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The assessment of key apparatuses' adequate technical conditions is crucial in the delivery of reliable and continuous electric power to customers. To meet this requirement, any fault in the power system must be detected and diagnosed as early as possible, with particular emphasis on the precision of the diagnostic process. Various online and offline diagnostic methods are widely applied for the early detection of system malfunctions, alongside a number of different sensors, which may be used to capture selected physical quantities indicating the type of potential faults. A specific fault diagnostic process is typically carried out by experts in the field; however, artificial intelligence (AI)-based systems are increasingly being proposed to support decision making related to this task. An essential step in fault diagnostic processes is signal analysis, and this is supported by features including (but not limited to) signal processing, feature extraction, modeling, and prediction methods. In this context, this Special Issue includes ten high-quality papers dealing with the main problems currently related to sensors and fault diagnostics in power system engineering.
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