基于机器视觉的硬质合金微型喷嘴缺陷检测

针对现有人工目检方法对精加工硬质合金微型喷嘴产品表面检测存在速度慢、缺陷漏检率和误检率高等问题,提出一种基于机器视觉的喷嘴图像缺陷检测方法.分析了喷嘴缺陷图像类型和喷嘴结构,重点研究了喷嘴缺损圆边缘拟合、疤料边缘增强、极坐标变换和缺陷灰度值差异统计等.该方法避免了喷嘴的复杂结构对缺陷定位和检测造成的大量计算.通过对合格...

Defect Detection of Carbide Micro nozzle Based on Machine Vision

There are some problems such as slow speed, high rate of defect omission and false detection when the existing manual visual inspection method is used to inspect the surface quality of precision machined carbide micro nozzle. In order to solve the above problems, a method for detecting nozzle image defects based on machine vision was proposed. The nozzle defect image type and nozzle structure were analyzed, the nozzle defect circle edge fitting, scar edge enhancement, polar transformation and defect gray value difference statistics were heavily studied. By using this method, a lot of calculations for defect location and detection caused by the complex nozzle structure were avoided. Through the detection of qualified and unqualified nozzles, the accuracy of the defect detection method was verified to be 98.6% and the detection time of each piece was about 0.834 s, while the accuracy of the manual visual inspection was about 91.2%, and the detection time of each piece was about 5.213 s. So this algorithm can effectively improve the detection accuracy and speed, and meets the requirements of nozzle detection accuracy and real time performance in industrial production lines.