摘要
农业物料输送技术是制约农场智能化应用的重要瓶颈。物料输送主要借助输送设备将物料由加料机输送至受料机中,提高受料机的续航时间,使其路程加大,以确保其高效率、持续性地正常工作。该研究按照物料特性和输送原理,将现有物料输送自动化技术与装备系统地划分为以下4类:固态种苗肥自动输送技术、液态水药燃油自动加注技术、收获物自动收集技术、收获物自动卸载技术,逐一对其研究现状和发展动态进行了重点阐述和深入剖析。总结了自主定位导航、物料流量实时监测及机群实时通信3项智能化物料输送关键技术的研究进展,并结合农场智能化技术要求和应用场景,从形成全生产环节物料输送技术体系、基于时空数据的农田物料需求决策技术、基于农田数字模型和变量作业处方的农机物料丰缺预测技术、物料车多机配送路径动态优化技术角度展望了农场智能化作业多机协同物料配送技术的发展趋势,以期进一步提高农场智能化作业效率、联动性能和应用效果。
Conveying technology of agricultural materials has been one of the most important bottlenecks to restricting the intelligent application of farms.In general,the conveying equipment can be used to transport the materials from the feeder to the receiver.It is a high demand for the long battery life of the receiver for efficient and continuous conveying in the long distance.An automation conveying technology of agricultural materials can mainly cover all production links of farming,management,and harvesting in the complex system engineering.In this study,the current automation conveying technologies were systematically reviewed to divide into the following four categories,according to the material characteristics and conveying:automatic conveying technology of solid seedling fertilizer,liquid water medicine fuel automatic filling,harvest automatic collection,and harvest automatic unloading technology.A clear development trend was also proposed for the intelligent transportation of agricultural materials,with the development of technologies,such as 3S(Remote Sensing,Global Position System,GPS,and Geographic Information System,GIS),sensing and detection,as well as the automatic control and information processing.The final goal was to optimize the coordination of the fleet for the complete point-to-point zero inventory distribution,further realize the intelligent transportation of agricultural materials.Four stages of materials transportation usually included the meeting,docking,conveying,and separating.The main challenges were focused on the precise docking of the feeder/receiver,as well as the highly efficient,stable,and flexible conveying of materials.Furthermore,the research progress was summarized for three key technologies of intelligent material conveying,including autonomous positioning and navigation,real-time monitoring of material flow,and real-time communication of fleets.Among them,the autonomous positioning and navigation technology can be used to accurately control the position and path between the feeder/receiver,in order to ensure the precise meeting and docking of the feeder/receiver for better intelligent material transportation.The sensors can be widely used to real-time monitor the material balance in the granary of the feeder/receiver for the highly efficient,stable,and flexible transportation of materials in the real-time monitoring technologies of material flow.Technical support can also be provided to realize intelligent material transportation in the real-time communication technology of the machine group.The communication task between the feeder and the feeder can be completed by the transmission of information and data between the machine and the ground control station,all of which can then be collected,transmitted,and processed efficiently in real time.The information and data between the feeder/receiver can be used for a rapid response to the actual situation.Therefore,it is very necessary to combine the technical requirements and application scenarios of farm intelligence.The entire production can be linked to the agricultural material transportation system,including the farmland material demand decision-making technology using spatiotemporal data,the agricultural machinery material abundance prediction using the farmland digital model and variable operation prescriptions,and various material vehicles.A prediction was given for the trend of multi-machine collaborative material distribution in the intelligent farm operation,particularly from the perspective of dynamic optimization of machine distribution path.Therefore,the agricultural material conveying technology can be expected to be more intelligent,user-friendly,and precise in the future.Anyway,intelligent farms can greatly contribute to optimizing agricultural production and resource allocation in sustainable agriculture.
作者
苑严伟
白圣贺
牛康
周利明
赵博
熊师
刘立晶
Yuan Yanwei;Bai Shenghe;Niu Kang;Zhou Liming;Zhao Bo;Xiong Shi;Liu Lijing(College of Engineering,China Agricultural University,Beijing 100083,China;The State Key Laboratory of Soil,Plant and Machine System Technology,Chinese Academy of Agricultural Mechanization Sciences,Beijing 100083,China)
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2022年第7期78-90,共13页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家重点研发计划(2019YFB1312302)
兵团重大科技项目(2018AA00404)。
关键词
农业机械
智能化
农业物料
输送技术
农场
多机协同
agricultural machinery
intelligence
agricultural materials
conveying technology
farm
multi-machine collaboration
