高压输电区域性重覆冰线路受损监测系统设计

通过对高压输电区域性重覆冰线路受损监测,提高高压输电稳定性,提出一种基于视觉特征重构的高压输电区域性重覆冰线路受损监测方法,并结合多层嵌入式构架进行系统设计。构建高压输电区域性重覆冰线路受损监测的视觉采集模型,采用激光扫描和红外分析方法进行高压输电区域性重覆冰线路受损部位的图像重构,构建高压输电区域性边缘轮廓检测模型,结合模板特征匹配方法进行高压输电区域性重覆冰线路受损部位检测,提取高压输电区域性重覆冰线路受损部位的异常特征信息,结合机器学习方法对提取的特征信息进行自动分类和人工智能识别,实现高压输电区域性重覆冰线路受损部位监测。采用程序加载和嵌入式的模块化设计方法,进行监测系统的集成开发设计。测试结果表明,采用该方法进行高压输电区域性重覆冰线路受损监测的智能性较高,人机交互性较好。

Design of damage monitoring system for high voltage transmission line

In order to improve the stability of high voltage transmission line,a method for monitoring the damage of high voltage transmission line is proposed based on visual feature reconstruction.The system is designed based on multi-layer embedded architecture.A visual acquisition model for monitoring the damage of regional reicing lines of high voltage transmission is constructed.The image reconstruction of the damaged parts of the regional reicing lines of high voltage transmission lines is carried out by laser scanning and infrared analysis.The regional edge contour detection model of HV transmission line is constructed,and the abnormal feature information of the damaged area of HV transmission line is extracted by combining the template feature matching method to detect the damaged part of the HV transmission line.Combined with machine learning method,t he extracted feature information is automatically classified and recognized by artificial intelligence to monitor the damaged parts of the regional reicing lines of HV transmission line.The integrated development and design of the monitoring system are carried out by using the modular design method of program loading and embedded.The test results show that the method is more intelligent and has better man-machine interaction in monitoring the damage of regional overlying lines of high voltage transmission.