Challenge and objective

  • Manual inspections are time consuming, resource demanding​ and the evaluation is most often subjective.
  • Drone technologies have reached a level of maturity where it is more efficient to perform condition monitoring automatically.

Work performed

  • Investigated state of the art regarding sensors and methods for automatic condition monitoring.

Significant results

  • Overview of available sensors and methods relevant for automatic inspection of infrastructure corridors, conductors, pylons and other components​.
  • Identification of challenges related to platform and data analysis.

Impact for distribution system innovation

  • Basis for increased utilisation of component life time and ​reduced total maintenance and reinvestment costs.
V. N. Nguyen, R. Jenssen and D. Roverso, “Automatic autonomous vision-based power line inspection: A review of current status and the potential role of deep learning”, International Journal of Electrical Power & Energy Systems, vol. 99, pp. 107-120, 2018.

Susanne Sandell

WP1 Lead
+47 984 891 26
Susanne Sandell
WP1 Lead


Reference in CINELDI

  • R. Moore, H. Schulerud, E. Solvang, H. Vefsnmo: "Automatic assessment of the distribution system for condition monitoring", project memo, CINELDI/SINTEF Energy Research, 2018.