scholarly journals Unmanned Aerial Vehicle Positioning Algorithm Based on the Secant Slope Characteristics of Transmission Lines

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 43229-43242
Author(s):  
Chang'An Liu ◽  
Yue Shao ◽  
Ziqiang Cai ◽  
Yuejie Li
Author(s):  
Alexandros Zormpas ◽  
Konstantia Moirogiorgou ◽  
Kostas Kalaitzakis ◽  
George A. Plokamakis ◽  
Panayotis Partsinevelos ◽  
...  

2019 ◽  
Vol 16 (1) ◽  
pp. 172988141982994 ◽  
Author(s):  
Xiaolong Hui ◽  
Jiang Bian ◽  
Xiaoguang Zhao ◽  
Min Tan

This article presents a monocular-based navigation approach for unmanned aerial vehicle safe and continuous inspection along one side of transmission lines. To this end, a navigation model based on the transmission tower and the transmission-line vanishing point was proposed, and the following three key issues were addressed. First, a deep-learning-based object detection and a fast and smooth tracking algorithm based on the kernelized correlation filter were combined to locate transmission tower timely and reliably. Second, the vanishing point of transmission lines was computed and optimized to provide unmanned aerial vehicle with a robust and precise flight direction. Third, to keep a stable safe distance from transmission lines, the transmission lines were first rectified by optimizing a homography matrix to eliminate the parallel distortion, and then their interval variation was estimated for reflecting the spatial distance variation. Finally, the real distance from transmission tower was measured by the triangulation across multiple views. The proposed navigation approach and the designed UAV platform were tested in a field environment, which achieved an encouraging result. To the best of authors’ knowledge, this article marks the first time that a safe and continuous navigation approach along one side of transmission lines is put forward and implemented.


2019 ◽  
Vol 140 ◽  
pp. 07008
Author(s):  
Phuong Nguyen ◽  
Sergey Dudkin ◽  
Chenzai Kong

Evaluation of the technical condition, reliability of the insulation of electrical equipment is an actual problem. It is confirmed by experience and statistics of operation at power plants and railway facilities. The combination of an unmanned aerial vehicle with UV-camera and software based on neural networks allows us to effectively diagnose long power lines. To increase the effectiveness of non-contact inspection of power lines, especially in hard-to-reach areas, more compact mobile solutions should be used which include an UV-camera and an unmanned aerial vehicle (UAV). The aircraft market currently has significant growth, that allows to bring the diagnostic experience to a new level by attaching an UV-camera to an aerial device, which will have a tremendous effect on examining long power lines. But we faced one problem related to the absence of any scientific basis for this method of examination, so it was decided to conduct experiments in a laboratory of St. Petersburg Polytechnic University. The results of experiments are presented in the work.


2018 ◽  
Vol 14 (11) ◽  
pp. 160
Author(s):  
Yao Yao ◽  
Qing-le Quan ◽  
Hong-hui Zhang ◽  
Qiong Li

<p class="0abstract"><span lang="EN-US">In order to study the power patrol technology of unmanned aerial vehicle, the tracking algorithm was applied. The automatic patrolling of power lines was discussed in terms of algorithms. An unmanned aerial vehicle transmission line inspection method based on machine vision was proposed. The image and video of the unmanned aerial vehicle inspection of the power line had a complex background. By Wiener filtering de-noising and probability density functions, the image clarity was improved. According to the existing tracking techniques and algorithms, a Camshaft target tracking algorithm based on lossless Kalman filter was proposed. The method of non-destructive Kalman filter was adopted to predict the region of interest of power line identification. Using the Camshaft algorithm, the prediction of the window was searched and the size of the window was adjusted. Transmission lines were tracked in real time. The results showed that the restoration effect of the algorithm was obvious. The clarity of the image was improved. It prepared for the extraction and tracking of the future transmission lines. Therefore, the proposed method provides a feasible way for the UAV power line inspection technology based on machine vision.</span></p>


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