An Efficient Voxel-Based Segmentation Algorithm Based on Hierarchical Clustering to Extract LIDAR Power Equipment Data in Transformer Substations

Abstract

Light detection and ranging (LIDAR) scanning is a common method of substation scene modeling that extracts point clouds of electrical equipment from the point cloud scene of a substation. The extraction effect is limited by uncertainty regarding the noise level, nonuniform point cloud density, and the computational complexity. In this paper, we propose a point cloud extraction solution for electrical equipment models. First, a statistical analysis of substation ground elevation is performed to obtain the point clouds of devices at the feature height and remove large numbers of redundant underground point clouds. Second, based on the statistically derived power equipment feature heights, the point cloud data are sliced according to the featured elevation intervals. Based on voxelization, the point cloud slices are then clustered using horizontal hierarchical clustering. The clustering results at different elevation intervals are then reclustered using vertical hierarchical clustering. Finally, we use filters combined with the DBSCAN algorithm to perform fine segmentation on the point cloud data. The results show that our slice clustering approach reduces the computational burden involved in point cloud processing, and the comprehensive clustering strategy ensures the accuracy of the clustering results.INDEX TERMS clustering methods, point cloud segmentation, smart grid, substation modeling,

Shocker─A Molecular Dynamics Protocol and Tool for Accelerating and Analyzing the Effects of Osmotic Shocks

“…To discern the inner and outer solvent compartments, the solvent bins are clustered using a distance-based clustering algorithm in which only adjacent bins are considered (Figure , Step II) . The algorithm starts in a bin with a value of 0, indicating a solvent bin.…”

“…To discern the inner and outer solvent compartments, the solvent bins are clustered using a distance-based clustering algorithm in which only adjacent bins are considered ( Figure 1 , Step II). 35 The algorithm starts in a bin with a value of 0, indicating a solvent bin. From this position, it considers the values of the six adjacent bins, of which the position is added to the cluster if it turns out to be a zero.…”

Shocker - a molecular dynamics protocol and tool for accelerating and analyzing the effects of osmotic shocks

“…Step II: Clustering of membrane and solvent bins. To discern the inner and the outer solvent compartment, the solvent bins are clustered using a distance-based clustering algorithm in which only adjacent bins are considered (Figure 1, step II) [33]. The algorithm starts in a bin with the value 0, indica6ng a solvent bin.…”

Overview of Substation Modeling Based on 3D Point Cloud

“…This method only applies to these relatively simple substation scenes and performs poorly in complex scenes. Guo et al [41] put forward a kind of efficient and voxel-based substation scene segmentation method. In the segmentation process, the algorithm firstly removes the ground point cloud according to elevation differences, slices it and clusters it in horizontal direction, then perform reclustering by using vertical clustering to complete the segmentation.…”