Unmanned Aircraft System Path Planning for Visually Inspecting Electric Transmission Towers

To detect faults on the power transmission and distribution systems, current electric utilities perform a visual inspection by dispatching line crews and helicopters. This practice has disadvantages such as high operation costs and safety concerns. To resolve these issues, power utilities are considering the use of an unmanned aircraft system (UAS). In this paper, we formulate an optimization model to find an efficient flight path for a UAS for visually inspecting a transmission tower. The objective of the model is to maximize a function involving three performance ratios, namely, flight time, image quality, and tower coverage. The optimization model is non-linear, non-differentiable, and multi-modal. We solve the problem by using a particle swarm optimization (PSO) based-algorithm and a simulated annealing (SA) based-algorithm and compare their results. We test the model under three inspection strategies. The experimental results show that the PSO-based algorithm outperforms the SA-based algorithm. They also show that the proposed model can provide a flight path that comprises a good balance over the three performance ratios.

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