| Abstract | This M.Tech Electrical Engineering topic focuses on A lightweight deep learning framework for motor fault diagnosis using alternating current signal analysis. It belongs to the Fault Diagnosis in Machines area within Electrical Machines & Drives. The work is suitable for research topic selection, synopsis preparation, literature review, machine-drive modelling, MATLAB/Simulink or Python-based analysis, controller design, fault-diagnosis experiments, sensorless estimation studies, result analysis, and dissertation documentation. Students can use this 2023-onward research reference as the base paper and then customize the implementation using suitable motor parameters, inverter model, control strategy, signal-processing method, machine-learning model, and performance metrics. |
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| Reference Paper | A lightweight deep learning framework for motor fault diagnosis using alternating current signal analysis |
| Year | 2026 |
| Domain | Electrical Machines & Drives |
| Sub-Domain | Fault Diagnosis in Machines |
| PDF / Source Link | Open Paper / PDF |
| Get Help | Get Help on WhatsApp
Message: Hi FE, I need help with "A lightweight deep learning framework for motor fault diagnosis using alternating current signal analysis" in "Electrical Machines & Drives" |
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