油菜直播机组无人播种作业远程监测系统设计
CSTR:
作者:
作者单位:

华中农业大学工学院/农业农村部长江中下游农业装备重点实验室,武汉430070

作者简介:

王登辉,E-mail:2575633691@qq.com

通讯作者:

丁幼春,E-mail:kingbug163@163.com

中图分类号:

S223.2

基金项目:

国家重点研发计划项目(2021YFD2000402;2021YFD2000402-3);湖北省重点研发计划项目(2021BBA080)


Remote monitoring system for unmanned sowing operation of rapeseed direct seeding
Author:
Affiliation:

College of Engineering /Ministry of Agriculture and Rural Affairs Key Laboratory of Agricultural Equipment in Mid-Lower Yangtze River, Huazhong Agricultural University, Wuhan 430070, China

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • | |
  • 文章评论
    摘要:

    为解决油菜直播机组无人播种作业过程中田间播种质量信息难以实时直观展示的问题,本研究以雷沃804拖拉机及其搭载的2BYQ-8型气送式油菜直播机为试验平台,设计一套油菜直播机组无人播种作业远程监测系统。该系统由油菜直播机组无人播种作业平台、无人播种作业数据采集系统和播种质量监测云平台三部分构成,通过对雷沃804拖拉机档位、离合、动力输出装置(power take off,PTO)、悬挂机构进行电控液压改装,设计相应控制策略实现直播机组的无人播种作业;利用车载路由器组建播种监测终端和车载计算机之间的局域网,实现对播种数据与导航数据的融合同步,并通过网络连接传输给云平台进行数据存储与实时展示;云平台计算播种质量数据及其对应的田间位置数据,基于网页端高精度地图生成田间作业区域的播种状态图。结果显示,直播机组无人播种作业段横向平均偏差0.037 m,最大偏差0.125 m,电控液压改装系统运行稳定、可靠,满足直播机组无人作业要求,4G网络条件下,云平台通信最大数据传输时延不超过100 ms,云存储数据完整无遗漏,各播种通道田间播量检测准确率不低于96.16%,满足远程监测系统实时性和准确性要求。研究表明,该系统可实现油菜直播机组的田间无人播种作业和对作业区域播种信息的精确采集与直观展示。

    Abstract:

    A remote monitoring system for unmanned sowing operation of rapeseed direct seeding unit was designed by taking the Reeva 804 tractor and its equipped 2BYQ-8 air-fed rapeseed direct seeding machine as the test platform to solve the problem that it is difficult to display the field sowing quality information in real time and intuitively during the unmanned sowing operation of rapeseed direct seeding unit. The system consists of three parts including unmanned sowing platform, unmanned sowing data collection system and sowing quality monitoring cloud platform. Corresponding control strategies were designed to achieve unmanned sowing operation of the direct seeding unit through the electric and hydraulic modification of the gear, clutch, power take off (PTO), and suspension mechanism of the Lovol 804 tractor. A vehicle mounted router was used to establish a local area network between the seeding monitoring terminal and the on-board computer to realize the fusion and synchronization of seeding data and navigation data. Data were transmitted to cloud platforms through network connections for data storage and real-time display. The cloud platform calculated the seeding quality data and its corresponding field location data, and generated the seeding status map of the field operation area based on the high-precision map on the web page. Results showed that the average lateral deviation of the unmanned sowing operation section of direct seeding unit was 0.037 m, with a maximum deviation of 0.125 m. The electric and hydraulic modification system operates stably and reliably, meeting the unmanned operation requirements of the direct seeding unit. The maximum data transmission time delay of the cloud platform communication did not exceed 100 ms under the 4G network conditions. The cloud storage data is complete without omission, the accuracy of field sowing detection of each sowing channel is not less than 96.16%, meeting the real-time and accuracy requirements of remote monitoring system. It is indicated that the system can realize the unmanned sowing operation of rapeseed oil direct seeding unit in the field and the accurate collection and intuitive display of sowing information in the operation area. It will provide reference for the remote monitoring of rapeseed sowing operation, the analysis and visualization of sowing data.

    表 4 田间播量检测准确率Table 4 Field sowing detection accuracy
    表 2 无人播种作业数据包定义Table 2 Unmanned seeding operation data package definition
    表 3 无人播种作业田间试验数据(部分)Table 3 Unmanned seeding operation field trial data (partial)
    图1 无人播种作业远程监测系统总体结构Fig.1 Overall structure of remote monitoring system for unmanned seeding operation
    图2 远程监测系统总体结构图Fig.2 Overall structure of the control system
    图3 电控液压改装油路设计Fig.3 Design of electric control hydraulic modified oil circuit
    图4 导航路径规划Fig.4 Navigation path planning
    图5 直播机组作业状态切换流程图Fig.5 Flow chart of live unit operation state switching
    图6 数据采集系统结构框图Fig.6 Data acquisition system architecture block diagram
    图7 油菜播种作业监测系统Fig.7 Rapeseed sowing operation monitoring system
    图8 无人播种作业数据采集软件流程Fig.8 Unmanned seeding operation data collection software process
    图9 油菜播种监测云平台网页端界面Fig.9 Rapeseed planting monitoring cloud platform web interface
    图10 播种状态图生成流程Fig.10 Seeding status map generation process
    图11 北斗天线与各通道播种位置关系Fig.11 Beidou antenna in relation to each channel seeding position
    图12 田间试验场景Fig.12 Field test scenes
    图13 数据包传输时延Fig.13 Packet transmission delay
    图14 直播机组作业轨迹Fig.14 Seeding unit operation track
    图15 田间播种质量状态图Fig.15 Field sowing quality status chart
    表 1 直播机组作业状态Table 1 Direct seeder unit working status
    参考文献
    相似文献
    引证文献
引用本文

王登辉,卢邦,李强,李浩鹏,孙阳,丁幼春.油菜直播机组无人播种作业远程监测系统设计[J].华中农业大学学报,2023,42(3):260-270

复制
分享
文章指标
  • 点击次数:359
  • 下载次数: 820
  • HTML阅读次数: 116
  • 引用次数: 0
历史
  • 收稿日期:2023-02-13
  • 在线发布日期: 2023-06-20
文章二维码