基于机器视觉的线束末端包覆质量检测系统研究

目的为了自动、准确地识别汽车线束末端包覆质量,以工业机器人和工业相机为基础,设计一种基于机器视觉的汽车线束末端包覆质量检测系统。方法该系统使用置于工业机器人手臂的CCD工业相机采集图像信息,首先运用HALCON对系统进行标定,其次通过梯度腐蚀等预处理,角点检测等方法得到线束的节点坐标,然后以归一化匹配标准为基础,提出多区域双层的多阈值模板匹配算法对线束末端包覆质量快速识别,计算线束末端未包覆长度并得到线束节点坐标修正值,最后进行未包覆段补包。结果实验表明,此系统在检测端末节点数少于10个的线束末端包覆质量的准确度维持在97.22%以上。补包后偏差量的绝对值小于2 mm,且重复性精度为1.07 mm。结论该检测系统稳定可靠,能满足实际生产中对线束包覆质量的检测,提高了线束包覆生产线的自动化和智能化水平。

Detection System for Harness End Coating Quality Based on Machine Vision

The paper aims to design a detection system for harness end coating quality based on machine vision on the basis of industrial robot and industrial camera to automatically and accurately identify the end coating quality of au-tomotive harnesses. The CCD industrial camera placed in the industrial robot arm was used in the system to collect image information. First, the system was calibrated by HALCON. Secondly, the gradient coordinates and other preprocessing, corner detection and other methods were used to obtain the node coordinates of the harness. And then, based on the normalized matching standard, the multi-region double-layer multi-threshold template matching algorithm was proposed to identity the end-wrapping quality of the harness quickly, calculate the uncoated length of the end of the harness, and obtain the correction value of the harness node. Finally, the unwrapped segment was replenished. The experiment showed that the accuracy of the coating quality at the end of the harness with less than 10 nodes at the end of the detection system was maintained above 97.22%. The absolute value of the deviation after the replenishment was less than 2 mm, and the repeatability accuracy was 1.07 mm. The detection system is stable and reliable, can meet the detection requirement of wire bundle coating quality in actual production. It improves the automation and intelligence level of the harness coating production line.