Honours Thesis: Motor Faults Diagnosis with Machine Learning Algorithms

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Project Roles

Researched current eccentricity fault detection methods and proposes an AI-based approach for the classification of eccentricity faults in induction motors using voltage signals.
Studied and applied k-Nearest-Neighbors (kNN) Algorithm in combination with data processing to the project.
Designed, trained, and tested the algorithm with experimental datasets and received positive results.
Compiled research and experimental findings into a paper to be submitted to the IEEE conference.