Article(id=1324333602921656605, tenantId=1146029695717560320, journalId=1319690209941618849, issueId=1324333573712511176, articleNumber=null, orderNo=null, doi=10.12398/j.issn.2096-7217.2026.01.014, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1729699200000, receivedDateStr=2024-10-24, revisedDate=1735574400000, revisedDateStr=2024-12-31, acceptedDate=null, acceptedDateStr=null, onlineDate=1793675335864, onlineDateStr=2026-11-03, pubDate=1771084800000, pubDateStr=2026-02-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793675335864, onlineIssueDateStr=2026-11-03, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793675335864, creator=13701087609, updateTime=1793675335864, updator=13701087609, issue=Issue{id=1324333573712511176, tenantId=1146029695717560320, journalId=1319690209941618849, year='2026', volume='7', issue='1', pageStart='1', pageEnd='196', issueExtLink='null', onlineDate='null', pubDate='1771084800000', pubDateStr='2026-02-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793675328901, creator='13701087609', updateTime=1793872389599, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1325160106287039215, tenantId=1146029695717560320, journalId=1319690209941618849, issueId=1324333573712511176, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1325160106287039216, tenantId=1146029695717560320, journalId=1319690209941618849, issueId=1324333573712511176, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=136, endPage=144, ext={EN=ArticleExt(id=1324333603479499038, articleId=1324333602921656605, tenantId=1146029695717560320, journalId=1319690209941618849, language=EN, title=Design and optimization of a drone sowing device based on discrete element method, columnId=null, journalTitle=Journal of Intelligent Agricultural Mechanization, columnName=null, runingTitle=null, highlight=null, articleAbstract=

In response to the practical issues faced in hilly areas, such as limited per capita arable land, scattered plots, rugged terrain, low efficiency of large agricultural machinery, and the occasional inconvenience of using small machinery, this paper designs a sowing device that combines a groove wheel and a sowing disk based on drone technology. The paper presents the design concept and optimization simulation plan for the combined sowing device, using rice seeds as the research subject. A discrete element method (DEM) is employed to model the rice seeds using basic unit particles. The sowing process of the device is simulated using DEM software EDEM, primarily analyzing the sowing disk structure. It is found that the angle of the sowing disk and its rotational speed significantly affect the distribution of rice seeds on the disk, while the number of blades significantly impacts the distribution of rice seeds in the air. To achieve uniform sowing, the study uses DEM to design an orthogonal experiment with three factors at three levels, focusing on the rotational speed of the sowing disk, the angle of the blades, and the number of blades. The simulation results indicate that the optimal seeding disc rotation speed of 850 r/min, deflection angle of 50° , and number of blades of 5 resulted in a uniformity coefficient of variation of 12.99%. Verification tests were conducted in three sets focusing on flight altitude, sowing amount, and flight speed. The results show that the maximum coefficient of variation for actual distribution is 24.25%, while the minimum is 15.42%. The average coefficients of variation for rice distribution corresponding to flight altitude, sowing amount, and flight speed are 17.83%, 20.90%, and 18.55%, respectively, which generally meet the agronomic requirements for rice aerial seeding. Through the research and analysis of the structural parameters, discrete element simulation, and field tests of the groove wheel and sowing disk combination, the paper identifies the optimal parameters for the operational performance of the sowing device. These parameters lay the groundwork for research on aerial seeding and its practical application in hilly areas.

, authors=Xiaodong BIAN1, 2, Chengsai FAN3, 4, Changqing CHEN1, 2, Hongfeng YU3, 4, Tao ZHENG1, 2, authorsList=Xiaodong BIAN, Chengsai FAN, Changqing CHEN, Hongfeng YU, Tao ZHENG, authorCompany=null, correspAuthors=Changqing CHEN, authorNote=

BIAN Xiaodong, E-mail:

, correspAuthorsNote=
* CHEN Changqing, E-mail:
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1324333604272222495, articleId=1324333602921656605, tenantId=1146029695717560320, journalId=1319690209941618849, language=CN, title=基于离散元的无人机撒播装置设计与优化, columnId=0, journalTitle=智能化农业装备学报(中英文), columnName=, runingTitle=null, highlight=null, articleAbstract=

