输电线路检查:无人机系统的方法、挑战、现状和使用情况

IF 3.1 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent & Robotic Systems Pub Date : 2024-03-26 DOI:10.1007/s10846-024-02061-y
Faiyaz Ahmed, J. C. Mohanta, Anupam Keshari
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引用次数: 0

摘要

输电线路的状态监测是提高输电效率和确保不间断供电的一个重要方面。其中,高效的检测方法对于在任何地理和环境条件下,以较少的工作量和成本、最少的劳动力投入和方便的执行方式进行定期检测起着至关重要的作用。早期的检测方法主要有人工检测、卷线机器人检测和直升机检测。如今,基于无人机系统(UAS)的检测技术在工作速度、困难情况下编程的灵活性、数据收集的准确性和成本最小化等方面的适用性正在逐步提高。本文报告了输电线路系统检测的最新研究成果,并对其中使用的各种方法及其优缺点进行了解释和比较。此外,还对用于输电线路检测的现有视觉检测系统进行了审查。此外,还讨论了用于输电线路检测的区块链实用程序,这说明了下一代数据管理的可能性,实现了有效检测的自动化,并为当前的挑战提供了解决方案。总之,综述展示了深度学习、导航控制概念和先进传感器利用的协同整合概念,从而可以从不同方面分析具有先进计算技术的无人机的实施情况。
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Power Transmission Line Inspections: Methods, Challenges, Current Status and Usage of Unmanned Aerial Systems

Condition monitoring of power transmission lines is an essential aspect of improving transmission efficiency and ensuring an uninterrupted power supply. Wherein, efficient inspection methods play a critical role for carrying out regular inspections with less effort & cost, minimum labour engagement and ease of execution in any geographical & environmental conditions. Earlier various methods such as manual inspection, roll-on wire robotic inspection and helicopter-based inspection are preferably utilized. In the present days, Unmanned Aerial System (UAS) based inspection techniques are gradually increasing its suitability in terms of working speed, flexibility to program for difficult circumstances, accuracy in data collection and cost minimization. This paper reports a state-of-the-art study on the inspection of power transmission line systems and various methods utilized therein, along with their merits and demerits, which are explained and compared. Furthermore, a review was also carried out for the existing visual inspection systems utilized for power line inspection. In addition to that, blockchain utilities for power transmission line inspection are discussed, which illustrates next-generation data management possibilities, automating an effective inspection and providing solutions for the current challenges. Overall, the review demonstrates a concept for synergic integration of deep learning, navigation control concepts and the utilization of advanced sensors so that UAVs with advanced computation techniques can be analyzed with different aspects of implementation.

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来源期刊
Journal of Intelligent & Robotic Systems
Journal of Intelligent & Robotic Systems 工程技术-机器人学
CiteScore
7.00
自引率
9.10%
发文量
219
审稿时长
6 months
期刊介绍: The Journal of Intelligent and Robotic Systems bridges the gap between theory and practice in all areas of intelligent systems and robotics. It publishes original, peer reviewed contributions from initial concept and theory to prototyping to final product development and commercialization. On the theoretical side, the journal features papers focusing on intelligent systems engineering, distributed intelligence systems, multi-level systems, intelligent control, multi-robot systems, cooperation and coordination of unmanned vehicle systems, etc. On the application side, the journal emphasizes autonomous systems, industrial robotic systems, multi-robot systems, aerial vehicles, mobile robot platforms, underwater robots, sensors, sensor-fusion, and sensor-based control. Readers will also find papers on real applications of intelligent and robotic systems (e.g., mechatronics, manufacturing, biomedical, underwater, humanoid, mobile/legged robot and space applications, etc.).
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