Transmission Line Anomaly Detection Method Based on Point Cloud Data Registration
Anomaly detection is an important link in the operation and maintenance of transmission lines,providing reliable basis for fault maintenance of transmission lines.However,existing detection methods have a low hit rate,and the Spearman correlation coefficient between detection results and actual operating lines is low.A transmission line anomaly detection method based on point cloud data registration is proposed to address the shortcomings of existing methods.Firstly,use a 3D laser scanner to collect point cloud data of transmission lines.Secondly,denoise the discrete points in the collected point cloud data and simulate the status of transmission lines through point cloud data registration methods.Finally,by comparing with normal transmission lines,identify the abnormal status of the transmission lines to complete the detection of abnormal transmission lines.The experiment shows that the hit rate of the anomaly detection method is over 96%,and the Spearman correlation coefficient between the detection results and the actual operating lines is over 0.9.At the same time,this method has good application prospects in anomaly detection of transmission lines.
point cloud data registrationtransmission lines3D laser scanningdiscrete pointshit rate
NETL
NSTL
万方数据
维普
