光学精密工程2023，Vol.31Issue(24)：3640-3650,11.DOI:10.37188/OPE.20233124.3640
融合知识蒸馏和注意力机制的光伏热斑检测
Photovoltaic hot spot detection method incorporating knowledge distillation and attention mechanisms
摘要
Abstract
A detection algorithm combining knowledge distillation and attention mechanism is proposed to solve the problem that multi-scale target of the hot spot fault of photovoltaic panel in a complex environ-ment leads to difficult detection.To efficiently extract and retain fault feature information,a module that integrates higher-order spatial interaction and channel attention was designed to improve the expression ability of fault feature information.To further enhance the ability of expressing target information in a com-plex background,an attention module combining channel and location information was constructed to im-prove the recognition accuracy of fault location information.The parameters of teacher network were trans-ferred to student network by knowledge distillation,and the detection accuracy of student network was im-proved without adding any complexity.A focal-CIoU loss function was introduced to accelerate network convergence and improve detection performance.In verifying the effectiveness of the proposed algorithm against eight classical algorithms,the experimental results show that the proposed algorithm has the high-est detection accuracy(84.8%),and the detection speed can reach 142 FPS for images with a resolution of 640×512.关键词
深度学习/光伏热斑检测/知识蒸馏/注意力机制Key words
deep learning/photovoltaic hot spot detection/knowledge distillation/attention mechanism分类
信息技术与安全科学引用本文复制引用
郝帅,吴瑛琦,马旭,李彤,王海莹..融合知识蒸馏和注意力机制的光伏热斑检测[J].光学精密工程,2023,31(24):3640-3650,11.基金项目
国家自然科学基金资助项目(No.51804250) （No.51804250）
中国博士后科学基金资助项目(No.2019M653874XB,No.2020M683522) （No.2019M653874XB,No.2020M683522）
陕西省科技计划资助项目(No.2021JQ-572,No.2020JQ-757) （No.2021JQ-572,No.2020JQ-757）
陕西省教育厅科研计划资助项目(No.18JK0512,No.21JK0769) （No.18JK0512,No.21JK0769）
