This study presents a system for short-circuit fault diagnosis in three-phase induction motors directly connected to the grid. The system's methodology is based on delayed mutual information in order to extract relevant characteristics between electrical current signals in alpha-beta  orthogonal reference system. Those data are submitted to several pattern classifiers evaluation of the proposed method adherence for classification on machine learning based algorithms. Assays in several machine's operation conditions validates the proposed methodology robustness and accuracy.