Search Results for author:
Found 4 papers, 0 papers with code
PowerGraph: A power grid benchmark dataset for graph neural networks
To this aim, we develop a graph dataset for cascading failure events, which are the major cause of blackouts in electric power grids.
Anomaly detection for automated inspection of power line insulators
Inspection of insulators is important to ensure reliable operation of the power system.
Uncertainty-aware deep learning for digital twin-driven monitoring: Application to fault detection in power lines
In such a scenario, the performance of the DNN model will be influenced by the uncertainty in the physics-based model as well as the parameters of the DNN.
Object detection-based inspection of power line insulators: Incipient fault detection in the low data-regime
We curate a large reference dataset of insulator images that can be used to learn robust features for detecting healthy and faulty insulators.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
