MODELING AND SIMULATION OF ELECTRICAL MACHINE FAULT DIAGNOSIS WITH MATLAB/SIMULINK

The reliability of electrical machines is vital in both academic and industrial applications. Frequent faults such as overheating, vibration, insulation breakdown, and electrical imbalances cause downtime, safety hazards, and costly maintenance. This study aims to develop a softwarebased simulation framework for fault detection and diagnosis (FDD) using MATLAB/Simulink. Specifically, the objectives are to (i) model common electrical and mechanical faults, (ii) simulate fault scenarios to analyze performance, and (iii) evaluate diagnostic strategies. The framework is anchored on the Condition-Based Maintenance Theory, which emphasizes continuous monitoring and predictive diagnostics. Using MATLAB/Simulink, the study incorporated fault injection models and sensor-based monitoring to detect anomalies through signal processing techniques. The findings revealed that the system achieved diagnostic accuracy of over 92% within 30 ms, demonstrating its real-time capability. The conclusion establishes that software-based FDD is cost-effective, improves safety, enhances predictive maintenance, and serves as a valuable tool for engineering laboratories and industrial training