Walsh Matrix Analysis and Feed Forward Neural Network based Fault Detection Technique

This dataset provides raw electrical current measurements for fault studies in power transformers, designed to support the development of fault detection techniques using artificial intelligence, machine learning, and deep learning. It includes both simulation and experimental data covering a range of operating scenarios, including normal, abnormal, and various fault conditions. The raw data enable training and validation of AI-, ML-, and DL-based diagnostic models. In addition, the dataset is suitable for use in data-driven, model-based, and waveform-based analysis approaches, facilitating research on reliable fault detection and classification in power transformer applications.