Power Pylon Reconstruction Based on Abstract Template Structures Using Airborne LiDAR Data

Abstract

As an important power facility for transmission corridors, automatic three-dimensional (3D) reconstruction of the pylon plays an important role in the development of smart grid. In this study, a novel three-dimensional reconstruction method using airborne LiDAR (Light Detection And Ranging) point cloud is developed and tested. First, a principal component analysis (PCA) algorithm is performed for pylon redirection based on the structural feature of the upper part of a pylon. Then, based on the structural similarity of a pylon, a pylon is divided into three parts that are inverted triangular pyramid lower structures, quadrangular frustum pyramid middle structures, and complex upper or lateral structures. The reconstruction of the inverted triangular pyramid structures and quadrangular frustum pyramid structures is based on prior knowledge and a data-driven strategy, where the 2D alpha shape algorithm is used to obtain contour points and 2D linear fitting is carried out based on the random sample consensus (RANSAC) method. Complex structures’ reconstruction is based on the priori abstract template structure and a data-driven strategy, where the abstract template structure is used to determine the topological relationship among corner points and the image processing method is used to extract corner points of the abstract template structure. The main advantages in the proposed method include: (1) Improving the accuracy of the pylon decomposition method through introducing a new feature to identify segmentation positions; (2) performing the internal structure of quadrangular frustum pyramids reconstruction; (3) establishing the abstract template structure and using image processing methods to improve computational efficiency of pylon reconstruction. Eight types of pylons are tested in this study, and the average error of pylon reconstruction is 0.32 m and the average of computational time is 0.8 s. These results provide evidence that the pylon reconstruction method developed in this study has high accuracy, efficiency, and applicability.

A Model-Driven Method for Pylon Reconstruction from Oblique UAV Images

“…Recently, there have been several high-quality algorithms focusing on 3D object reconstruction. However, according to our knowledge, the automatic image-based reconstruction of pylon has rarely been reported, and only a few works research automatic pylon reconstruction based on ALS data [10][11][12][13]. Li et al first proposed a model-driven method to reconstruct the pylon [10].…”

“…The pylon body is reconstructed by a data-driven strategy, and the pylon head is efficiently reconstructed by a model-driven strategy using a Metropolis-Hastings sampler coupled with a simulated annealing algorithm, which reduces the number of parameters and searching space. Chen et al divided the pylon into three parts: inverted triangular pyramid lower structures, quadrangular frustum pyramid middle structures and complex upper structures [12]. The prior knowledge with a data-driven strategy is applied to reconstruct the lower and middle structures and the priori abstract template structures are used to reconstruct the upper structures.…”

Modelling a Cell Tower Using Sfm: Automated Detection of Structural Elements From Skeleton Extraction on a Point Cloud

“…More recently, case studies of power pylons are reported, which are bigger and more complex objects than cell towers. In (Chen et al, 2019) Airborne Laser Scanners (ALS) are used to acquire 3D data, and an automatic reconstruction algorithm is developed to retrieve the frame of the quadrangular frustrum pyramid, while the internal structure reconstruction is based on prior knowledge of it. In (Jiang.…”

Systematic Comparison of Power Corridor Classification Methods from ALS Point Clouds

“…Airborne laser scanning (ALS) is an active remote sensing technology that can directly and efficiently acquire the three-dimensional spatial information of objects. It is widely used in digital city construction [3,4], forestry surveys [5,6], and power line inspection [7][8][9][10][11][12]. ALS eliminates some of the limitations of traditional inspection, such as high labor intensity, low efficiency, and low accuracy.…”

“…Since they are complex and diverse, multiple pylon models using a variety of parameters to describe the shape, need to be considered for this class. Thus, this leads to low adaptability and high complexity of the algorithm [11]. For the power line class, the defined rules mainly depend on the elevation, resulting in poor noise immunity.…”