TY  - JOUR 
AU  - Martín Diaz, Ignacio
AU  - Moríñigo Sotelo, Daniel
AU  - Duque Pérez, Óscar
AU  - Romero Troncoso, René de Jesús
PY  - 2017
SN  - 0093-9994
UR  - https://uvadoc.uva.es/handle/10324/64936
AB  - Abstract—Intelligent fault detection in induction motors (IMs) is a widely studied research topic. 
Various artificial-intelligence- based approaches have been proposed to deal with a large amount of 
data obtained from destructive laboratory...
LA  - spa
TI  - Early fault detection in induction motors using AdaBoost with imbalanced small data and optimized sampling
DO  - 10.1109/TIA.2016.2618756
ER  -