 | Citation: | RENA LEONG (2024). INVESTIGATING ENERGY EFFICIENCY GAINS WITH FAULT DETECTION IN FAN COIL UNITS THROUGH PREDICTIVE AND PREVENTIVE MAINTENANCE. ScholarBank@NUS Repository. | Abstract: | This investigation explores the energy impacts and indoor air quality implications of undetected faults in Fan Coil Units (FCUs) within the Air-conditioning and Mechanical Ventilation (ACMV) systems. Through a case study approach, common faults are identified and prioritized for the implementation of fault detection diagnostics (FDD) solutions. Field investigations assess prevalent faults through correlational studies, followed by fault impact analysis using fault modeling techniques in energy simulation software. Key findings revealed significant impacts on fan power consumption due to dirty air filters. Additionally, the investigation discovered that although there was reduced cooling power consumption due to choked cooling coils, this also resulted in compromised occupant comfort and increased pump power consumption. This highlights the potential of FDD adoption in maintaining thermal comfort and optimizing energy efficiency. The investigation also suggests that implementing FDD in existing buildings would enable proactive fault detection, transitioning conventional preventive maintenance to a cost-effective, condition-based approach, and enhancing overall system performance while reducing energy wastage. The research was constrained by limited resources and time, leading to gaps in the field data collected from the case study and restricted features available in the fault simulation tool. Hence, these limitations may present opportunities for further refinement and optimization of research methodologies. | URI: | https://scholarbank.nus.edu.sg/handle/10635/249343 |
Appears in Collections: | Bachelor's Theses |
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Leong Yuan Ting Rena DBE_Rena Leong.pdf | 12.45 MB | Adobe PDF | RESTRICTED | None | Log In |
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