M.Sc. Tezi Görüntüleme

      The periodic monitoring of energy lines to lessen the impacts of threats and to destroy the potential risks against the Power Transmission Lines (PTL) is highly important. The risks can involve natural causes (vegetation, landslides, trees, avalanches, storms etc.) on one hand and the human factor (constructions and buildings breaking the safety distance, dumping the excavated material, theft etc.) on the other hand. In this study, an algorithm, which can automatically detect PTLs wires and pylons using the LIDAR data, is developed. Specific safety distances are also spatially analyzed and the existence of risky ground objects is examined with the help of the detected PTLs. In the newly developed algorithm, ground points are located and the low object points in vertical distance to these ground points are eliminated using the Cloth Simulation Filtering (CSF) method. The remaining point cloud is separated into voxels of 3x3x3 m in size. In the search of 26 neighbour voxels; starting from automatically determined seed voxel, final detection of wire and pylons has been determined by the algorithm of ‘concave hull’ after their straight slopes which are fitted by height values variant and RANSAC were analysed. Periodic applications on the basis of the proposed approach will make it easy to monitor and maintain PTLs component (wires and pylons) without topographic works.