A. M. Alcaide

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.