摘要
针对植物叶面积采集操作繁琐的现状,以及过于依赖于人力、智能化差等问题,提出了番茄叶面积智能采集的方法,开发了番茄叶面积智能采集系统,并对系统的运动精度、稳定性进行试验研究。所开发的番茄叶面积智能采集系统软件主要包含运动控制程序、传感器数据采集程序、实时位置显示程序、数据的显示与储存程序、三维模型拟合程序以及串口通信程序的6个模块。智能采集系统验证试验结果表明:总面积和投影面积的误差值分别为1.02%和0.64%,垂直投影总面积值误差率为0.42%,所得误差在误差允许范围内,验证了智能采集方法的科学性,证明了番茄叶面积智能采集系统的准确性,能够满足设施农业精准化和智能化的要求。
The operation of leaf area data collection is very complicated.There are some problems in the process of data collection,such as too much reliance on human resources and low degree of intelligence.In this paper,the intelligent acquisition method of tomato leaf area is proposed,and the intelligent acquisition system of tomato leaf area is developed,and the motion precision and stability of the system are tested too.The software of tomato leaf area intelligent acquisition system developed mainly includes six modules:motion control program,sensor data acquisition program,real-time position display program,data display and storage program,three-dimensional model fitting program and serial communication program.The verification test results of intelligent acquisition system software show that the error values of total area and projection area are 1.02%and 0.64%respectively,and the error rate of total vertical projection area is 0.42%.The obtained error is also within the allowable error range,which verifies the scientificity of the intelligent acquisition method proposed and the accuracy of the intelligent acquisition system of tomato leaf area,it can meet the requirements of precision and intelligence of facility agriculture.
作者
贺峰
杨青丰
刘思雨
He Feng;Yang Qingfeng;Liu Siyu(Changzhou Vocational College of Information Technology,Changzhou 213000,China;Changzhou Industrial Internet Industry Technology Research Institute,Changzhou 213000,China;Changzhou Industrial Internet Research Institute Co.,Ltd.,Changzhou 213000,China)
出处
《农机化研究》
北大核心
2022年第11期155-158,共4页
Journal of Agricultural Mechanization Research
基金
江苏省教育厅高等学校自然科学研究计划项目(18KJB480001)
常州信息职业技术学院自然科学研究项目(CX ZK201805Q)
校级科研平台智慧教育工程中心项目(CXPT201701G)
常州信息职业技术学院校级科研课题(CXZK 202011Z)
常州信息职业技术学院校级课题(2020CXJ G22)。
关键词
智能采集
实时监控
三维模型
番茄叶面积
intelligent collection
real-time monitoring
three-dimensional model
tomato leaf area