摘要
介绍了一种基于图像识别技术的电动工具视觉检测系统。机器视觉传感器采集被测物体图像后,将原始数据送入图像识别检测模块,该模块由机器视觉算法和深度学习的图像处理技术组成,利用图像采集技术对可视化检测项目进行建模分析。实际应用表明,电动工具视觉检测系统的测量效果优于人工光学检测,避免了人为因素造成的检测误差。
The visual inspection of electric tools in our country shows the characteristics of backward inspection equipment and low reliability.In this paper,a visual inspection system for electric tools based on image recognition technology is introduced.The system uses machine vision sensors to collect images of the object under test,the original data is sent to the image recognition and detection module,which is composed of machine vision image algorithm and depth learning related image technology,at the same time,the visual detection project is modeled and analyzed by using image acquisition technology,and the hardware and software of the detection and control system for electric tools are described emphatically,including the motor,image acquisition,and its related applications have been analyzed and studied.
作者
徐健康
朱正兵
杨德志
许莹
胡帅
胡卓星
Xu Jiankang;Zhu Zhengbing;Yang Dezhi;Xu Ying;Hu Shuai;Hu Zhuoxing
出处
《电动工具》
2024年第1期1-3,22,共4页
Electric Tool
基金
浙江省市场监督管理局青年项目(QN202344)。
关键词
电动工具
产品质量
图像识别
深度学习
检测
electric tools
product quality
image recognition,visual detection,power tools
depth learning
detection
