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基于改进YOLOv8n的船舶设备拆装流程规范性评估方法

张振东 管聪 张泽辉 吴超 丁学文

中国舰船研究2025,Vol.20Issue(2):140-150,11.
中国舰船研究2025,Vol.20Issue(2):140-150,11.DOI:10.19693/j.issn.1673-3185.03902

基于改进YOLOv8n的船舶设备拆装流程规范性评估方法

Operation standardization evaluation method based on improved YOLOv8n for ship equipment disassembly and assembly

张振东 1管聪 1张泽辉 2吴超 1丁学文1

作者信息

  • 1. 武汉理工大学 船海与能源动力工程学院,湖北 武汉 430063
  • 2. 杭州电子科技大学 自动化学院(人工智能学院),浙江 杭州 310018
  • 折叠

摘要

Abstract

[Objectives]The standardization of ship engine room operations is a critical component of ship safety management.Therefore,the practical examination for crew members includes the disassembly and as-sembly of ship equipment as a key assessment item.To enhance the digitalization and intelligence of crew practical examinations,a computer vision-based automated recognition method for assessing the standardiza-tion of ship equipment disassembly and assembly processes is proposed.[Methods]First,the backbone net-work of the ship equipment detection model is constructed using YOLOv8n,and the shuffle-attention(SA)mechanism is introduced to improve the model's feature extraction capability and training efficiency.Sub-sequently,a reparameterized generalized feature pyramid network(GFPN)fusion structure is incorporated in-to the neck network to enhance the model's ability to fuse multi-scale features.Finally,the original CIoU loss function is replaced with the wise intersection over union(WIoU)loss function to improve the model's accur-acy.[Results]Experimental results on a self-constructed dataset demonstrate that,compared to YOLOv8n,the improved object detection algorithm achieves a 0.15 increase in mean average precision and a 0.6 frames-per-second improvement in real-time detection,enabling accurate recognition of the disassembly and as-sembly processes of gear pumps.[Conclusion]The improved algorithm exhibits superior recognition cap-abilities and is better suited for identifying the standardization of ship equipment disassembly and assembly processes.

关键词

船舶设备/拆除和安装/目标检测/注意力机制(SA)/泛化特征金字塔网络(GFPN)/动态非单调聚焦机制(WIoU)损失函数

Key words

ship equipments/disassembly and assembly/objection detection/shuffle-attention(SA)mech-anism/global feature pyramid network(GFPN)/wise-intersection over union(WIoU)loss function

分类

交通运输

引用本文复制引用

张振东,管聪,张泽辉,吴超,丁学文..基于改进YOLOv8n的船舶设备拆装流程规范性评估方法[J].中国舰船研究,2025,20(2):140-150,11.

基金项目

浙江省基础公益研究计划项目(LTGG24F030004) (LTGG24F030004)

国家水运安全工程技术研究中心开放基金资助项目(A202403) (A202403)

国家重点研发计划项目(2022YFE0210700) (2022YFE0210700)

中央高校基本科研业务费专项资金资助项目(104972024JYS0043) (104972024JYS0043)

中国舰船研究

OA北大核心

1673-3185

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