First Measurement Campaign by a Multi-Sensor Robot for the Lifecycle Monitoring of Transformers

被引:1
|
作者
Waikat, Jakub [1 ]
Jelidi, Amel [2 ]
Lic, Sandro [2 ]
Sopidis, Georgios [2 ,3 ]
Kaehler, Olaf [4 ]
Maly, Anna [4 ]
Pestana, Jesus [2 ,5 ]
Fuhrmann, Ferdinand [4 ]
Belavic, Fredi [6 ]
机构
[1] Siemens Energy Austria GmbH, A-1210 Vienna, Austria
[2] Pro2Future GmbH, A-8010 Graz, Austria
[3] Johannes Kepler Univ Linz JKU, Inst Pervas Comp, A-4040 Linz, Austria
[4] Joanneum Res, A-8010 Graz, Austria
[5] Graz Univ Technol TU Graz, Inst Comp Graph & Vis, A-8010 Graz, Austria
[6] Austrian Power Grid, A-1220 Vienna, Austria
关键词
transformer; lifecycle-monitoring; electric transmission grid; service robotics; anomaly detection; internet of things; AI;
D O I
10.3390/en17051152
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Transformers are a very important asset in the electrical transmission grid, and they can suffer from destructive events-e.g., rare transformer fires. Unfortunately, destructive events often lead to a lack of data available for investigators during post-event forensics and failure analysis. This fact has motivated our design and implementation of a robotic multi-sensor platform and cloud backend solution for the lifecycle monitoring, inspection, diagnostics, and condition assessment of transformers. The robotic platform collects data from specific viewpoints around the transformer during operation and at specific relevant lifecycle milestones of the transformer (e.g., at the factory acceptance test) in an automated, repetitive, precise, and reliable manner. The acquired data are stored in the cloud backend, which also provides computing resources and data access to relevant in- and off-premises services (e.g., respectively, SCADA systems, and weather reports). In this paper, we present the results of our first measurement campaign to showcase the value of our solution for transformer lifecycle monitoring, for anomaly detection, and as a crucial tool for post-event forensics in the case of destructive events.
引用
收藏
页数:26
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