pv magazine International

PV inverter output and anomalies predicted without environmental sensors

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...
Security Boulevard

AI-Driven Anomaly Detection in Post-Quantum Context Streams

Discover how AI-driven anomaly detection safeguards post-quantum context streams in Model Context Protocol (MCP) environments, ensuring robust security for AI infrastructure against future threats.
pv magazine International

US researchers use machine learning to detect hidden solar array defects

US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...
pv magazine USA

Machine learning models identify hidden physical defects in solar arrays

The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.
IEEE

Unified Approach to Detection of Induction Motor Faults from Vibration Signals using Hilbert Transform based Autoencoder Features and Hybrid Efficient Machine Learning Algorithms

Abstract: Since vibration signals are sensitive to changes, they are regularly used to assess the condition of rotating electrical machines. These signals include vital data that makes it possible to ...
Devdiscourse

Fast and Accurate Water Leak Detection in Distribution Networks Using Deep Anomaly Models

Researchers from Politecnico di Milano propose a data-driven water leak detection method that treats leaks as anomalies in ...