摘要
将机器视觉引入电镀件表面缺陷检测中,设计了一种基于机器视觉的电镀件表面缺陷检测系统。该系统由工控机、图像采集卡、工业相机、伺服电机、照明装置和运动控制卡组成。获取电镀件表面光学图像并经预处理后,利用算法提取出图像中缺陷区域边界特征,通过计算用于标记缺陷区域边界特征的白色像素点个数,并与设定的阈值做比较,实现电镀件表面缺陷检测。该系统满足电镀件表面缺陷在线检测的要求。
Computer vision was applied to detection of the surface defects of electroplated parts,and a surface defects detection system for electroplated parts based on computer vision was designed.This system was composed of industrial personal computer,image capture card,industrial camera,servo motor,lighting device and motion control card.The surface optical image of electroplated parts was obtained,and after the pre-processing,the boundary characteristics of defect area in the image was extracted and the number of white pixels for labeling the boundary characteristics of defect area was calculated.Comparing the calculated value with the predetermined threshold,then to realize the detection of the surface defects of electroplated parts.This system can meet the requirements of online detection of surface defects of electroplated parts.
引文
[1]于海,刘建华,李云飞,等.喷砂对镀镉层防护性能的影响及分析[J].电镀与精饰,2015,37(4):32-35.
[2]李定川.机器视觉原理解析及其应用实例[J].智慧工厂,2017(8):73-75.
[3]易贞弟.基于机器视觉的零件表面缺陷检测技术研究[D].沈阳:沈阳理工大学,2015.
[4]谢无极.电镀故障手册[M].北京:化学工业出版社,2013.
[5]李莎莎,邓彩霞,侯杰.基于图像融合技术的阶梯型边界检测[J].哈尔滨理工大学学报,2009,14(2):75-77.