基于无人机采集图像的输电线路异常检测方法研究

Study on anomaly detection method of transmission line based on image acquired by UAV

针对现有无人机航拍输电线路图像异常检测方法效率低、精度差等问题,在无人机航拍输电线路图像预处理的基础上,提出改进的相位编组算法用于导线提取和滑动像素块模型用于输电线路的异常检测。根据输电线路的最佳相位划分方式和伪导线判断基准优化相位编组算法,通过改变滑动像素块的旋转梯度角,确定传输线异常的准确位置,并完成导线断股和悬挂异物检测。通过实验对所提方法的可行性进行验证。结果表明,与常规方法相比,所提导线提取方法具有更高的精度、防误检和运行效率,在导线断股和悬挂异物检测中具有更高的准确度和运行效率,所提出的研究可以大幅提高巡检的安全性和效率。

Aiming at the problems of low efficiency and poor accuracy of the existing methods for anomaly detection of transmission line images taken by UAV aerial photography,an improved phase grouping algorithm is proposed for wire extraction and sliding pixel block model for anomaly detection of transmission lines based on the preprocessing of transmission line images taken by UAV aerial photography.According to the optimal phase division mode of the transmission line and the pseudo wire judgment benchmark,the phase grouping algorithm is optimized.The accurate location of the transmission line anomaly is determined by changing the rotation gradient angle of the sliding pixel block,and the detection of broken wires and suspended foreign objects is completed.The feasibility of the proposed method is verified by experiments.The results show that,compared with the conventional methods,the proposed wire extraction method has higher accuracy,error detection prevention and operation efficiency,and has higher accuracy and operation efficiency in the detection of wire strand breakage and suspended foreign matters.This research can greatly improve the safety and efficiency of patrol inspection.