Patent №
US 11,680,977
Granted
—
Owner
—
Lab
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AI components
4
ml · vision · planning · hardware
Assignment
None on record
Dataset
AIPD
2023_r1 edition
Application
16822261
Systems and methods for identifying a fault condition in an Ungrounded Electrical Distribution (UED) system, the system receives measurements with instantaneous values and effective values associated when a fault event is identified, measured transient waveforms and a fault type. A processor applies an empirical mode decomposition to the measured transient waveforms to extract a dominant vibration mode and an associated derived waveform corresponding to the dominant vibration mode. A Hilbert transform is applied to the associated derived waveform to obtain a set of feature attributes. Subsets are computed from the set, at a pre-fault time, at a fault inception time, and at a post-fault time, and inputted into the fault type trained neural network model. An output of the model are locational parameters used to determine a fault section, a fault line segment and a fault location point with a topology connectivity analysis of the UED system.