Abstract
Airborne LiDAR has been traditionally used for power line cruising. Nevertheless, data acquisition with airborne LiDAR is constrained by the complex environments in urban areas as well as the multiple parallel line structures on the same power line tower, which means it is not directly applicable to the extraction of urban power lines. Vehicle-borne LiDAR system has its advantages upon airborne LiDAR and this paper tries to utilize vehicle-borne LiDAR data for the extraction of urban power lines. First, power line points are extracted using a voxel-based hierarchical method in which geometric features of each voxel are calculated. Then, a bottom-up method for filtering the power lines belonging to each power line is proposed. The initial clustering and clustering recovery procedures are conducted iteratively to identify each power line. The final experiment demonstrates the high precision of this technique.
Highlights
Power lines are important components of the power sector and their monitoring has significant roles in various areas, such as power line patrols [1], electric net design and upgrading [2], and the professional analysis of electricity [3]
The peak interval corresponds to the non-power line points and the others correspond to the power line points for the following reasons: (1) In a grid there may be just few points, such as one or two points, in this case they may not be filtered using above single voxel filtering method; (2) Such situations are extremely common in the point cloud
The power line points acquired by vehicle-borne LiDAR system exhibit a dense breakage-dense distribution pattern, so the intensively distributed points can be clustered initially based on their point distance
Summary
Power lines are important components of the power sector and their monitoring has significant roles in various areas, such as power line patrols [1], electric net design and upgrading [2], and the professional analysis of electricity [3]. Jwa et al [12] used the Hough transform, feature eigenvectors, and point density in a comprehensive approach to extract power line points, and a piecewise catenary curve model-growing algorithm was proposed to identify the points in each power line Based on this method, Jwa and Sohn [13] conducted an experiment using a high density point cloud, which was acquired at a height of 120 m, and good results were obtained. Based on a height constraint and the Hough transform, they extracted power line points and fitted the power lines using a parabolic function This experiment showed that it is feasible to use vehicle-borne LiDAR data for detecting and inspecting power lines. Based on the extracted power line points, a bottom-up method is introduced for the identification of points belonging to each power line
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