计算机应用与软件2025，Vol.42Issue(4)：57-62,6.DOI:10.3969/j.issn.1000-386x.2025.04.010
基于机器视觉的小型光伏电站鸟粪监测系统
BIRD DROPPINGS MONITORING SYSTEM FOR SMALL PHOTOVOLTAIC POWER STATION BASED ON MACHINE VISION
摘要
Abstract
In order to accurately and efficiently identify and locate the bird droppings on small photovoltaic power station,the improved YOLOv5 model is carried on the Raspberry Pi to form a bird droppings detection system of photovoltaic power plants.The system reduced the threshold of confidence to identify all suspicious bird droppings,identified and partitioned single photovoltaic panels,and increased the confidence threshold to accurately detect suspicious bird droppings in photovoltaic panels.In order to make the YOLOv5 algorithm more suitable for detection,the pyramid split attention was integrated in the algorithm.The small target detection layer was added and the original pooling operation was replaced by SoftPool.In the test set,the mAP_0.5 of PV-YOLOv5 model identified for photovoltaic panels was 96.78％,which was 2.35 percentage points higher than that of Faster-RCNN.The mAP_0.5 of NF-YOLOv5 for bird droppings recognition was 94.12％,which was 5.8 percentage points higher than the original YOLOv5 model.关键词
鸟粪/光伏电站/机器视觉/YOLOv5/树莓派Key words
Bird droppings/Photovoltaic power station/Machine vision/YOLOv5/Raspberry Pi分类
信息技术与安全科学引用本文复制引用
王松,顾翔,王强..基于机器视觉的小型光伏电站鸟粪监测系统[J].计算机应用与软件,2025,42(4):57-62,6.基金项目
江苏省高等学校自然科学研究重大项目(19KJA320004). （19KJA320004）