针对丘陵地区人均耕地面积少,且土地比较分散,地形崎岖,大型农机作业效率低,甚至无法工作,小型农机有时也使用不方便的实际问题,基于无人机技术,设计了一种槽轮—撒种盘相结合的撒种装置。给出了槽轮—撒种盘相结合的撒种装置设计思路与优化仿真方案,以水稻种子为研究对象,基于离散元方法,用基础单元颗粒对水稻种子进行建模,利用离散元软件EDEM对撒种装置的排种过程进行模拟,主要理论分析撒种盘结构,发现撒种盘偏角、转速显著影响水稻种子在撒种盘上的分布,扇叶数量显著影响水稻种子在空气中的分布。为实现均匀撒播,借助离散元方法,以偏角、转速和扇叶数量为指标,设计了以撒种盘转速、扇叶偏角、扇叶数的3因素3水平的正交试验。仿真结果表明,最终优化得到撒种盘转速850 r/min、偏角50°、扇叶数为5个,其一致性变异系数为12.99%。验证试验分别针对飞行高度、播种量和飞行速度进行3组测试,结果显示实际分布变异系数最大值为24.25%,最小值为15.42%,飞行高度、播种量和飞行速度3个因素对应的水稻分布变异系数平均值分别为17.83%、20.90%、18.55%,基本能达到水稻飞播的农艺要求。通过对槽轮—撒种盘相结合的撒种装置的结构参数、离散元仿真和验证试验的研究分析,确定了槽轮—撒种盘相结合的撒种装置工作性能的最优参数,这些参数为飞机直播的研究以及在丘陵地区的实际应用打下了基础。

, authors=边晓东1, 2, 樊成赛3, 4, 陈长卿1, 2, *, *, 余洪锋3, 4, 郑涛1, 2, authorsList=边晓东, 樊成赛, 陈长卿, 余洪锋, 郑涛, authorCompany=null, correspAuthors=陈长卿, authorNote=

边晓东,男,1992年生,浙江金华人,硕士,工程师;研究方向为农业装备自动化技术。E-mail:

, correspAuthorsNote=
* 陈长卿,男,1980年生,贵州遵义人,正高级工程师;研究方向为现代农业技术装备。E-mail:
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基于离散元的无人机撒播装置设计与优化
边晓东 1, 2 , 樊成赛 3, 4 , 陈长卿 1, 2, *, * , 余洪锋 3, 4 , 郑涛 1, 2
智能化农业装备学报(中英文) | 2026,7(1): 136-144
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智能化农业装备学报(中英文) | 2026 , 7 (1) : 136 -144
基于离散元的无人机撒播装置设计与优化
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边晓东,男,1992年生,浙江金华人,硕士,工程师;研究方向为农业装备自动化技术。E-mail:

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边晓东1, 2 , 樊成赛3, 4, 陈长卿1, 2, *, * , 余洪锋3, 4, 郑涛1, 2
作者信息
  • 1.金华市农业科学研究院,浙江 金华,321017
  • 2.金华市丘陵山区适用农机重点实验室,浙江 金华,321017
  • 3.南京农业大学,江苏 南京,210095
  • 4.江苏省智能化农业装备重点实验室,江苏 南京,210095
通讯作者:
* 陈长卿,男,1980年生,贵州遵义人,正高级工程师;研究方向为现代农业技术装备。E-mail:
作者简介:

边晓东,男,1992年生,浙江金华人,硕士,工程师;研究方向为农业装备自动化技术。E-mail:

Design and optimization of a drone sowing device based on discrete element method
Xiaodong BIAN1, 2 , Chengsai FAN3, 4, Changqing CHEN1, 2 , Hongfeng YU3, 4, Tao ZHENG1, 2
Affiliations
  • 1.Jinhua Agricultural Science Research Institute, Jinhua 321017, China
  • 2.Jinhua Key Laboratory of Applied Agricultural Machinery in Hilly and Mountainous Areas, Jinhua 321017, China
  • 3.Nanjing Agricultural University, Nanjing 210095, China
  • 4.Jiangsu Key Laboratory of Intelligent Agricultural Equipment, Nanjing 210095, China
  • Corresponding Author:
    * CHEN Changqing, E-mail:

    BIAN Xiaodong, E-mail:

