基于机器视觉技术的电缆结构参数检测系统研究

摘要:

随着电力技术的快速发展,电力基础设施电缆化程度不断提升,各种电缆故障和事故亦愈加频发。为了提高电力工程中电缆入场和安装前结构参数检测精度,有效预防和减少物理缺陷对电缆安全稳定运行造成的隐患,研究了基于机器视觉技术的电缆结构参数检测系统。该系统通过机器视觉模块实时采集电缆截面图像,通过优化图像处理算法并开发检测程序,拓宽现场条件下电缆结构尺寸参数可检测种类,实现检测数据的保存和输出。非接触检测的便捷性和数据的可追溯性,有利于纵向提升电缆入场和安装前的质量管控精准度。通过对比分析及现场测试表明该系统具有良好的实际操作性和较强的实用价值。

Abstract:

With the rapid development of power technology,the degree of power infrastructure cabling is increasing,and various cable failures and accidents happen more frequently. In order to improve the detection accuracy of cable structure parameters before entering into the site and installation,and to effectively prevent and reduce the hidden dangers caused by physical defects for the safe and stable operation of cables,a cable structure parameter detection system based on machine vision technology is studied. The system collects the section images of cable in real time through machine vision module,optimizes the image processing algorithm and develops the detection program,widens the types of cable structure size parameters that can be detected under the field conditions,and realizes the storage and output of detection data. The convenience of non-contact detection and the traceability of data are conducive to improving the accuracy of quality control before cable entry and installation. Through comparative analysis and field test,it shows that the proposed system has a good practical operation and strong practical value.