| dc.description.abstract | In recent years, the use of UAVs has increased significantly, both for commercial and
private use. UAVs are particularly favorable in situations where other alternatives are impractical, or poses a threat to human lives, e.g. in search and rescue missions, or when
operating in polar regions. The use of UAVs in harsh conditions such as a cold and humid
environment, poses a major risk as ice can form on the aircraft surface. Ice accretion can
cause severe damage as it may result in reduced controllability, which in worst case can
cause the aircraft to crash. The wings are the parts of the UAV that is most vulnerable to
ice accretion, as they constitute a large surface towards the surroundings. This motivates
for an efficient and reliable ice detection application, to be used in de-icing systems.
This master thesis explores the possibilities of detecting ice formation, by the use of
temperature sensors and heating elements applied to the wings. The problem has been
addressed in two ways: The first method comprises of estimating the theoretical heat flux
on the surface, with the intention of being able to separate between a free surface, and a
surface covered with ice. The second method uses a least squares estimation model. By
using temperature measurements from experiments in an icing tunnel, the model estimates
an expression for both a free surface as well as a surface covered with ice.
The results from the use of least squares has given valuable information. Estimations
show that it is possible to detect icing based on temperature measurements, as temperature
fluctuations decrease when ice is present on the wings. To create a reliable and accurate
detection algorithm however, the model still needs to gather more measurements. A
continuation of this thesis should therefore primarily focus on that. | en |
