基于机器视觉的网络变压器模块缺陷检测系统研究

针对电子元件缺陷传统人工检测方法存在劳动量大、检测效率和自动化程度低、成本高等问题,提出一种基于Halcon的视觉检测系统.针对研究对象的特殊性,提出两次采集、两次判断的多特征自动检测方法,并构建验证试验平台;利用CCD相机实时采集元件图像,再对图像进行中值滤波等预处理,降低图形噪声;采用阈值分割、Blob分析的方法对...

Research on Defect Detection System of Electronic Components Based on Machine Vision

In view of the problems in traditional manual inspection methods for electronic component defects,such as large amount of labor,low efficiency and automation,and high cost,a vision inspection system based on Halcon was proposed.According to the particularity of the research object,a multi-feature automatic detection method of twice acquisition and twice judgment was pro?posed,and a verification test platform was built;the CCD camera was used to acquire the component image in real time,and then the image was preprocessed with median filter to reduce the image noise.Finally,the methods of threshold segmentation and Blob analysis were used to recognize the morphological features of the image defect features and the judgment result was gotten.The experimental re?sults show that the detection method can be used to extract the defect features of electronic components quickly,accurately and effi?ciently.The average image processing time of a single image is 131 ms,and the average detection accuracy is 95%;on the other hand,the automatic control system has strong stability and high accuracy,the average detection cycle time of a single component is 4.7 s,and the detection efficiency is increased by 38%compared with manual detection,which meets the industrial requirements.