自动化学报2026，Vol.52Issue(4)：833-845,13.DOI:10.16383/j.aas.c250540
基于结构频谱感知框架的配电网点云语义分割
Semantic Segmentation of Distribution Network Point Clouds Based on a Structure Spectrum-Aware Framework
摘要
Abstract
The semantic segmentation of point clouds in power distribution networks is of great significance for en-abling unmanned inspection and intelligent grid operation and maintenance.Although existing methods have made some progress in spatial modeling and structural enhancement,they still face prominent challenges in spectral fea-ture extraction and the efficiency of large-scale point cloud processing.To address these issues,this paper proposes a structure spectrum-aware framework(SSAF)to enhance the expressive capability of point clouds in long-distance distribution network scenarios.In the data preprocessing stage,a structure-guided hierarchical filtering strategy and a structure-aware sample partitioning method are designed to reduce redundant background points while preserving the structural integrity and continuity of key objects such as poles and wires.During the semantic segmentation stage,a spatial-spectral collaborative semantic segmentation network is constructed,in which local polar coordin-ates are introduced to enhance direction-sensitive feature modeling.Furthermore,a dynamic fusion mechanism based on attention maps is employed to enable adaptive interaction and information enhancement between spatial and spectral features.Experimental results show that SSAF achieves higher segmentation accuracy and inference ef-ficiency on real-world distribution network point cloud datasets.It outperforms existing representative methods across multiple key metrics,demonstrating its practicality and engineering generalization potential in complex scen-arios.关键词
配电网点云/语义分割/结构频谱感知/空谱融合/极坐标频谱变换Key words
distribution network point cloud/semantic segmentation/structure spectrum awareness/spatial-spec-tral fusion/polar spectral transform引用本文复制引用
唐友源,张辉,杜瑞,张恺宁,曹云康,别克扎提·巴合提,陈厚权,王耀南..基于结构频谱感知框架的配电网点云语义分割[J].自动化学报,2026,52(4):833-845,13.基金项目
国家自然科学基金重大项目(62595801),湖南省十大技术攻关项目(2024GK1010),湖南省自然科学基金重点项目(2025JJ30024),国网湖南省电力有限公司科技项目(5216A522001Y,5216A5240003,5216AJ250008)资助 Supported by Major Program of National Natural Science Foundation of China(62595801),Ten Technical Research Projects of Hunan Province(2024GK1010),Natural Science Foundation of Hunan Province(2025JJ30024),and Science and Technology Project of State Grid Hunan Electric Power Co.,Ltd.(5216A522001Y,5216A5240003,5216AJ250008) （62595801）
