基于红外热成像的光伏发电板缺陷检测技术研究
Research on Defect Detection Technology for Photovoltaic Panels Based on Infrared Thermal Imaging
何心坤1
作者信息
- 1. 山东胜沃塑料机械科技有限公司,山东 济南 271100
- 折叠
摘要
随着光伏产业的快速发展,快速检测光伏板的异常已经成为提升巡检效率的关键要素.然而,传统的光伏板缺陷检测方法存在效率不高、检测效果差等问题.本文提出了一种基于红外热成像的光伏发电板缺陷检测技术,分析了红外检测技术用于光伏板缺陷检测的原理,通过引入SENet注意力到YOLOV4网络,完成了光伏发电板缺陷的智能检测.
Abstract
With the rapid development of the photovoltaic industry,rapid detection of abnormalities in photovoltaic panels has become a key element in improving inspection efficiency.However,traditional defect detection methods for photovoltaic panels have problems such as low efficiency and poor detection results.This article proposes a photovoltaic panel defect detection technology based on infrared thermal imaging,analyzes the principle of infrared detection technology for photovoltaic panel defect detection,and achieves intelligent detection of photovoltaic panel defects by introducing SENet attention to YOLOV4 network,
关键词
深度学习/缺陷检测/光伏发电/注意力机制Key words
Deep learning/defect detection/photovoltaic power generation/attention mechanism引用本文复制引用
出版年
2024
NETL
NSTL
万方数据