基于轻量化YOLOv7的带式输送机输送带撕裂检测算法  

Conveyor belt tear detection algorithm of belt conveyor based on lightweight YOLOv7

作　　者：安龙辉 王满利 张长森 An Longhui;Wang Manli;Zhang Changsen(School of Physics and Electronic Information,Henan Polytechnic University,Jiaozuo 454000,China)

机构地区：[1]河南理工大学物理与电子信息学院,焦作454000

出　　处：《电子测量技术》2025年第1期64-75,共12页Electronic Measurement Technology

基　　金：国家自然科学基金(52074305);河南省科技攻关项目(242102221006);河南省研究生教育改革与质量提升工程(YJS2024AL026)项目资助。

摘　　要：针对矿井下输送机特殊运行环境下输送带撕裂的检测难题,提出一种线激光辅助下的改进YOLOv7轻量化检测算法。首先,针对输送带撕裂以小目标为主,不需要最大的检测层,从而简化网络模型,达到减小模型体积和减少参数量的目的。此外,采用动态非单调FM的Wise-IoU损失函数,使模型更加关注普通质量的样本,提高模型检测性能。然后,使用LAMP剪枝方法,提高模型的计算速度并降低计算复杂度,实现检测网络的轻量化,采用通道知识蒸馏无损提高模型精度,最后使用TensorRT加速模型,达到更快的检测速度。实验结果表明,与基准模型相比,改进后模型的参数量和计算量分别减少了86.8%、49.2%,mAP@0.5:0.95达到了62.4%,并且检测速度提升151.0 fps,模型大小从71.3 MB减少到12.8 MB。经过改进后的模型,提高了对输送带撕裂故障检测的准确性和实时性。To solve the problem of conveyor belt tear detection in the special operating environment of underground mines,a lightweight detection algorithm based on line laser assistance and improved YOLOv7 is proposed.Firstly,considering that the conveyor belt tear is mainly small targets,the largest detection layer is not needed,thus simplifying the network model to reduce the model size and the number of parameters.In addition,the dynamic non-monotonic FM-based Wise-IoU loss function is adopted to make the model pay more attention to common quality samples and improve the model detection performance.Then,the LAMP pruning method is used to improve the model′s computing speed and reduce the computing complexity,achieving the lightweight of the detection network.The channel knowledge distillation is used to improve the model accuracy without loss,and finally,the model is accelerated by TensorRT to achieve faster detection speed.The experimental results show that compared with the benchmark model,the improved model has a parameter number and computing volume reduced by 86.8%and 49.2%,respectively,mAP@0.5:0.95 reached 62.4%,and the detection speed was improved by 151.0 fps,the model size was reduced from 71.3 MB to 12.8 MB.After the improvement,the model has improved the accuracy and real-time detection of conveyor belt tear faults.

关 键 词：YOLOv7 目标检测 Wise-IoU LAMP剪枝 通道知识蒸馏 TensorRT 

分 类 号：TN911.73[电子电信—通信与信息系统] TP391.41[电子电信—信息与通信工程]