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基于机器视觉的水稻秧盘育秧智能补种装置设计与试验
引用本文:王桂莲,刘伟超,王安,柏凯凯,周海波.基于机器视觉的水稻秧盘育秧智能补种装置设计与试验[J].农业工程学报,2018,34(13):35-42.
作者姓名:王桂莲  刘伟超  王安  柏凯凯  周海波
作者单位:天津市先进机电系统设计与智能控制重点实验室机电工程国家级实验教学示范中心(天津理工大学);佳木斯大学信息电子技术学院;佳木斯大学机械工程学院
基金项目:国家自然科学基金资助项目(51275209);黑龙江省普通高等学校青年学术骨干支持计划项目(1251G061);佳木斯大学自然科学研究面上项目(13Z1201575);大学生创新创业训练计划项目资助(201810060001)
摘    要:对于工厂化育秧作业的水稻、蔬菜、花卉等,尤其是超级杂交稻,其机械化秧盘育秧播种的理想目标为2~3粒/穴,且普遍存在空穴和单粒穴的情况,为了保证秧盘育秧成秧率,提高精密播种合格率就显得非常重要。该文基于机器视觉技术,提出了一种智能补种方法,设计并研制了智能补种装置,主要用于超级杂交稻钵体秧盘育秧播种质量检测与补种过程。首先利用CCD摄像头采集秧盘图像,对图像处理与分析后得到空穴和1粒穴位置坐标,再利用定位机构和补种机构实现从种槽取种和对秧盘指定位置动态补种等功能。应用LabVIEW图形化编程软件,针对空穴和单粒穴的补种方案,开发出秧盘播种质量在线检测与补种运动控制系统,实现了智能补种任务。由试验结果统计可知,当补种率小于2%时,双补种器能够满足450盘/h的生产需求。

关 键 词:农作物  设计  机器视觉  水稻  精密播种  智能补种  智能补种装置  质量检测
收稿时间:2017/12/8 0:00:00
修稿时间:2018/5/5 0:00:00

Design and experiment on intelligent reseeding devices for rice tray nursing seedling based on machine vision
Wang Guilian,Liu Weichao,Wang An,Bai Kaikai and Zhou Haibo.Design and experiment on intelligent reseeding devices for rice tray nursing seedling based on machine vision[J].Transactions of the Chinese Society of Agricultural Engineering,2018,34(13):35-42.
Authors:Wang Guilian  Liu Weichao  Wang An  Bai Kaikai and Zhou Haibo
Institution:1. Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, National Demonstration Center for Experimental Mechanical and Electrical Engineering Education , Tianjin 300384, China;,1. Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, National Demonstration Center for Experimental Mechanical and Electrical Engineering Education , Tianjin 300384, China;,2. College of Information Electronic Technology, Jiamusi University, Jiamusi 154007, China;,1. Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, National Demonstration Center for Experimental Mechanical and Electrical Engineering Education , Tianjin 300384, China; and 1. Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, National Demonstration Center for Experimental Mechanical and Electrical Engineering Education , Tianjin 300384, China; 3. College of Mechanical Engineering, Jiamusi University, Jiamusi 154007, China;
Abstract:Super hybrid rice is a kind of rice variety that provides excellent quality and high yield. Super hybrid rice is very popular as a large-scale rice crop in China. The precision seeding of tray nursing seedling requires (2±1) seeds per hole. At present, the performance of seed metering devices can reach 1-4 seeds per hole, but the rate of single seed is high (more than 20%), and there are cavities. Due to the factors such as the germination rate, survival rate, characteristics of blanket and injured seedling rate, the seeding results cannot reach 1-2 plants per hole. Therefore, seeding target should be raised to 2-3 seeds per hole, which will reduce single-grain rate and eliminate the presence of cavities. When the seedlings for planting rice, vegetables, flowers, and so on, especially the super hybrid rice were used to mechanized seeding, the situation of cavity and single seed commonly exists. In order to achieve the goal of digital and intellectual precision seeding, which is difficult to achieve by the traditional seeding device or seed metering device, focusing on imitating the manual sowing principle with the monocular camera as eyes, the vision inspection systems as the brain, and the hill-drop device performing hand movements, this paper presents a new method of intelligent reseeding based on machine vision technology, and develops an intelligent reseeding devices, which is mainly used for quality detection and compensating seeds of the super hybrid rice. Firstly, the image of seedling tray was collected by CCD (charge coupled device) camera, the positions of cavities and the holes of single seed were obtained by image processing and analysis, and then the positioning mechanism and reseeding mechanism were used to realize the function of picking up the seed from seed groove and dynamically reseeding on the designated location. Applying LabVIEW graphical programming software, on-line testing and motion control system of seedling planting quality was developed to realize the task of intelligent reseeding. According to the statistics of the test results, the hill-drop machine can meet the production requirements of 450 trays per hour and the average reseeding time per hole was about 2.48 s when the reseeding rate was less than 2%. The average processing time of an image was about 0.518 s, and the accuracy was more than 95%. The paper achieves the intelligent reseeding according to the required number of seeds per hole. As a new precision seeding technology, the method will raise the level of planting accuracy, and have important scientific significance and application prospects. However, in the practical application of intelligent reseeding, considering the single dibbler''s working efficiency is still relatively low, the integrated design method can be used with 2-3 seeding devices according to reseeding rate and productivity, or the lightweight, fast reseeding mechanism, such as SCARA, parallel or serial manipulator, which can play a better advantage of intelligent reseeding. In addition, with the rapid development of robot technology, the cost of intelligent dibbler will become lower and lower, and the efficiency will be higher and higher.
Keywords:crops  designs  machine vision  rise  precision seeding  intelligent reseeding  intelligent reseeding devices  quality detection
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