Innovative system for automated monitoring of critical electricity lines (Q80222): Difference between revisions
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(Created claim: summary (P836): The project consists of setting up a system to monitor the modernisation works on the existing critical electricity network infrastructure.The reporting will be based on the data collected from the drone strikes.The accuracy of the data collected will be acceptable at around1 centimetres for major components such as foundations, cables, hooks.The mere access to the data by drones will be carried out by means of photogrammetry and/or by using a l...) |
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| Property / summary | |||
The project consists of setting up a system to monitor the modernisation works on the existing critical electricity network infrastructure.The reporting will be based on the data collected from the drone strikes.The accuracy of the data collected will be acceptable at around1 centimetres for major components such as foundations, cables, hooks.The mere access to the data by drones will be carried out by means of photogrammetry and/or by using a laser scanner (includes multiscan).A system of automatic positioning and taking of images by drones will be developed as a result of research.The data collected will be digitised and analysed using artificial intelligence and machine-learning algorithms (:Machine Learning, ML), such as for example:Convololutional neRural networks, CNN).The Alliance will not make it possible to increase reliability (more secure and less emergency electricity system work), to anticipate the impact of project solutions on their viability (examination of the ageing of individual elements of the line) and to speed up the removal of the accident (collection of qualitative data on existing lines) will make it possible to estimate the workload and the progress of the work, including the identification of individual sites.The algorithm will use the network learning rules, which will translate into a classification of identified objects that differ in the defined range of deviation from the reference object.Protect_public_pomo_public_:Article 25 of Commission Regulation (EC) No 651/2014 of 17 June 2014 declaring certain categories of aid compatible with the internal market in the application of Article 107 and 108 of the Treaty (OJ(OJ LEU L 187/1, 26.06.2014). (English) | |||
| Property / summary: The project consists of setting up a system to monitor the modernisation works on the existing critical electricity network infrastructure.The reporting will be based on the data collected from the drone strikes.The accuracy of the data collected will be acceptable at around1 centimetres for major components such as foundations, cables, hooks.The mere access to the data by drones will be carried out by means of photogrammetry and/or by using a laser scanner (includes multiscan).A system of automatic positioning and taking of images by drones will be developed as a result of research.The data collected will be digitised and analysed using artificial intelligence and machine-learning algorithms (:Machine Learning, ML), such as for example:Convololutional neRural networks, CNN).The Alliance will not make it possible to increase reliability (more secure and less emergency electricity system work), to anticipate the impact of project solutions on their viability (examination of the ageing of individual elements of the line) and to speed up the removal of the accident (collection of qualitative data on existing lines) will make it possible to estimate the workload and the progress of the work, including the identification of individual sites.The algorithm will use the network learning rules, which will translate into a classification of identified objects that differ in the defined range of deviation from the reference object.Protect_public_pomo_public_:Article 25 of Commission Regulation (EC) No 651/2014 of 17 June 2014 declaring certain categories of aid compatible with the internal market in the application of Article 107 and 108 of the Treaty (OJ(OJ LEU L 187/1, 26.06.2014). (English) / rank | |||
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Revision as of 09:02, 4 March 2020
Project in Poland financed by DG Regio
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Innovative system for automated monitoring of critical electricity lines |
Project in Poland financed by DG Regio |
Statements
8,682,391.89 zloty
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12,402,373.75 zloty
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2,976,569.6999999997 Euro
0.24 Euro
13 January 2020
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70.01 percent
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1 February 2019
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31 January 2022
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ENPROM SPÓŁKA Z OGRANICZONA ODPOWIEDZIALNOŚCIĄ
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50°8'6.0"N, 19°37'55.2"E
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Projekt polega na stworzeniu systemu służącego do monitorowania prac modernizacyjnych na istniejącej infrastrukturze krytycznej w zakresie sieci elektroenergetycznych. Raportowanie będzie oparte na danych zbieranych z nalotów dronami. Dokładność zbieranych danych będzie dopuszczalna na poziomie ok. 1 centymetra dla większych elementów, takich jak fundamenty, przewody, haki. Samo zasilanie danych przez drony będzie realizowane za pomocą fotogrametrii i/lub przy użyciu skanera laserowego (obejmuje multiskanowanie). W wyniku prac badawczych zostanie opracowany system automatycznego pozycjonowania się i robienia zdjęć przez drony. Zebrane dane będą poddawane obróbce cyfrowej i analitycznej z wykorzystaniem algorytmów sztucznej inteligencji i uczenia maszynowego (ang.: machine learning, ML), takich jak np. systemy regułowe i sieci neuronowe ze splotem (ang.: convolutional neural networks, CNN). Rozwiąznie umożliwi zwiększenie niezawodności (bezpieczniejsza i mniej awaryjna praca systemu elektroenergetycznego), przewidywanie na bazie analizy wpływu rozwiązań projektowych na ich żywotność (badanie starzenia się poszczególnych elementów linii), a także szybsze usuwanie awarii (gromadzenie danych jakościowych na temat istniejących linii) Przetwarzane dane pozwolą oszacować pracochłonność oraz postęp prac, w tym identyfikację poszczególnych obiektów. Algorytm wykorzysta mechanizmy reguły uczenia się sieci, co przełoży się na klasyfikację identyfikowanych obiektów różniących się między sobą w zdefiniowanym zakresie odchyłu od obiektu wzorcowego. Przeznaczenie_pomocy_publicznej: art. 25 rozporządzenia KE nr 651/2014 z dnia 17 czerwca 2014 r. uznające niektóre rodzaje pomocy za zgodne z rynkiem wewnętrznym w stosowaniu art. 107 i 108 Traktatu (Dz. Urz. UE L 187/1 z 26.06.2014). (Polish)
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The project consists of setting up a system to monitor the modernisation works on the existing critical electricity network infrastructure.The reporting will be based on the data collected from the drone strikes.The accuracy of the data collected will be acceptable at around1 centimetres for major components such as foundations, cables, hooks.The mere access to the data by drones will be carried out by means of photogrammetry and/or by using a laser scanner (includes multiscan).A system of automatic positioning and taking of images by drones will be developed as a result of research.The data collected will be digitised and analysed using artificial intelligence and machine-learning algorithms (:Machine Learning, ML), such as for example:Convololutional neRural networks, CNN).The Alliance will not make it possible to increase reliability (more secure and less emergency electricity system work), to anticipate the impact of project solutions on their viability (examination of the ageing of individual elements of the line) and to speed up the removal of the accident (collection of qualitative data on existing lines) will make it possible to estimate the workload and the progress of the work, including the identification of individual sites.The algorithm will use the network learning rules, which will translate into a classification of identified objects that differ in the defined range of deviation from the reference object.Protect_public_pomo_public_:Article 25 of Commission Regulation (EC) No 651/2014 of 17 June 2014 declaring certain categories of aid compatible with the internal market in the application of Article 107 and 108 of the Treaty (OJ(OJ LEU L 187/1, 26.06.2014). (English)
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Identifiers
POIR.01.02.00-00-0307/17
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