基于机器视觉的齿轮自适应测量系统设计

Design of Gear Adaptive Measurement System Based on Machine Vision

针对采用传统方法进行齿轮测量时容易遇到测量困难与测量效率低等问题,设计了一种基于机器视觉的齿轮自适应测量系统,由机器人结合视觉定位将齿轮抓取至检测平台,利用Halcon图像处理软件提取齿轮对应参数,根据齿轮参数自动生成合适的阈值以完成多批齿轮共同测量,同时机器人利用测量信息对所测齿轮进行分组。研究结果表明,系统可以识别出不同类型的齿轮,齿轮的参数检测精度误差可以达到±0.02mm,图像系统响应时间为0.2262s,该系统大大提高了测量效率,降低了测量所需的人工成本。

Aiming at the problems of difficulty in measurement and low measurement efficiency when using traditional methods to measure gears,a gear adaptive measurement system based on machine vision is designed.The processing software extracts the parameters corresponding to the gears,and automatically generates appropriate thresholds according to the gear parameters to complete the joint measurement of multiple batches of gears.At the same time,the robot uses the measurement information to group the measured gears.The research results show that the system can identify different types of gears,the parameter detection accuracy error of the gears can reach±0.02mm,and the response time of the image system is 0.2262s.The system greatly improves the measurement efficiency and reduces the labor cost required for measurement.