基于增强滤波和特征聚类分析的导线隐患识别技术研究与应用

Research and application of traverse hidden trouble identification technology based on enhanced filter and feature clustering analysis

及时发现输电线路导线隐患是保障线路安全运行的关键,鉴于现有巡检图像处理过程中存在的不足,本研究在国内外已有研究成果的基础上进行了算法优化,提出了一种基于增强滤波和特征聚类分析的导线隐患识别算法。实验测试表明该算法对于线路巡检图像中的处理速度和识别准确率均优于传统算法,能够快速准确地实现导线提取和隐患的识别。由于该算法对硬件配置要求较低,能够在巡检现场完成对图像的分析和处理,具有较大的实用价值。

It is the key to ensure the safe operation of transmission line to find the hidden danger in time.In view of the existing shortcomings in the inspection image processing,this study optimized the algorithm based on the existing research results at home and abroad,and proposed a hidden danger identification algorithm based on enhanced filtering and feature clustering analysis.Experimental tests show that the algorithm is superior to the traditional algorithm in processing speed and recognition accuracy in line inspection image,and can quickly and accurately realize wire extraction and hidden trouble identification.Because the algorithm has low requirements on hardware configuration,it can complete image analysis and processing on inspection site,so it has great practical value.