摘要
为了解决电子元件蜂鸣器出厂时人工质检效率低、容易伤害分拣人员听觉等问题,设计了基于机器视觉的电子元件在线质检分类系统。该系统主要由自动上料、视觉检测、声音检测、电极控制和下料控制这5个部分组成,由PLC主控制器、OpenMV视觉检测模块、声音识别模块以及步进电机等配合完成蜂鸣器的自动上料、检测和等级分类功能。经过现场调试及应用表明,该控制系统提高了蜂鸣器的质检分类效率,其效率是人工质检的1.9倍,准确率提高了9.4%,每台设备至少替代3名工人,节约了企业的成本。
In order to solve the problem that the manual quality inspection of the buzzer was inefficient and easy to damage the hearing of the sorter,the electronic component quality inspection and classification system based on machine vision was designed.The system was mainly composed of five parts:automatic feeding,visual inspection,sound detection,electrode control and unloading control.The PLC main controller,OpenMV vision inspection module,voice recognition module,and stepping motor were used cooperatively to complete the buzzer automatic feeding,detection and grade classification.On-site debugging and application shows that the control system improves the efficiency of the buzzer quality inspection and classification in which the efficiency is 1.9 times of manual,the accuracy rate is increased by 9.4%and at least 3 workers are replaced by each equipment,which saves cost for the enterprise.
作者
王丹
杨江照
WANG Dan;YANG Jiangzhao(School of Mechanical and Electrical Engineering,Guangdong University of Science and Technologly,Dongguan 523083,China;Googol Paradox(Dongguan)Intelligent Technology Co.,Ltd.,Dongguan 523808,China)
出处
《现代制造工程》
CSCD
北大核心
2021年第2期139-144,133,共7页
Modern Manufacturing Engineering
基金
广东省普通高校青年创新人才项目(2020KQNCX104)
东莞市社会科技发展项目(2020507154647)
广东科技学院校级项目(GKY-2019KYYB-6)。
关键词
蜂鸣器
机器视觉
声音识别
可编程逻辑控制器
质检
buzzer
machine vision
voice recognition
Programmable Logic Controller(PLC)
quality inspection
作者简介
王丹,硕士研究生,研究方向为智能装备控制算法、机器视觉等。E-mail:wangdanhbyc@163.com。
