A New Automatic Fault Diagnosis Algorithm for Electrical Equipment Based on Infrared Thermography

In this paper, a novel algorithm is proposed for an Efficient Fault Diagnosis Method (EFDM) for electrical equipment in real time. A combined optical and thermal image processing system is employed to detect thermal anomalies in electrical components in real time. A video camera is initially used to monitor and identify the electrical components, while an infrared camera, aligned with the same viewpoint, is used to capture thermal images of the equipment. The EFDM is then applied to identify and locate faults in electrical components. Numerical results indicate that the proposed algorithm achieves higher accuracy in detecting thermal anomalies compared to existing methods. Evaluation across 300 scenarios shows that the proposed method achieves 97.57% accuracy in localizing abnormal electrical components and 95.30% accuracy in estimating their surface temperatures. These results demonstrate that the proposed thermal anomaly detection algorithm is effective for electrical power monitoring applications.