Demonstrating a novel proactive fault detection and diagnosis method for air handling units in case study buildings
Air handling units (AHUs) connect primary heating/cooling plants with building zones. They contribute a significant portion to the energy consumption in heating, ventilation and air conditioning (HVAC) systems of buildings. Large varieties of faults in AHUs could lead to uncomfortable indoor environment, poor indoor air quality, occupant complains and energy waste. The automated fault detection and diagnosis (FDD) tools are useful to alarm faults and then identify faults timely. There is still a lack of effective methods for diagnosing AHU faults automatically. This project aims to demonstrate a novel proactive FDD method proposed by the supervisor.
General project problem description
Methodology; A major barrier of AHU FDD is that there are usually not enough sensors equipped in AHUs. The basic idea of proactive FDD is to make proactive activities in AHU to get more useful information. The fans, valves and dampers can be controlled in proactive way to get more information to make FDD. For instance, if the valve of heating coil is stuck, the supply air temperature will be not affected if the control signals of the heating coil valve is changed significantly.
A set of proactive actions have been proposed by the supervisor. The participants will conduct faults and then process these proactive actions in the AHU in different case study buildings.
Expected Outputs; Experiment data of each proactive action. The demonstration will be a part of a SCI journal paper. Participants will be co-authors if the contributions are significant. It is expected that the participants will learn a lot about AHU, controls, PID logic, as well as air distribution systems in buildings.
