AI fault detection uses waveform analytics and machine learning to identify early electrical failure signatures in distribution systems. Utilities gain predictive insight into incipient faults, asset ...

Incipient fault detection using AI classification represents a fundamental advancement in distribution system reliability engineering. By continuously analyzing waveform behavior and classifying ...

CNIguard is transforming underground utility operations by shifting from reactive, break-fix approaches to proactive, ...

Microchip Technology has introduced full-stack edge AI solutions built around its microcontrollers and microprocessors to ...

A group of researchers led by the University of Sharjah in the UAE proposed to use the convolutional neural network (CNN) technique to detect temperature and shading-induced faults in PV modules. CNN ...

Sense, a company focused on grid edge intelligence, has announced a new edge-powered Fault Detection Solution that is embedded directly into next-generation smart meters.

Scientists in India have proposed using a multilayer neural network to find line-to-ground, line-to-line, and bypass diode faults in PV module strings. They tested the new approach on a 22.5 kW solar ...

A recent study has made a significant step forward in improving the energy efficiency of buildings by enhancing the accuracy and adaptability of fault detection and diagnosis (FDD) in heating, ...

Denso’s fault detection device for antennas adjusts carrier wave frequency, modulates the signal, and measures antenna current to detect faults. By analyzing current values, the device identifies ...