基于深度学习的光伏阵列缺陷检测与识别方法分析
Analysis of Defect Detection and Recognition Methods for Photovoltaic Arrays Based on Deep Learning
张智慧1
作者信息
- 1. 大唐山西新能源公司,山西 030032
- 折叠
摘要
阐述光伏阵列缺陷的类型和特征,探讨深度学习在该领域中的应用,关键技术包括特征提取、分类器选择、缺陷识别模型设计与实现.通过深度学习技术,实现准确识别和定位光伏阵列中的缺陷.
Abstract
This paper describes the types and characteristics of defects in photovoltaic arrays,and explores the application of deep learning in this field.Key technologies include feature extraction,classifier selection,and defect recognition model design and implementation.It achieves accurate identification and localization of defects in photovoltaic arrays through deep learning techniques.
关键词
深度学习/缺陷检测/缺陷识别/特征提取/分类器Key words
deep learning/defect detection/defect recognition/feature extraction/classifier引用本文复制引用
出版年
2024
NETL
NSTL
万方数据