摘要
为了解决曲轴轴肩部位加工质量检测过程耗时长、效率低的问题,面向实际应用,开发了一种基于视觉的曲轴轴肩加工质量高效检测方法与检测系统。根据曲轴轴肩磨削加工过程中尺寸超差的原因,制定了轴肩尺寸公差超限的图像检测判据,设计了曲轴零件的载物成像、光源系统及检测平台,提出了轴肩尺寸超差的高效检测算法。实验结果表明:开发的视觉检测系统操作简单、使用方便,对轴肩尺寸超差检测的准确率为100%,大大提高了检测效率,可用于多种轴类零件的检测。
In order to improve the detecting efficiency of the crankshaft shoulder, a machine vision system for crankshaft rapid de- tecting was developed. Firstly, according to the crankshaft grinding process and the producing principle of over limit error, the im- age identifying criterion to judge the acceptable crankshaft part and the nonconforming product was provided. Secondly, the detec- tion platform of the crankshaft with part-hold and light imaging system was designed. Some high-efficiency image processing algo- rithms was described. Finally, the vision system performance testing experiments were carried out. Experimental results indicate that the detecting accuracy rate of the crankshaft vision detection system is 100% and the detection system is easy to use. The de-tecting system has high measurement efficiency, which could be used to check many shaft parts in manufacture.
出处
《现代制造工程》
CSCD
北大核心
2017年第3期122-125,共4页
Modern Manufacturing Engineering
基金
北京市重点学科建设项目(2015NCUTXN017)
关键词
机器视觉
零件检测
曲轴轴肩
图像处理
computer vision
parts detection
crank shaft shoulder
image processing