Tilt Detection Of Transmission Line Tower Based On UAV Remote Sensing Technology

The current inspection methods of high-voltage transmission lines and power facilities in China mainly rely on manual tower climbing,erection of instruments or naked eye to complete the inspection of power facilities defects.Not only the working environment is harsh,the inspection efficiency is low,the labor intensity is high,but the safety of inspectors is not guaranteed,so manual inspection has gradually been failed to follow the pace of the development of modern and intelligent power grids.At this stage,the remote sensing technology of UAV is developing rapidly,and the automated inspection system,which is equipped with high-precision sensors such as oblique camera and Li DAR scanner,has broad application prospects in the power sector.The tower is an indispensable part of the power transmission system,so it is of great significance to the safe and stable operation of the entire power system to efficiently detect the inclination of the tower to eliminate hidden dangers.This thesis takes the UAV remote sensing technology as the starting point.Firstly,introduce the composition of the UAV power inspection system,using a multi-rotor UAV platform,equipped with positioning and orientation system,self-stabilizing gimbal system,multi-sensor data acquisition system ect.,to realize the oblique image and Li DAR point cloud 3D information acquisition of towers.Secondly,on the basis of the obtained oblique image,use image homogeneity and distortion correction preprocessing,bundle block adjustment,SIFT algorithm-based feature extraction and image matching,texture mapping and other oblique photogrammetry techniques to construct 3D point cloud model.At the same time,the airborne Li DAR point cloud data is classified and processed to obtain the local point cloud of the power tower,and the Li DAR point cloud is converted to the WGS84 coordinate system,then the ICP algorithm is used to align the point cloud,complete the fusion of oblique image point cloud and Li DAR point cloud data,and generate the refined 3D model of the tower by texture mapping.Finally,the space rectangular coordinates of the power tower in the CGCS2000 coordinate system are extracted in this refined 3D model of the power corridor,according to the principle of tower inclination detection,a mathematical model for calculating the inclination of the tower is constructed in Python language to calculate the inclination of the tower,and the calculation results are compared and analyzed with the inclination of power tower measured by the traditional total station method.The experimental results show that point cloud fusion can achieve complementary advantages in real-world 3D modeling and information extraction of electric power towers.After the fusion,the surface of the tower model is smooth and flat,and the outer contour of the structure has obvious edge features,which can provide more accurate measurement results.Through repeated UAV remote sensing 3D modeling of electric power tower tilt detection,the measurement results meet the daily inspection demand of electric power tower tilt defects,and provide reference for intelligent inspection of power facilities.