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Thesis Defence: Comparative Analysis of Straight and Arbitrary Unmanned Aerial Vehicle Trajectory Planning for Corona Effect Detection on Powerlines
October 15 at 2:00 pm - 6:00 pm
Amirali Rahnama, supervised by Dr. Julian Cheng, will defend their thesis titled “Comparative Analysis of Straight and Arbitrary Unmanned Aerial Vehicle Trajectory Planning for Corona Effect Detection on Powerlines” in partial fulfillment of the requirements for the degree of Master of Applied Science in Civil Engineering.
An abstract for Amirali Rahnama’s thesis is included below.
Examinations are open to all members of the campus community as well as the general public. Please email Julian.Cheng@ubc.ca to receive the Zoom link for this exam.
Abstract
The integration of Unmanned Aerial Vehicles (UAVs) in power line inspections significantly improves efficiency and safety compared to traditional methods. This thesis explores optimizing UAV trajectories for detecting the Corona effect, characterized by ultraviolet (UV) emissions due to high-voltage discharges, which indicate potential faults in power transmission systems. The study compares the effectiveness of straight and spiral UAV trajectories using advanced algorithms to determine the most efficient inspection paths. Simulations conducted in MATLAB reveal that straight trajectories offer an estimation error as low as 0.22%, demonstrating better accuracy and efficiency for large-scale inspections. In contrast, spiral trajectories, while providing detailed data for specific areas, exhibit higher estimation errors, up to 10.31%, and are more resource-intensive. This research uniquely incorporates a mobile receiver in UAV simulations, allowing a dynamic and realistic assessment of UAV performance. The findings contribute to enhancing the reliability and safety of power lines by optimizing UAV trajectories for accurate fault detection, thereby improving maintenance protocols and preventing power outages. This thesis provides significant insights into the practical applications of advanced UAV technology and optimization algorithms in power line inspections.
