中北大学学报（自然科学版）2025，Vol.46Issue(4)：508-516,9.DOI:10.62756/jnuc.issn.1673-3193.2024.07.0007
基于状态空间模型的输电线路隐患目标检测方法
Target Detection Method of Hidden Danger Targets in Transmission Lines Based on State Space Models
贺慧心 1樊永生 1崔文红2
作者信息
- 1. 中北大学 计算机科学与技术学院,山西 太原 030051
- 2. 太原理工大学 数学学院,山西 太原 030600
- 折叠
摘要
Abstract
Transmission line inspection is an important means to ensure the stable transportation of electricity,and existing hidden danger detection methods are difficult to effectively model global information while ensuring real-time model performance.This article introduced a state space model based on YOLOv8,and achieved long-distance hidden danger detection in space through block operation and low rank approximation,and global information was extracted with lower complexity.In the state space model,cross scanning and dynamic multi-path activation mechanisms were used to address the direction insensitivity and non-causal characteristics of the state space model to image data,capture hidden target structure and pattern information,and using spatial context information to identify local features;In the stage of target classification and localization,a separated detection head based on spatial alignment was designed to align spatial misalignment through different rep-resentation methods to enhance the accuracy of classification and localization.Finally,experiments show that the new model outperforms mainstream single-stage and two-stage object detection models in terms of average accuracy and frame rate with an accuracy improvement of 2.8%.关键词
状态空间模型/YOLO/Mamba/目标检测/输电线路隐患Key words
state space models/YOLO/Mamba/target detection/hidden dangers in transmission lines分类
武器工业引用本文复制引用
贺慧心,樊永生,崔文红..基于状态空间模型的输电线路隐患目标检测方法[J].中北大学学报（自然科学版）,2025,46(4):508-516,9.
