基于机器视觉的馈线终端单元插口状态自动识别系统研究

针对不同类型馈线终端单元FTU(Feeder Terminal Unit)检测中的插口状态自动识别问题,设计了基于机器视觉的FTU插口状态自动识别系统。该系统由工控机,图像采集处理模块和工业机器人组成,通过CCD相机与图像采集卡采集并处理图像,应用了中值滤波、灰度化、畸变矫正、相机标定等图像处理环节简化计算的方法,提出了FTU航插口的位置和角度偏差计算方法以及FTU插口视觉特征增强方法。上述方法解决了FTU自动化检测流程中插口识别准确性差、效率低等问题,提高了检测作业的自动化程度,降低了人工带电作业的安全隐患。

Research on The Automatic Recognition System of Socket Status of Feeder Terminal Unit Based on Machine Vision

The problem of cable insertion for different types of distribution terminal FTU (Feeder Terminal Unit) in the detection is increasingly prominent. An automatic recognition system of socket status based on machine vision was designed to solve the problem above. The system consists of an industrial computer, an image acquisition processing module and an industrial robot. The image is collected and processed by CCD camera and image acquisition card. The details of image processing techniques such as median filtering, grayscale, distortion correction and camera calibration are utilized to simplify the following calculation. The calculation method of position and angle deviation and the method of vision characteristics of FTU navigation socket are proposed. The system solves the problem of poor accuracy and low efficiency of insertion in the automatic inspection process of FTU, improves the automation degree, and avoids the safety hazard of manual live working.