基于PLC和粒子群算法的采摘机械手电气控制系统  

Electric Control System of Picking Manipulator Based on PLC and PSO

作　　者：朱文琦[1] Zhu Wenqi(Henan Polytechnic Institute,Nanyang 473000,China)

机构地区：[1]河南工业职业技术学院,河南南阳473000

出　　处：《农机化研究》2021年第12期238-241,246,共5页Journal of Agricultural Mechanization Research

基　　金：河南省科技发展计划项目(182102310750)。

摘　　要：为了提高采摘机械手电气控制系统的控制效率,基于PLC控制器,结合计算机图像处理技术,提出了一种基于粒子群的控制系统优化算法。通过对待采摘果实图像的识别和定位,利用粒子群算法规划出最佳的采摘顺序,缩短采摘机械手的末端移动距离,提高作业效率。为了验证该方案的可行性,以真实的青椒采摘生长环境为图像采集的对象,对采用和不采用粒子群算法时机械手移动末端的距离和采摘精度进行了测试。结果表明:采用粒子群算法可以有效性地提高果实采摘的定位识别精度,缩短了移动距离,对于提高作业效率具有明显的作用。In order to improve the control efficiency of the electrical control system of the picking manipulator, it proposed a control system optimization algorithm based on particle swarm optimization(PSO) based on PLC controller and computer image processing technology. Through the recognition and positioning of the picking fruit image, PSO algorithm is used to plan the best picking sequence, shorten the end moving distance of the picking manipulator, and improve work efficiency. In order to verify the feasibility of the scheme, taking the real green pepper picking and growing environment as the object of image collection, it tested the distance and picking accuracy of the manipulator moving end with and without particle swarm optimization algorithm. The test results show that the particle swarm optimization algorithm can effectively improve the positioning and recognition accuracy of fruit picking, shorten the moving distance, and improve the work efficiency with obvious effect.

关 键 词：采摘机械手 电气控制系统 粒子群算法 PLC控制器 定位识别 

分 类 号：S225[农业科学—农业机械化工程] TP273[农业科学—农业工程]