出版时间: 2026-02-15 doi: 10.12398/j.issn.2096-7217.2026.01.014
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针对丘陵地区人均耕地面积少,且土地比较分散,地形崎岖,大型农机作业效率低,甚至无法工作,小型农机有时也使用不方便的实际问题,基于无人机技术,设计了一种槽轮—撒种盘相结合的撒种装置。给出了槽轮—撒种盘相结合的撒种装置设计思路与优化仿真方案,以水稻种子为研究对象,基于离散元方法,用基础单元颗粒对水稻种子进行建模,利用离散元软件EDEM对撒种装置的排种过程进行模拟,主要理论分析撒种盘结构,发现撒种盘偏角、转速显著影响水稻种子在撒种盘上的分布,扇叶数量显著影响水稻种子在空气中的分布。为实现均匀撒播,借助离散元方法,以偏角、转速和扇叶数量为指标,设计了以撒种盘转速、扇叶偏角、扇叶数的3因素3水平的正交试验。仿真结果表明,最终优化得到撒种盘转速850 r/min、偏角50°、扇叶数为5个,其一致性变异系数为12.99%。验证试验分别针对飞行高度、播种量和飞行速度进行3组测试,结果显示实际分布变异系数最大值为24.25%,最小值为15.42%,飞行高度、播种量和飞行速度3个因素对应的水稻分布变异系数平均值分别为17.83%、20.90%、18.55%,基本能达到水稻飞播的农艺要求。通过对槽轮—撒种盘相结合的撒种装置的结构参数、离散元仿真和验证试验的研究分析,确定了槽轮—撒种盘相结合的撒种装置工作性能的最优参数,这些参数为飞机直播的研究以及在丘陵地区的实际应用打下了基础。

丘陵山区  /  无人机  /  水稻  /  撒播  /  槽轮  /  离散元仿真

In response to the practical issues faced in hilly areas, such as limited per capita arable land, scattered plots, rugged terrain, low efficiency of large agricultural machinery, and the occasional inconvenience of using small machinery, this paper designs a sowing device that combines a groove wheel and a sowing disk based on drone technology. The paper presents the design concept and optimization simulation plan for the combined sowing device, using rice seeds as the research subject. A discrete element method (DEM) is employed to model the rice seeds using basic unit particles. The sowing process of the device is simulated using DEM software EDEM, primarily analyzing the sowing disk structure. It is found that the angle of the sowing disk and its rotational speed significantly affect the distribution of rice seeds on the disk, while the number of blades significantly impacts the distribution of rice seeds in the air. To achieve uniform sowing, the study uses DEM to design an orthogonal experiment with three factors at three levels, focusing on the rotational speed of the sowing disk, the angle of the blades, and the number of blades. The simulation results indicate that the optimal seeding disc rotation speed of 850 r/min, deflection angle of 50° , and number of blades of 5 resulted in a uniformity coefficient of variation of 12.99%. Verification tests were conducted in three sets focusing on flight altitude, sowing amount, and flight speed. The results show that the maximum coefficient of variation for actual distribution is 24.25%, while the minimum is 15.42%. The average coefficients of variation for rice distribution corresponding to flight altitude, sowing amount, and flight speed are 17.83%, 20.90%, and 18.55%, respectively, which generally meet the agronomic requirements for rice aerial seeding. Through the research and analysis of the structural parameters, discrete element simulation, and field tests of the groove wheel and sowing disk combination, the paper identifies the optimal parameters for the operational performance of the sowing device. These parameters lay the groundwork for research on aerial seeding and its practical application in hilly areas.

hilly and mountainous area  /  drone  /  rice  /  sowing  /  sheave  /  discrete element simulation
边晓东, 樊成赛, 陈长卿, 余洪锋, 郑涛. 基于离散元的无人机撒播装置设计与优化. 智能化农业装备学报(中英文), 2026 , 7 (1) : 136 -144 . DOI: 10.12398/j.issn.2096-7217.2026.01.014
Xiaodong BIAN, Chengsai FAN, Changqing CHEN, Hongfeng YU, Tao ZHENG. Design and optimization of a drone sowing device based on discrete element method[J]. Journal of Intelligent Agricultural Mechanization, 2026 , 7 (1) : 136 -144 . DOI: 10.12398/j.issn.2096-7217.2026.01.014
  • 金华市农业类重点科技项目(2020-2-031)
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2026年第7卷第1期
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doi: 10.12398/j.issn.2096-7217.2026.01.014
  • 接收时间:2024-10-24
  • 首发时间:2026-11-03
  • 出版时间:2026-02-15
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  • 收稿日期:2024-10-24
  • 修回日期:2024-12-31
基金
Key Agricultural Science and Technology Projects in Jinhua City(2020-2-031)
金华市农业类重点科技项目(2020-2-031)
作者信息
    1.金华市农业科学研究院,浙江 金华,321017
    2.金华市丘陵山区适用农机重点实验室,浙江 金华,321017
    3.南京农业大学,江苏 南京,210095
    4.江苏省智能化农业装备重点实验室,江苏 南京,210095

通讯作者:

* 陈长卿,男,1980年生,贵州遵义人,正高级工程师;研究方向为现代农业技术装备。E-mail:
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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