Abstract
Unmanned aerial vehicles (UAVs) have become important tools for power transmission line inspection. Cameras installed on the platforms can efficiently obtain aerial images containing information about power equipment. However, most of the existing inspection systems cannot perform automatic real-time detection of transmission line components. In this paper, an automatic transmission line inspection system incorporating UAV remote sensing with binocular visual perception technology is developed to accurately detect and locate power equipment in real time. The system consists of a UAV module, embedded industrial computer, binocular visual perception module, and control and observation module. Insulators, which are key components in power transmission lines as well as fault-prone components, are selected as the detection targets. Insulator detection and spatial localization in aerial images with cluttered backgrounds are interesting but challenging tasks for an automatic transmission line inspection system. A two-stage strategy is proposed to achieve precise identification of insulators. First, candidate insulator regions are obtained based on RGB-D saliency detection. Then, the skeleton structure of candidate insulator regions is extracted. We implement a structure search to realize the final accurate detection of insulators. On the basis of insulator detection results, we further propose a real-time object spatial localization method that combines binocular stereo vision and a global positioning system (GPS). The longitude, latitude, and height of insulators are obtained through coordinate conversion based on the UAV’s real-time flight data and equipment parameters. Experiment results in the actual inspection environment (220 kV power transmission line) show that the presented system meets the requirement of robustness and accuracy of insulator detection and spatial localization in practical engineering.
Highlights
Overhead transmission lines connect power plants, substations and consumers to form power transmission and distribution networks [1,2]
An automatic transmission line inspection system integrated with Unmanned aerial vehicles (UAVs) remote sensing and binocular stereo vision technology is developed to accurately detect and locate power equipment in real time. This system would be beneficial for transmission line inspection and similar applications in other fields; We propose an insulator detection algorithm based on RGB-D saliency detection and skeleton structure characteristics, which can detect insulators in real time for aerial images with complex backgrounds; We propose a real-time object spatial localization method that combines binocular stereo vision and a global positioning system (GPS) device
An automatic linespatial inspection system incorporating application and can further serve for the navigation of UAV, target tracking, defect diagnosis remote sensing with binocular vision perception technology is developed to accurately and inspection management inin operation effectively
Summary
Overhead transmission lines connect power plants, substations and consumers to form power transmission and distribution networks [1,2]. The failure of insulators directly threatens the stability and safety of transmission lines. Accidents are caused by insulator faults account for the highest proportion of power system faults [5]. The condition monitoring of insulators is of great significance to the safety and stability of the power system. Traditional manual inspections have high labor costs and low-efficiency. Unfavorable factors such as climate and the geographical environment will restrict manual inspections, leading to many hidden dangers that cannot be discovered in time [6,7,8]. The images in the dataset are divided into two parts, in which the complex backSimple background ground samples account for. 70%, and the remaining are simple background samples. 63.5% proThe efficiency of the proposed algorithm is evaluated through cessing time and detection Simple successbackground rate.
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