定期对球罐等承压设备的焊缝进行磁粉检测是保障其安全的重要措施，发展基于爬壁机器人的磁粉检测系统是球罐自动检测作业的重要方向。爬壁检测机器人携带有视觉传感器，可实时采集磁粉检测结果。故，磁粉检测图像的快速自动缺陷分析是实现爬壁检测机器人的重要研究基础。通过图像像素分析法，对视觉传感器收集的实时图像进行自动识别，并将图像快速自动分拣归类到无缺陷、有缺陷及可疑图像等3个文件夹，以协助磁粉检测人员快速识别焊缝缺陷。

Periodic magnetic particle testing of the welds of pressure equipment such as spherical tanks is an important measure to ensure its safety. The development of magnetic particle testing system based on wall climbing robot is an important step towards the automatic inspection of spherical tanks. The wall climbing inspection robot carries a visual sensor to collect magnetic particle testing images in real time. Therefore, the rapid automatic analysis of magnetic particle testing images is an important research content of the wall climbing inspection robot. In this study, the image pixel analysis method was used to automatically identify the real-time images collected by the visual sensor. The images were quickly and automatically picked into three identical folders, named defect-free folder, defective folder and risk categories folder. The system is to assist the magnetic particle tester to identify weld defects quickly.