气吸振动式播种机定量供种装置设计及试验研究

发布时间：2018-03-05 08:50

本文选题：精密播种机　切入点：定量供种　出处：《江苏大学》2017年硕士论文　论文类型：学位论文

【摘要】：工厂化水稻育秧设备可以提高水稻作物产量,气吸振动式精密播种机作为工厂化水稻育秧设备的一种,对种子不需要分级精选、不伤种,因而具有很好的应用前景。相关研究人员已从影响其吸排种系统工作的因素:吸盘气流场种子受力、振动种盘内种群的运动规律等方面进行了广泛深入的研究,并给出了具体的建议,提升了播种效果。但现有播种机在播种过程中依然依靠人工加种和检测播种效果,劳动量大、自动化程度低,针对以上问题,本文开展的主要研究工作如下:设计了一种在播种间歇时进行自动补种的定量供种装置,以解决原有加种装置人工重复劳动、无法实现自动定量供种的问题。供种装置机械部分主要由步进电机支撑板、窝眼轮、旋转轴、轴承及联轴器组成,控制及执行部分主要由PLC控制器、触摸屏、步进电机、光电传感器部分组成。基于EDEM进行仿真试验与分析以确定窝眼型孔的参数;根据播种机的工作过程,确定了供种装置与吸排种系统在工作过程中的间歇关系,采用光电传感器计数播种盘数、PLC控制步进电机带动窝眼轮旋转进行补种的方法;自动定量供种装置可以实现在播种间歇时进行自动定量供种。为了检测播种机加上自动定量供种装置后的播种效果,验证供种装置设计的合理性,设计了基于机器视觉和GABP算法的播种效果检测系统试验平台,试验平台硬件主要包括摄像镜头、光源组成的育秧盘图像采集系统,软件主要包括LABVIEW图像采集和结果显示模块,以及MATLAB图像信息处理模块。进行了播种试验,验证了预设的播种盘数的合理性及供种装置在实际播种时的加种效果。以超级稻为播种对象进行了定量供种试验,试验结果表明:每播种10盘、15盘、20盘,由供种装置进行加种后,播种平均合格率分别为91.96%,90.98%,90.31%。考虑每盘播种合格率和工作效率,确定每播种15盘由供种装置加种;在保持真空压力、振动种盘振幅和频率等条件不变的情况下,进行了播种检测试验,加种后连续播种15盘,各盘播种合格率均在90%以上,平均合格率91.30%。人工检测和系统检测的播种平均合格率分别为92.15%,88.26%,相对误差为4.2%,检测算法平均用时为1.118s。播种平均合格率大于90%,供种效果达到预期目标,验证了供种装置的合理性。
[Abstract]:Industrial rice seedling raising equipment can improve the yield of rice crops. As one of the industrial rice seedling raising equipment, the precision seeder of air suction vibration type does not need to grade and select the seeds and do not hurt the seeds. Therefore, it has a good prospect of application. Researchers have carried out extensive and in-depth studies on the factors that affect the work of the suction and drainage system, such as the force on the air flow field on the sucker, the movement law of the population in the vibrating seed disk, and so on. Some specific suggestions are given to improve the seeding effect. However, the existing seeding machines still rely on artificial seeding and testing seeding effect in the process of seeding, which has the advantages of large amount of labor and low degree of automation, aiming at the above problems. The main research work in this paper is as follows: a quantitative seed feeding device is designed to solve the problem of artificial repeated work of the original seed feeding device. The mechanical part of the seed feeding device is mainly composed of step motor support board, hole wheel, rotary shaft, bearing and coupling, and the control and execution part is mainly composed of PLC controller, touch screen, step motor, etc. According to the working process of the seeder, the intermittent relationship between the seeding device and the sucking and metering system in the working process is determined. The method of using photoelectric sensor to count the seeding plate and PLC to control the stepper motor to drive the rotation of the hole wheel to make up the seed; In order to test the seeding effect of seeding machine and automatic quantitative seed supply device, the design of seed supplying device is reasonable. The experiment platform of seeding effect detection system based on machine vision and GABP algorithm is designed. The hardware of the test platform mainly includes the image acquisition system composed of camera lens and light source. The software mainly includes LABVIEW image acquisition and result display module. And MATLAB image information processing module. Seeding experiment was carried out to verify the rationality of the preset seeding disc number and the effect of seed feeding device in actual seeding. The quantitative seeding experiment was carried out with super rice as the seeding object. The test results show that the average qualified rate of seeding is 91.96 ~ 90.98 ~ 90.98 ~ 90.31 / 10 / 10 / 10 / pan / 15 / L / 20 / L, respectively, after seeding is added by the seeding device. Considering the qualified rate and working efficiency of each tray, it is determined that the seed is added to each seeding plate by the seeding device, and the vacuum pressure is maintained. Under the condition that the vibration seed disc amplitude and frequency are not changed, the test of seeding is carried out. After continuous seeding of 15 discs, the qualified rate of seeding of each disc is above 90%. The average qualified rate was 91.30.The average qualified rate of seeding was 92.158.26, the relative error was 4.2, the average time of the detection algorithm was 1.118s, the average qualified rate of seeding was more than 90, the seed supply effect reached the expected goal, and the reasonableness of the seed supplying device was verified.
【学位授予单位】：江苏大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：S223.2

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