输电线路无人机自主巡检方法研究与应用
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引用本文:黄 郑1,王红星1,翟学锋1,王永强2,高 超2.输电线路无人机自主巡检方法研究与应用[J].计算技术与自动化,2021,(3):157-161
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黄 郑1,王红星1,翟学锋1,王永强2,高 超2 (1.江苏方天电力技术有限公司, 南京 2111022. 国网江苏省电力有限公司, 江苏 南京 210024) 
中文摘要:为了解决输电线路无人机巡检作业易受恶劣天气影响、远距离遥控不及时、通信稳定性差等问题,提出了一种输电线路无人机自主巡检方法。首先,利用卡尔曼滤波算滤除原始线路中的轨迹噪点,采用垂距法对轨迹冗余点进行过滤,优化巡检航线;其次,提出基于巡检对象差异特性的动态优化定位方法提升无人机巡检质量。以某220 kV输电线路杆塔进行测试,测试结果表明,提出的方法解决了航线采集以及定位优化问题,贯穿航线学习到自主巡检的流程之中,兼顾了无人机自主巡检效率以及巡检精确度。
中文关键词:输电线路  无人机自主巡检  航线自学习  定位优化
 
Research and Application of UAV Autonomous Inspection Method for Transmission Line
Abstract:In order to solve the problems such as vulnerable to bad weather, untimely remote control and poor communication stability, the uav autonomous inspection method is proposed in this paper. Firstly, kalman filter was used to filter the track noise points in the original line, and the offset method was used to filter the track redundancy points, so as to optimize the inspection route. Secondly, a dynamic optimization positioning method based on the difference characteristics of inspection objects is proposed to improve the quality of uav inspection. A 220kV transmission line tower was used for the test. The test results showed that the method proposed in this paper effectively solved the problems of route acquisition and positioning optimization, learned the process of autonomous inspection throughout the route, and took into account the autonomous inspection efficiency and accuracy.
keywords:transmission line  uav autonomous inspection  route self-learning  location optimization
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