自动化与信息工程2025，Vol.46Issue(5)：54-62,9.DOI:10.12475/aie.20250507
半监督YOLO在电梯检验视频合规性审查的应用
Application of Semi-supervised YOLO in Compliance Review of Elevator Inspection Videos
罗伟立 1陈贵龙 2刘桂雄 2陈建勋3
作者信息
- 1. 珠海市安粤科技有限公司,广东 珠海 519080
- 2. 华南理工大学机械与汽车工程学院,广东 广州 510640
- 3. 广东省特种设备检测研究院珠海检测院,广东 珠海 519002
- 折叠
摘要
Abstract
Addressing the issues of high labor and resource costs associated with the manual review of elevator inspection videos,as well as the difficulty in ensuring objectivity and consistency,this paper proposes an automatic compliance review method for key elements in elevator inspection videos based on YOLOv11n.The method constructs an initial training dataset following the principles of orthogonal experimental design and introduces a semi-supervised learning strategy to reduce manual annotation costs and enhance model generalization capability.Differentiated compliance review algorithms are designed according to the characteristics of various key elements,achieving full automation of the detection and review pipeline.Experimental results indicate that the proposed method achieve P=0.958 6,R=0.978 3,mAP@50 0.979 5=,mAP@50∶95 0.825 6=in image-level object detection;and in video-level compliance review,PSp==1.00,ensuring a review process with zero false positives.The method not only demonstrates advantages in detection accuracy but also balances real-time performance and a lightweight design,providing a practical and feasible technical pathway for the automatic compliance review of key elements in elevator inspection videos.关键词
半监督学习/YOLOv11n模型/电梯检验/合规性审查/目标检测Key words
semi-supervised learning/YOLOv11n model/elevator inspection/compliance review/object detection分类
信息技术与安全科学引用本文复制引用
罗伟立,陈贵龙,刘桂雄,陈建勋..半监督YOLO在电梯检验视频合规性审查的应用[J].自动化与信息工程,2025,46(5):54-62,9.
