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基于机器视觉的智能种子分选机设计

封玉搏 赵晓顺 范晓飞 田瑞涛 刘景艳 孙磊

中国农业大学学报2024,Vol.29Issue(8):204-212,9.
中国农业大学学报2024,Vol.29Issue(8):204-212,9.DOI:10.11841/j.issn.1007-4333.2024.08.17

基于机器视觉的智能种子分选机设计

Design of an intelligent seed sorting machine based on machine vision

封玉搏 1赵晓顺 1范晓飞 1田瑞涛 1刘景艳 1孙磊1

作者信息

  • 1. 河北农业大学机电工程学院,河北保定 071000
  • 折叠

摘要

Abstract

Current seed sorting machines on the market are mostly traditional mechanical or semi-automatic type,which have low automation level and low sorting accuracy.In view of the problem,an intelligent seed sorting machine was designed based on machine vision technology.It is composed of transmission system,seed-feeding system,image acquisition system,seed-screening system and control system.Taking the'Zheng Dan 958'corn seeds as the research object,the horizontal distance of the seed flow and the transmission speed of the conveyor belt is tested as the preferential conditions to determine the pressure value of the optimal air pump and the controller pulse frequency.A total of 960 seed samples(The number of high-quality and inferior seeds was 824 and 136,respectively.)are identified by the target detection model.The quality of the seeds was evaluated,and the seed state is marked and coordinate recorded.The PLC(SIMATIC S7-200 CN,CPU224XP)sorting module was used to control the direct-action solenoid valve set to perform sorting tests on the seeds.The results show that:1)The pressure value of the optimal combination air pump is 0.3 MPa,and the controller pulse frequency is 3 175 Hz.2)The recognition rate of high quality and inferior seeds was 93.69%and 91.91%,respectively,and the seed sorting rate was 89.6%.In conclusion,the machine can effectively meet the seed sorting requirements.

关键词

机器视觉/分选机/种子/线扫描相机/PLC

Key words

machine vision/seed sorting machine/seed/line scan camera/PLC

分类

农业科技

引用本文复制引用

封玉搏,赵晓顺,范晓飞,田瑞涛,刘景艳,孙磊..基于机器视觉的智能种子分选机设计[J].中国农业大学学报,2024,29(8):204-212,9.

基金项目

国家大宗蔬菜产业技术体系(CARS-23) (CARS-23)

河北省重点研发计划项目(20327403D) (20327403D)

河北省省属高校基本科研业务费项目(KY2022020) (KY2022020)

中国农业大学学报

OA北大核心CSTPCD

1007-4333

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