摘要
针对铝合金零件的高反光、尺寸较大导致难以检测的问题,对机器视觉系统、图像合成、图像处理等方面进行了研究,提出了基于机器视觉的铝合金零件尺寸误差的自动检测方法。采用同轴平行光源在零件上方打平行光和两轴运动平台采集局部高精度图像并拼接合成的方法,获取了高精度大尺寸零件图,提高了检测精度并可突破检测尺寸局限;利用视觉检测技术实现了图像的预处理、尺寸特征量提取等的处理,采取Canny算子结合双线性插值方法提取了零件亚像素级边缘,提高了检测精度,通过将提取的零件边缘图像与标准零件CAD图匹配、判识,完成了零件尺寸的测量分析。研究结果表明:该铝合金零件检测方法实现检测精度高于0.02 mm,可满足铝合金零件生产现场自动检测的要求。
Aiming at the problems of the reflection-light interference and the difficulty of detecting large size aluminum alloy parts in the dimension errors detection process,the machine vision system,image synthesis,and image processing were studied.Then,an automatic detection method based on machine vision system was proposed.The high precision images for large size parts were obtained by using a coaxial parallel light system and a two-axis motion platform.In order to obtain a higher detection accuracy,the local high precision images were captured and then spliced together to rebuild the whole image of the aluminum alloy part,which allows this method to detect large size parts without size limitation.The preprocess and feature extraction of the obtained images were performed by visual inspection technology.The part edges were extracted by using Canny operator combined with bilinear interpolation method,which can obtain sub-pixel precision for the part edges.The dimension errors of aluminum alloy parts were determined by matching these processed images with the CAD drawings.The results indicate that the detection accuracy is higher than 0.02mm,which can meet the requirement of the automatic detection for the aluminum alloy part manufacture.
作者
冯淼
周传德
孟明辉
FENG Miao;ZHOU Chuan-de;MENG Ming-hui(College of Mechanical and Power Engineering,Chongqing University of Science and Technology,Chongqing 401331,China)
出处
《机电工程》
CAS
北大核心
2018年第4期380-384,共5页
Journal of Mechanical & Electrical Engineering
基金
国家自然科学基金资助项目(51205431)
重庆科技学院研究生科技创新计划项目(YKJCX1620302)
关键词
机器视觉
铝合金零件
图像合成
模板匹配
machine vision system
aluminum alloy parts
image synthesis
template matching
