SOTAVerified

Fault Diagnosis

Papers

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Showing 251–275 of 375 papers

TitleStatusHype
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
Structural Vibration Signal Denoising Using Stacking Ensemble of Hybrid CNN-RNN—0
VSLLaVA: a pipeline of large multimodal foundation model for industrial vibration signal analysis—0
Wasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis—0
Weighted Joint Maximum Mean Discrepancy Enabled Multi-Source-Multi-Target Unsupervised Domain Adaptation Fault Diagnosis—0
Linguistic Ordered Weighted Averaging based deep learning pooling for fault diagnosis in a wastewater treatment plant—0
LLM-based Framework for Bearing Fault Diagnosis—0
Machine Learning-based Anomaly Detection in Optical Fiber Monitoring—0
Machine learning-based approach for online fault Diagnosis of Discrete Event System—0
Model-Agnostic Meta-Learning for Fault Diagnosis of Induction Motors in Data-Scarce Environments with Varying Operating Conditions and Electric Drive Noise—0
Modeling and Soft-fault Diagnosis of Underwater Thrusters with Recurrent Neural Networks—0
Intelligent Condition Based Monitoring Techniques for Bearing Fault Diagnosis—0
Multi-Fault Diagnosis Of Industrial Rotating Machines Using Data-Driven Approach: A Review Of Two Decades Of Research—0
Multi-label Classification for Fault Diagnosis of Rotating Electrical Machines—0
Multi-mode Fault Diagnosis Datasets of Gearbox Under Variable Working Conditions—0
Multi-output Classification for Compound Fault Diagnosis in Motor under Partially Labeled Target Domain—0
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Benchmark Results

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