Tag: fault diagnosis

A new video-based diagnostic model combining the Grey Wolf Optimizer and a neural network identifies faults in oil-immersed transformers online ...

Researchers developed a two-stage random forest framework that classifies faults in Sallen–Key and Chebyshev analog filter circuits with about 98.5% ...

A new incremental few-shot fault diagnosis framework uses a diffusion model to generate synthetic samples for rare new fault classes, ...

The distinction between local vibration responses and machine-level load variations reflects a fundamental division in how rotating and reciprocating machinery ...

Researchers at Cranfield University built a digital twin of aircraft electromechanical actuators that generated 70,000 labelled fault simulations to train ...

Researchers have trained a reinforcement learning system that autonomously plans collisions between robots to determine whether a malfunctioning agent's fault ...

Researchers at Shanghai Jiao Tong University have developed a fault diagnosis framework that uses recurrent attentional reinforcement learning to adaptively ...

A new deep learning framework converts bearing vibration signals into dynamically weighted texture images and classifies them with a hybrid ...

Researchers have developed an RBF neural network framework that combines physics-based trend monitoring with deep learning to detect, isolate, and ...

Researchers combined Monte Carlo Tree Search-tuned deep reinforcement learning with the GEMMA industrial safety framework to detect equipment faults early ...