摘要
为提高电力系统监测和故障诊断能力，结合无人机的无线遥感视觉监测技术进行电力系统实时监测方法研究，提出一种基于无人机视觉信息融合和Harris角点检测技术的电力系统损坏监测方法。采用远程无人机红外遥感扫描技术进行电力系统分布式图像采集，对采集的无人机红外遥感图像进行块分割和向量量化处理，对提取的视觉图像量化特征进行信息融合，结合Harris角点检测方法提取电力系统损坏部位的异常分布特征，实现电力系统损坏部位的准确定位识别。仿真结果得知，采用该方法进行无人机视觉下的电力系统损坏监测的准确性较高，实时性较好，对损坏点的定位准确性较好。
In order to improve the power system damage is monitoring and fault diagnosis ability of real-time monitoring method of power system based on wireless remote sensing visual monitoring technology of UAV, monitoring method of damage to the power system of a UAV visual detection technology based on information fusion and Harris corner. The UAV remote infrared remote sensing technology for distributed scanning the image acquisition of power system, the UAV infrared remote sensing image block segmentation and vector quantization acquisition and processing, information fusion on quantitative characteristics of the visual image, abnormal distribution of feature extraction of power system damage with Harris corner detection, accurate positioning to achieve identification of power system damage. The simulation results show that the method for monitoring high accuracy without damage of power system under the visual, real-time, loss of Good point positioning accuracy.
出处
《自动化与仪器仪表》
2018年第3期169-172,共4页
Automation & Instrumentation
关键词
无人机视觉
电力系统
损坏
检测
特征提取
UAV vision
power system
damage detection
feature extraction
