14 citations · 14 across the 2 of their papers we have counts for
4 papers
Explainable AI guided unsupervised fault diagnostics for high-voltage circuit breakers
Chi-Ching Hsu, Gaëtan Frusque, Florent Forest +3
Commercial high-voltage circuit breaker (CB) condition monitoring systems rely on directly observable physical parameters such as gas filling pressure with pre-defined thresholds.…
Informed Graph Learning By Domain Knowledge Injection and Smooth Graph Signal Representation
Keivan Faghih Niresi, Lucas Kuhn, Gaëtan Frusque +1
Graph signal processing represents an important advancement in the field of data analysis, extending conventional signal processing methodologies to complex networks and thereby fa…
Semi-Supervised Health Index Monitoring with Feature Generation and Fusion
Gaëtan Frusque, Ismail Nejjar, Majid Nabavi +1
The Health Index (HI) is crucial for evaluating system health and is important for tasks like anomaly detection and Remaining Useful Life (RUL) prediction of safety-critical system…
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly Generation
Hao Dong, Gaëtan Frusque, Yue Zhao +2
Anomaly detection (AD) is essential in identifying rare and often critical events in complex systems, finding applications in fields such as network intrusion detection, financial…