SOTAVerified

Fault Diagnosis

Papers

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Showing 276–300 of 375 papers

TitleStatusHype
Synthesizing Rolling Bearing Fault Samples in New Conditions: A framework based on a modified CGAN—0
Synthetic to Real Framework based on Convolutional Multi-Head Attention and Hybrid Domain Alignment—0
System Resilience through Health Monitoring and Reconfiguration—0
T4PdM: a Deep Neural Network based on the Transformer Architecture for Fault Diagnosis of Rotating Machinery—0
TDANet: A Novel Temporal Denoise Convolutional Neural Network With Attention for Fault Diagnosis—0
Technical Language Supervision for Intelligent Fault Diagnosis in Process Industry—0
TelApart: Differentiating Network Faults from Customer-Premise Faults in Cable Broadband Networks—0
The LiU-ICE Benchmark -- An Industrial Fault Diagnosis Case Study—0
Thermal Image-based Fault Diagnosis in Induction Machines via Self-Organized Operational Neural Networks—0
The State of the Art in transformer fault diagnosis with artificial intelligence and Dissolved Gas Analysis: A Review of the Literature—0
Three-dimensional instantaneous orbit map for rotor-bearing system based on a novel multivariate complex variational mode decomposition algorithm—0
Time Series Diffusion Method: A Denoising Diffusion Probabilistic Model for Vibration Signal Generation—0
Toward Debugging Deep Reinforcement Learning Programs with RLExplorer—0
Toward End-to-End Bearing Fault Diagnosis for Industrial Scenarios with Spiking Neural Networks—0
Towards a Universal Vibration Analysis Dataset: A Framework for Transfer Learning in Predictive Maintenance and Structural Health Monitoring—0
Towards Fault Diagnosis in Induction Motor using Fractional Fourier Transform—0
Towards federated multivariate statistical process control (FedMSPC)—0
Knowledge Transfer based Evolutionary Deep Neural Network for Intelligent Fault Diagnosis—0
Transfer Learning for Fault Diagnosis of Transmission Lines—0
TSViT: A Time Series Vision Transformer for Fault Diagnosis—0
UBMF: Uncertainty-Aware Bayesian Meta-Learning Framework for Fault Diagnosis with Imbalanced Industrial Data—0
Uncertainty-Aware Artificial Intelligence for Gear Fault Diagnosis in Motor Drives—0
UniFault: A Fault Diagnosis Foundation Model from Bearing Data—0
Unsupervised Clustering for Fault Analysis in High-Voltage Power Systems Using Voltage and Current Signals—0
Vibration Fault Diagnosis in Wind Turbines based on Automated Feature Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DANNAccuray80.22—Unverified
2LSTMAccuray61.56—Unverified