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 ...

Residential and commercial circuit breakers face three major challenges: detecting arc faults reliably, reducing false trips ...

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. The software gives utilities ...

Researchers have proposed a multimodal sensor fusion approach to AI-based fault detection in 3D printing, aiming to push AM monitoring closer to reliable, Industry 4.0 operation.

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 ...

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

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 ...