Open access
Jul 2026
Hybrid Fault-Space Restructuring for Machine Learning-Based Fault Diagnosis in Power Electronic Converters
This work proposes an edge-oriented hybrid fault-space restructuring methodology that utilizes UMAP-based embeddings and hierarchical clustering to group overlapping fault conditions into robust hybrid representations, ensuring a highly viable execution on resource-constrained devices once the classifiers are trained.
J. M. García-Campos, A. M. Alcaide, A. Letrado-Castellanos et al.
· Electronics · 0 citations