[1]孙 强,刘广毅,哈斯铁尔·艾列西,等.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(04):47-52.
　SUN Qiang,LIU Guangyi,HASITIEER Ailiexi,et al.A Conveyor Belt Deviation Detection Method in Coal Handling Systems Based onthe Exposed Idler Rollers Feature[J].Machinery & Electronics,2026,44(04):47-52.
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基于托辊裸露特征的输煤皮带跑偏检测方法()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
44
期数:
2026年04期
页码:
47-52
栏目:
智能检测
出版日期:
2026-04-27

文章信息/Info

Title:
A Conveyor Belt Deviation Detection Method in Coal Handling Systems Based on
the Exposed Idler Rollers Feature
文章编号:
1001-2257(2026)04-0047-06
作者:
孙 强1; 刘广毅1; 哈斯铁尔·艾列西1; 蔡 勇1; 陈晓霄2; 万书亭2; 金从兵3
(1.华电新疆红雁池发电有限公司,新疆 乌鲁木齐 830063;
2.华北电力大学河北省电力机械装备健康维护与失效预防重点实验室,河北 保定 071003;
3.湖北凯瑞知行智能装备有限公司,湖北 孝感 430070)
Author(s):
SUN Qiang1; LIU Guangyi1; HASITIEER Ailiexi1; CAI Yong1; CHEN Xiaoxiao2; WAN Shuting2; JIN Congbing3
(1.Huadian Xinjiang Hongyanchi Power Generation Co.,Ltd.,Urumqi 830063,China;2.Hebei Key Laboratory of Electric
Machinery Health Maintenance and Failure Prevention,North China Electric Power University,Baoding 071003,China;
3.Hubei Kairui Zhixing Intelligent Equipment Co.,Ltd.,Xiaogan 430070,China)
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YOLO11
Keywords:
belt conveyor; belt deviation detection; idler exposure features; deep learning; improved YOLO11
分类号:
TH222;TP391.41
文献标志码:
A
摘要:
为实现对复杂工业环境下带式输送机皮带跑偏的实时、准确检测,提出一种融合了改进YOLO11
轻量化语义分割模型与基于托辊裸露面积的工程友好型跑偏判别方法。改进YOLO11模型主干引
入C3k2 Edge模块,通过多尺度边缘特征提取与DSM 注意力机制,强化复杂背景下边缘感知能力;颈部设
计HS PAN 网络,融合自上而下与自下而上路径,提升特征融合与定位效率。在自建数据集与实际跑偏检
测实验上的结果表明,所提方法能够满足复杂工业场景下高精度、轻量化、实时的皮带跑偏检测需求,具备
良好的工程适用性。
Abstract:
To achieve real time and accurate detection of belt deviation in belt conveyors under complex
industrial environments,this paper proposes a method that integrates an improved lightweight semantic
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 complex
industrial settings,exhibiting good engineering applicability.

参考文献/References:

 [1] 杨文波,闫学伟,王明信,等.基于多模态信息融合的输煤皮带跑偏故障智能视觉识别[J].自动化应用,2025,
66(19):51 53.
[2] 余浩,刘红梅,田俊杰,等.基于EDEM 的输送带动态跑偏仿真分析[J].机械与电子,2022,40(8):8 13.
[3] 曹高生,李志强,蒋刚.矿用带式输送机跑偏控制系统研究[J].机械与电子,2019,37(3):59 61.
[4] 邹盛,沈科,陈晓晶,等.基于Hough变换的带式输送机托辊图像分割方法[J].能源与环保,2020,42(10):
169 172.
[5] 王浩宇,王希鹏.基于机器视觉的带式输送机胶带跑偏检测方法研究[J].中国煤炭,2024,50(增刊2):158 163.
[6] 刘锋,白金牛.基于视觉技术的带式输送机跑偏检测方法[J].山西焦煤科技,2023,47(4):25 28.
[7] 史艳斌.基于神经网络的运输机皮带跑偏检测研究[J].矿业装备,2024(11):157 159.
[8] 聂志勇,官锋,穆杞梓.基于图像分割的皮带跑偏故障分级报警方法研究[J].中国设备工程,2023(24):271 274.
[9] ZHANG M C,JIANG K,CAO Y S,et al.A deep learning based method for deviation status detection in intelligent
conveyor belt system[J].Journal of cleaner production,2022,363:132575.
[10] GAO M Z,LI S H,CHEN X S,et al.A novel combined method for conveyor belt deviation discrimination
under complex operational scenarios[J].Engineering applications of artificial intelligence,2024,
137:109145.
[11] CUI Y N,REN W Q,CAO X C,et al.Focal network for image restoration[C]∥Proceedings of the IEEE/
CVF international conference on computer vision,2023:13001 13011.
[12] CHEN Y F,ZHANG C Y,CHEN B,et al.Accurate leukocyte detection based on deformable DETR and
multi level feature fusion for aiding diagnosis of blood diseases[J].Computers in biology and medicine,
2024,170:107917.
[13] WANG X P,WAN S T,LI Z H,et al.ECL Tear:lightweight detection method for multiple types of
belt tears[J].Measurement,2025,251:117269.

相似文献/References:

[1]曹高生,李志强,蒋刚.矿用带式输送机跑偏控制系统研究[J].机械与电子,2019,(03):59.
　CAO Gaosheng,LI Zhiqiang,JIANG Gang.Research on Deviation Control System of Mine Belt Conveyor[J].Machinery & Electronics,2019,(04):59.

备注/Memo

备注/Memo:
 收稿日期:2025-12-28
基金项目:国家自然科学基金资助项目(52275109)
作者简介:孙 强 (1976-),男,河南商丘人,高级工程师,研究方向为火电厂智慧化燃料输送与管理;刘广毅 (1987-),男,甘肃酒泉人,
工程师,研究方向为燃煤电站电气自动化技术;哈斯铁尔·艾列西 (1994-),男,新疆伊犁人,助理工程师,研究方向为燃煤电站
集控运行技术;陈晓霄 (2002-),男,云南大理人,硕士研究生,研究方向为电力设备状态监测与故障诊断;万书亭 (1970-),
男,山西长治人,博士,教授,博士研究生导师,研究方向为电力设备状态监测与故障诊断,通信作者,E-mail:52450809@
ncepu.edu.cn。
更新日期/Last Update: 2026-05-11