Abstract
Unmanned aerial vehicles (UAVs) are an emerging and promising alternative for monitoring of transmission lines in terms of flexibility, complexity, working speed, and cost. One of the main challenges is to enable UAVs to become as autonomous as possible. A vital component toward this direction is the robust and accurate estimation of the UAV placement with respect to the transmission grid. This work faces this challenge by developing a transmission line autonomous tracking system, which allows the placement of a commercial drone over a transmission grid using a monocular camera. This feature provides accurate positioning for the vehicle even where the Global navigation satellite system (GNSS) signal is denied, enabling to report the status of transmission lines, at any time. The system isolates transmission grid conductors in each acquired RGB-image using an image-processing algorithm based on Hough transform, morphological operations, and Gabor filters. With this information, the system computes the location of the UAV using a geometric approach that relates transmission lines building parameter and optical geometry. However, it has the problem of gradual error accumulation when the drone moves. In this regards, the estimated position of the drone is computed by the maximum likelihood estimation (MLE) by the position information estimated by visual-system, the inertial measurement unit (IMU) and GNSS. The proposed positioning system showed an efficiency of 91.44% in field experimentation in the extraction of transmission conductor, with a root mean square the error of 0.18 m in the UAV localization.
Highlights
Inspection of power system assets—including conductors, protection systems, towers, transformers and other devices—plays an important role in addressing the growing need for sustainable energy worldwide
The model was wrapped with camouflage at the bottom to simulate the different objects which could be found in a transmission grid environment
The Unmanned aerial vehicles (UAVs) movement was simulated by a KUKA robotic arm model KR-6
Summary
Inspection of power system assets—including conductors, protection systems, towers, transformers and other devices—plays an important role in addressing the growing need for sustainable energy worldwide. Monitoring process is often neglected or shelved due to more pressing priorities, high deployment costs or industrial policies, which brings hardship to both unprepared businesses and society at large [3,4]. Within this context, the development of machinery based on autonomous robots, dedicated systems and intelligent machines, helps face the increasingly complex challenges within a rapidly expanding power industry [5], ensuring an efficient, cost-effective and safe maintenance process [6].
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