摘要
针对目前柑橘分拣过程中的作业成本高、标准难以统一、分拣精度低等问题,基于深度学习技术和PLC设计并开发了一套柑橘分拣控制系统。该系统利用YOLO模型提取柑橘图像特征,根据柑橘外观特征进行分类,再结合PLC控制技术,实现了柑橘的精准分拣,有效提高了分拣的精度和效率,为农产品的自动化分级提供了技术参考。
To address the issues of high operational costs,difficult standardization,and low sorting accuracy in the current citrus sorting process,a citrus sorting control system was designed and developed based on deep learning technology and PLC(Programmable Logic Controller).The system employs the YOLO model to extract image features of citrus fruits,classifies them according to appearance characteristics,and integrates PLC control technology to achieve precise sorting of citrus.This effectively enhances the accuracy and efficiency of the sorting process,providing a technical reference for the automated grading of agricultural products.
作者
唐涛
TANG Tao(College of Information and Intelligence,Hunan Agricultural University,Changsha,Hunan 410128,China;Changde College of Science and Technology,Changde,Hunan 415000,China)
出处
《农业工程与装备》
2024年第5期21-26,共6页
AGRICULTURAL ENGINEERING AND EQUIPMENT
