An Improved Method for Power-Line Reconstruction from Point Cloud Data

Bo Guo,Chisheng Wang,Qingquan Li,Xianfeng Huang

doi:10.3390/rs8010036

Abstract

This paper presents a robust algorithm to reconstruct power-lines using ALS technology. Point cloud data are automatically classified into five target classes before reconstruction. In order to improve upon the defaults of only using the local shape properties of a single power-line span in traditional methods, the distribution properties of power-line group between two neighbor pylons and contextual information of related pylon objects are used to improve the reconstruction results. First, the distribution properties of power-line sets are detected using a similarity detection method. Based on the probability of neighbor points belonging to the same span, a RANSAC rule based algorithm is then introduced to reconstruct power-lines through two important advancements: reliable initial parameters fitting and efficient candidate sample detection. Our experiments indicate that the proposed method is effective for reconstruction of power-lines from complex scenarios.

Highlights

The safety of power-line infrastructure significantly affects our everyday life and industrial activities
In order to overcome these faults, we introduce an improved method based on RANdom SAmple Consensus (RANSAC) rule, which is an iterative method to estimate the parameters of a mathematical model from a set of observed data that contains a number of outliers, resulting in robustly reconstructed power-line spans
The method was mainly based on RANSAC algorithm

Summary

Introduction

The safety of power-line infrastructure significantly affects our everyday life and industrial activities. Automating the monitoring of high-voltage transmission lines is of importance to power utility companies [1]. There are two components of the automated monitoring methodology: detection of potential hazards, such as encroaching vegetation [2,3], and the analysis of power-line structural stability. An important consideration when reconstructing 3D power-lines is to assert that the physical parameters of the cable are still within a safe margin while quickly detecting anomalies or defects [4]. An algorithm to reconstruct individual spans using ALS is introduced in this paper to model the sag of individual spans, or to compute its parameters

Results

Discussion

Conclusion