基于机器视觉的电缆绝缘护套断裂伸长率测量系统

X. Su, Gangwei Wang, Zhiqiang Zhang, Jiale Yang, Zhijia Zhang
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引用次数: 0

摘要

在电力电缆的生产中,电缆绝缘护套的性能测试是一个重要的组成部分。与传统的测试方法相比,机器视觉具有运行稳定、精度高、效率高等优点。针对这种情况,首先基于机器视觉理论,对老式拉伸机的结构进行了重构,利用CMOS相机对电缆绝缘护套拉伸试验的整个过程进行了成像,并提出了颜色识别算法、有效面积分割算法和工件;采用断裂判断检测算法和腐蚀差分算法,计算出标线之间的距离,进而计算出电缆材料断裂时的伸长率。通过对同一批电缆护套的系统试验,目测所得断裂伸长率偏差最大,不超过1%。实验结果和实际应用表明,基于机器视觉的视觉检测系统比传统的检测系统具有更高的精度、更快的效率和更稳定可靠的运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring system for elongation at break of cable insulation sheath based on machine vision
In the production of power cables, the performance test of the cable insulation sheath is an important part. Compared with traditional testing methods, machine vision has the advantages of stable operation, high precision, and high efficiency. Because of this situation, firstly, based on machine vision theory, the structure of the old-fashioned tensile machine was reconstructed, and the whole tensile test process of the cable insulation sheath test was imaged by a CMOS camera, and the color recognition algorithm, effective area segmentation algorithm, and workpiece were proposed. The fracture judgment detection algorithm and the corrosion difference algorithm are used to calculate the distance between the marked lines and then calculate the elongation at the break of the cable material. Through systematic experiments on the same batch of cable jackets, the deviation of the elongation at break measured by visual inspection is the largest, no more than 1%. The experimental results and practical applications show that the machine vision-based visual inspection system has higher accuracy, faster efficiency, and more stable and reliable operation than the traditional inspection system.
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