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

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 ...

Fault detection and diagnosis (FDD) constitute a critical area of research that underpins the efficient and safe operation of modern industrial processes. The field integrates data analytics, machine ...

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

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

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 ...

In today's industries, quality inspection in semiconductor manufacturing is critical. Many traditional fault detection and diagnosis techniques have been developed to determine the existence of trends ...

EAST SYRACUSE, N.Y.--(BUSINESS WIRE)--INFICON, a leading provider of manufacturing software and hardware solutions for the semiconductor and related industries, is proud to announce the release of the ...

More than 90% of US power outages start on the distribution grid – the part closest to homes that utilities can’t always see in real time – but Sense says it’s trying to change that by pushing fault ...

A research team led by the University of Sharjah in the United Arab Emirates has developed a novel machine learning approach for fault detection in bifacial PV systems. The method combines a ...