机械与电子2026，Vol.44Issue(4)：47-52,6.
基于托辊裸露特征的输煤皮带跑偏检测方法
A Conveyor Belt Deviation Detection Method in Coal Handling Systems Based on the Exposed Idler Rollers Feature
摘要
Abstract
To achieve real-time and accurate detection of belt deviation in belt conveyors under com-plex industrial environments,this paper proposes a method that integrates an improved lightweight seman-tic segmentation model based on YOLO11 with an engineering-friendly deviation criterion utilizing idler exposure areas.The improved YOLO11 model incorporates a C3k2-Edge module in its backbone,which enhances edge perception capabilities in complex backgrounds through multi-scale edge feature extraction and a DSM attention mechanism.The neck is designed with a HS-PAN network that integrates top-down and bottom-up paths to improve feature fusion and localization efficiency.Results from experiments on the self-built dataset and actual deviation detection scenarios demonstrate that the proposed method can meet the requirements of high-precision,lightweight,and real-time belt deviation detection in com-plex industrial settings,exhibiting good engineering applicability.关键词
带式输送机/皮带跑偏检测/托辊裸露特征/深度学习/改进YOLO11Key words
belt conveyor/belt deviation detection/idler exposure features/deep learning/improved YOLO11分类
机械制造引用本文复制引用
孙强,刘广毅,哈斯铁尔·艾列西,蔡勇,陈晓霄,万书亭,金从兵..基于托辊裸露特征的输煤皮带跑偏检测方法[J].机械与电子,2026,44(4):47-52,6.基金项目
国家自然科学基金资助项目(52275109) （52275109）
