Project
Use of UAVs and AI to determine health index of overhead lines
Context
Arya Fazilat
Innovation Manager
The electricity sector is undergoing major changes, particularly in relation to :
It is therefore necessary to be able to determine, with a good degree of accuracy, the health index for all overhead lines (OHL) while limiting the risks to persons (internal employees, contractors and third parties). The use of Unmanned Aerial Vehicles (UAV, i.e. drones) and AI can respond to these major changes and can be an aid to decision-making in relation to investments (the proper actions at the right place). |
Approach
The implementation of the UAV and AI was done through 3 proofs of concept (equipment, concrete poles and lattice towers) with the following methodology:
Based on the results, it was decided to switch to business as usual for inspections of equipment and lattice towers with the knowledge that the AI will become more accurate in the coming years. |
Description
Deployment of a tool to reduce the safety risk
The reduction of climbing is very significant and give the same (higher) quality information to take decision for the asset management of OHL.
Development of a tool to support the business
This tool has an impact on Elia business: significant reduction of switching, collecting of information for asset management, engineering and maintenance.
Participation of digitalisation
The deployment of this tool provides an opportunity to reduce the administrative tasks and to win time and digitalise our infrastructure.
Results
Today, it is possible to localise, on a tower silhouette, all the degradations with a link to an Excel file containing all degradations.
Partners
