精准喷施型水田自适应除草机设计与试验  

Design and Experiment of Precision Spray-type Adaptive Weeder for Paddy Fields

作　　者：王金峰[1] 朱朋运 初宇航 徐琛 宋育岭 王一甲 WANG Jinfeng;ZHU Pengyun;CHU Yuhang;XU Chen;SONG Yuling;WANG Yijia(College of Engineering,Northeast Agricultural University,Harbin 150030,China;College of Water Conservancy and Civil Engineering,Northeast Agricultural University,Harbin 150030,China)

机构地区：[1]东北农业大学工程学院,哈尔滨150030 [2]东北农业大学水利与土木工程学院,哈尔滨150030

出　　处：《农业机械学报》2025年第2期195-205,共11页Transactions of the Chinese Society for Agricultural Machinery

基　　金：黑龙江省自然科学基金联合基金重点项目(ZL2024E001);国家重点研发计划项目(2021YFD200060502);国家自然科学基金面上项目(32472012)。

摘　　要：水田除草是提升水稻产量的关键农艺措施,其中化学除草因其高效性被广泛应用。传统化学除草依赖人工操作,且常采用大面积喷施,操作成本增加的同时还易引起环境污染等负面问题。基于此背景,设计了一款精准喷施型水田除草机用于自适应除草作业。搭建了除草机喷施装置及系统,基于构建的多样化水田杂草数据集设计了以MS-YOLO v7为核心框架的杂草检测系统。MS-YOLO v7模型将骨干网络与MobileOne相结合,将CIoU损失函数替换为SIoU损失函数。通过消融试验和不同模型对比试验验证模型性能,结果显示模型识别精度为95.65%,平均精度均值(mAP)为92.67%,实时性达到51.29 f/s。在树莓派上使用OpenVINO对IR模型进行推理,检测单幅水田杂草图像耗时0.806 s。构建的喷施系统能即时捕捉并解析来自杂草检测系统的传输信号,进而实现对除草喷施装置的精准调控。田间试验结果表明,精准喷施型水田自适应除草机伤苗率为2.95%,对靶施药准确率为94.98%,变异系数为0.128%,满足水田除草的农艺要求。该除草机实现了水田除草无人化操作,可为农业的智能化发展提供技术参考。University;Weed control in paddy fields is a key agronomic measure to improve rice yield,and chemical weed control is widely used because of its high efficiency.Traditional chemical weed control relies on manual operation and often uses large area spraying,which increases the operation cost and causes negative problems such as environmental pollution.Based on this background,a precision spraying type paddy weeder for adaptive weeding operation was designed.The weeder spraying device and system were constructed,and the weed detection system with MS-YOLO v7 as the core framework was designed based on the constructed diversified paddy field weed dataset.The MS-YOLO v7 model combined the backbone network with MobileOne,and replaced the CIoU loss function with the SIoU loss function.The model performance was verified by ablation test and different model comparison test,and the results showed that the model recognition accuracy was 95.65%,the mean average precision(mAP)was 92.67%,and the real-time performance reached 51.29 f/s.The IR model was reasoned by using OpenVINO on Raspberry Pi,and the detection of a single paddy field weed image took 0.806 s.The constructed spraying system can instantly capture and analyze the transmission signals from the weed detection system,and then realize the precise regulation of the weed spraying device.The results of the field test showed that the precision spraying type paddy field adaptive weeder had a seedling injury rate of 2.95%,a target application accuracy of 94.98%,and a coefficient of variation of 0.128%,which met the agronomic requirements for weed control in paddy fields.The weeder realized the unmanned operation of paddy field weeding and it can provide technical reference for the intelligent development of agriculture.

关 键 词：水田除草机 精准喷施 自适应 深度学习 YOLO v7 

分 类 号：S224.1[农业科学—农业机械化工程]