A Proactive Fault Detection and diagnosis method for air handling unit
Objective: 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.
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 signal the heating coil valve is changed
significantly. The schematic diagram of a general AHU is as shown in Figure 1.
Return air
Exhaust air
Re-circulation
air
T Temperature sensor
P Pressure sensor
F Flow rate sensor
H Humidity sensor
H
C
Fresh air
C
T H
T
Supply air
C
T ΔP
F T P
Air handling controller
Figure 1. Schematic diagram of a general air handling unit
Experiment Design: 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 the
laboratory in 2/F, Vertigo, Tu/e.
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.
Required Participants: About 1-3 master students.
Supervisor:
Dr. Y. (Yang) Zhao
Postdoc researcher
Unit Building Physics and Services
Department of the Built Environment
Y.Zhao.1@tue.nl