Patent US 11,680,977

Patent №

US 11,680,977

Granted

Owner

Lab

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.

Machine learningVisionPlanningAI hardwareG01R 31/088G01R 31/085G01R 31/086G01R 31/52G06N 3/048G06N 3/084Y04S 10/52

AI classification

Machine learning1.00
Planning1.00
Vision0.97
AI hardware0.94
Knowledge representation0.40
Evolutionary computation0.01
Speech0.00
Natural language0.00
© 2026 NYSGPT2525 LLC