Fault Detection Projects for ME, MTech, Masters, MS abroad, and PhD students. These Fault Detection ieee projects are implemented with future work and extension for final year students with research paper writing and publishing. These research projects guide final year students to learn, practice, and complete their academic submissions successfully. Each project includes complete source code, project report, PPT, a tutorial, documentation, and a research paper.
Latest Fault Detection Projects
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A Hybrid Fault Detection Method for Hairpin Windings Integrating Physics Model and Machine Learning
This project focuses on detecting faults in electric motor windings. It combines a modeling method and a data-based method to identify problems caused by epoxy issues. The model simulates motor behavior, while data analysis helps find patterns linked to faults. This approach improves accuracy in detecting hidden motor defects that traditional methods might miss. -
Bearing Fault Detection and Recognition From Supply Currents With Decision Trees
This project uses machine learning to detect faults in electric motor bearings by analyzing current signals. It focuses on using decision trees, which can explain how they make decisions in a simple way. The method works well even when tested on new and unseen motor load conditions. It achieved more than 90% accuracy in identifying bearing faults.
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