首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >AUTOMATING POWERLINE INSPECTION: A NOVEL MULTISENSOR SYSTEM FOR DATA ANALYSIS USING DEEP LEARNING
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AUTOMATING POWERLINE INSPECTION: A NOVEL MULTISENSOR SYSTEM FOR DATA ANALYSIS USING DEEP LEARNING

机译:自动化电力线检查:使用深度学习的数据分析新型多传感器系统

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Powerline infrastructure provides the backbone for the electricity supply of industrial, administrative and private sectors. Its maintenance requires regular inspections, that are still largely carried out manually. In this work, we propose an automated inspection system instead. We review current inspection processes as a baseline, give an overview of relevant inspection criteria, propose a suitable multi-modal sensor system, and discuss methods to automate the inspection tasks. In our system, we particularly focus on the high-level organization of the sensor data and inspection results to form a Digital Twin of the power line, that allows operators to browse through the recorded data in a meaningful way and review the status of their powerline from the desk.
机译:电力线基础设施为工业,行政和私营部门的电力供应提供骨干。其维护需要定期检查,仍然在很大程度上手动进行。在这项工作中,我们提出了一种自动化检查系统。我们审查了当前的检查过程作为基线,概述了相关的检查标准,提出了合适的多模态传感器系统,并讨论了自动化检查任务的方法。在我们的系统中,我们特别关注传感器数据和检查结果的高级组织,以形成电源线的数字双胞胎,允许操作员以有意义的方式浏览记录的数据并查看其电力线的状态从桌子。

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