Generator Fault Diagnosis Using Electrical Signature Analysis and Thermal Imaging: A MATLAB-Based Approach

Abstract

This study proposes a MATLAB-based approach for generator fault diagnosis by combining Thermal Imaging Analysis and Electrical Signature Analysis (ESA) to detect early signs of faults and optimize maintenance. Six thermal imaging tests simulate generator surface temperatures, identifying hotspots exceeding the 80°C threshold at specific positions: (2,10): 85°C, (4,8): 85°C, (4,9): 88°C, (4,10): 90°C, (5,9): 89°C, and (5,10): 91°C. These high-temperature zones suggest localized overheating, potentially due to mechanical friction, insulation degradation, or inadequate cooling, highlighting areas needing further inspection.

Simultaneously, ESA analysis introduces a 120 Hz harmonic component to a baseline 50 Hz sinusoidal current, emulating fault-related electrical anomalies. Frequency analysis shows this 120 Hz harmonic distinctly, confirming electrical irregularities that could indicate rotor or stator imbalances, aligning with the thermal findings.

The dual-diagnostic method strengthens fault detection by addressing both thermal and electrical indicators, providing a comprehensive insight into generator health. The study demonstrates that integrating thermal and ESA analyses significantly enhances diagnostic accuracy, supporting proactive maintenance efforts. This approach contributes to reducing downtime and optimizing repair efforts, offering an effective framework for stakeholders to ensure generator reliability and extend operational life.