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The Power Line Inspection Software (PoLIS): A versatile system for automating power line inspection

机译:电力线检查软件(PoLIS):用于自动化电力线检查的多功能系统

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摘要

A large amount of data, provided in the form of video data, is acquired during manned inspections flights of electric power lines. This data is analyzed by expert human inspectors to detect faults in the power lines infrastructure and prepare the inspection reports. This process is extremely time consuming, very expensive and prone to human error. In this paper, we present PoLIS: the Power Line Inspection Software, which has been developed with the objective of assisting the analysis of the data acquired during inspection flights. PoLIS is based on the cooperation between computer vision and machine learning techniques to automatically process video sequences acquired during inspection flights, resulting in a set of representative images per electric tower which we call Key Frames. These representative images can then be used for inspection purposes, leading to a drastic reduction of the human operators’ workload. At the core of the strategy lies an electric tower detector, which is in charge of estimating the location of the towers within the images based on the combination of a sliding window search technique and a supervised classifier. The location of the tower is then tracked using a tracking-by-registration algorithm based on direct methods, estimating the position of the tower in different images. Finally, different criteria are applied for defining whether the image corresponds to a Key Frame image or not. Extensive evaluation of the proposed strategy is conducted using videos acquired during manned helicopter inspections. The videos constituting this database contain several thousand frames representing both medium and high voltage power transmission lines in the infra-red (IR) and visible spectra. The obtained results show that the proposed strategy can reduce the large amount of data present in the inspection videos to a few Key Frames for each tower. It is also demonstrated that the learning-based approach proposed in PoLIS is appropriate for detecting electric towers, a process which is made faster and more robust by coupling it with a tower tracking algorithm. A Graphical User Interface allowing the application of PoLIS to user-provided videos is also presented in this paper, illustrating the whole process and the automated generation of an inspection report.
机译:在电力线的人工检查飞行期间,获取了以视频数据形式提供的大量数据。专家检查人员会分析此数据,以检测电力线基础设施中的故障并准备检查报告。该过程非常耗时,非常昂贵并且容易发生人为错误。在本文中,我们介绍了PoLIS:电力线检查软件,其开发目的是协助分析在检查飞行期间获取的数据。 PoLIS基于计算机视觉和机器学习技术之间的合作,可以自动处理在检查飞行过程中获取的视频序列,从而为每个电塔产生一组代表性图像,我们称之为关键帧。这些代表性图像随后可用于检查目的,从而大大减少了操作员的工作量。该策略的核心是电力塔检测器,它基于滑动窗口搜索技术和监督分类器的组合来估计图像中塔的位置。然后使用基于直接方法的注册跟踪算法跟踪塔的位置,从而估计塔在不同图像中的位置。最后,应用不同的标准来定义图像是否对应于关键帧图像。使用载人直升机检查期间获得的视频对提议的策略进行了广泛的评估。构成该数据库的视频包含数千帧,分别代表红外(IR)和可见光谱中的中压和高压输电线路。获得的结果表明,所提出的策略可以将检查视频中存在的大量数据减少到每个塔的几个关键帧。还证明了PoLIS中提出的基于学习的方法适用于检测电塔,通过将其与塔跟踪算法耦合,该过程变得更快,更鲁棒。本文还介绍了一个图形用户界面,允许将PoLIS应用到用户提供的视频中,说明了整个过程和自动生成检查报告。

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  • 作者单位

    Faculty of Engineering, Industrial Engineering Department, Pontificia Universidad Javeriana, Bogotá,Computer Vision and Aerial Robotics Group , Centro de Automática y Robótica (CAR) UPM-CSIC, Universidad Politécnica de;

    Computer Vision and Aerial Robotics Group , Centro de Automática y Robótica (CAR) UPM-CSIC, Universidad Politécnica de;

    Computer Vision and Aerial Robotics Group , Centro de Automática y Robótica (CAR) UPM-CSIC, Universidad Politécnica de;

    Computer Vision and Aerial Robotics Group , Centro de Automática y Robótica (CAR) UPM-CSIC, Universidad Politécnica de;

    Computer Vision and Aerial Robotics Group , Centro de Automática y Robótica (CAR) UPM-CSIC, Universidad Politécnica de;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Power line inspection; Machine learning; Visual tracking; Computer vision;

    机译:电力线检查;机器学习;视觉跟踪;计算机视觉;

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