Fault Diagnosis for Electrical Systems and Power Networks: A Review

In this paper, we review the state of art in detection, location, and diagnosis faults electrical wiring interconnection systems (EWIS) including electric power grid vehicles machines. Most test methods rely on measurements either currents voltages or high frequency reflections from impedance discontinuities. Of these methods, phasor, travelling wave reflectometry methods. The summarized include time domain (TDR), sequence (STDR), spread spectrum (SSTDR), orthogonal multi-tone (OMTDR), noise (NDR), chaos (CTDR), binary (BTDR), (FDR), multicarrier (MCR), time-frequency (TFDR). All result complex data sets (reflectometry signatures) that are time/frequency/spatial domains. Automated analysis techniques needed to detect, locate, diagnose fault genetic algorithm (GA), neural networks (NN), particle swarm optimization, teaching-learning-based backtracking search inverse scattering, iterative approaches. We summarize several electromagnetic time-reversal (TR) matched-pulse (MP) approach. also discuss issue soft (small changes) augment their signatures, challenges branched networks. suggest directions for future research development.