DESIGN AND IMPLEMENTATION OF A REAL-TIME SYSTEM FOR FAULT DIAGNOSIS IN POWER ELECTRONICS

A real-time system for power electronics problem diagnosis is discussed in this work, along with its design and implementation. Improving system reliability, decreasing downtime, and preventing costly damage all depend on the ability to diagnose defects promptly and effectively in power electronics systems. Data quality, feature extraction, class imbalance, real-time processing, interpretability of models, system complexity, and hardware restrictions are only few of the obstacles that must be overcome when creating such a system. This study presents a technique for tackling these issues, including data collection and processing, feature extraction, machine learning algorithm selection, and hardware optimisation. The report also compares and contrasts several current approaches and their shortcomings. The paper also discusses possible future directions, such as the incorporation of additional data sources, the creation of hybrid models, the investigation of other machine learning algorithms, and the design of fault-tolerant systems, and highlights the challenges and limitations of the proposed methodology. As a whole, this study sheds light on the difficulties and potentials of real-time systems for problem identification in power electronics