Abstract: This paper presents a comprehensive fault classification framework for three-phase Induction Motors (IMs) using a novel Grey Wolf Optimization-enhanced Support Vector Machine (GWO-SVM) ...

Code, configuration templates, and documentation for the PSCC 2026 paper Comparison of Deep Learning Methods for Fault Analysis in Power System Protection. An end-to-end machine learning pipeline for ...

The New York Court of Appeals in Government Employees Insurance Co. v. Mayzenberg upheld that insurers can deny no-fault claims based on providers’ failure to meet licensing requirements, but not ...

As the core equipment in industrial production, rotating machinery bearings play a critical role. However, traditional feature extraction algorithms for vibration signals are susceptible to noise ...

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 ...

Abstract: Fault detection in power systems is critical for ensuring system reliability and stability. This study presents a rule-based classification approach for identifying fault types, including ...

Reliable fault detection is essential for ensuring the safe and efficient operation of electrochemical energy storage systems, including lithium-ion batteries and transformer. However, the performance ...

ABSTRACT: Rolling element bearings are commonly used in rotating machines to transmit rotation and power. On the other hand, bearing faults could be the most common reason for machinery imperfections.