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Fault Diagnosis

Papers

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Showing 251–300 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
Multi-output Classification Framework and Frequency Layer Normalization for Compound Fault Diagnosis in Motor—0
Multi-output Classification using a Cross-talk Architecture for Compound Fault Diagnosis of Motors in Partially Labeled Condition—0
Multi-scale Fusion Fault Diagnosis Method Based on Two-Dimensionaliztion Sequence in Complex Scenarios—0
Multi-sensor data fusion based on a generalised belief divergence measure—0
Multi-Source Interactive Resilient Fusion Algorithm Based on RIEKF—0
Network Tomography with Path-Centric Graph Neural Network—0
Neural Architecture Search For Fault Diagnosis—0
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation—0
Neuromorphic AI Empowered Root Cause Analysis of Faults in Emerging Networks—0
A New Approach for Verification of Delay Coobservability of Discrete-Event Systems—0
Detection of Nonlinear Behavior in Voltage Source Converter Control in Wind Farms Based on Higher-Order Spectral Analysis—0
NonSysId: A nonlinear system identification package with improved model term selection for NARMAX models—0
Offline and Online Use of Interval and Set-Based Approaches for Control and State Estimation: A Selection of Methodological Approaches and Their Application—0
On-board Fault Diagnosis of a Laboratory Mini SR-30 Gas Turbine Engine—0
Optimized Spectral Fault Receptive Fields for Diagnosis-Informed Prognosis—0
Optimizing a Digital Twin for Fault Diagnosis in Grid Connected Inverters -- A Bayesian Approach—0
Oversampling Adversarial Network for Class-Imbalanced Fault Diagnosis—0
PCA Methods and Evidence Based Filtering for Robust Aircraft Sensor Fault Diagnosis—0
Personalized Federated Learning for Multi-task Fault Diagnosis of Rotating Machinery—0
Physics-Informed Deep Learning and Partial Transfer Learning for Bearing Fault Diagnosis in the Presence of Highly Missing Data—0
Power System Fault Diagnosis with Quantum Computing and Efficient Gate Decomposition—0
Power Transformer Fault Diagnosis with Intrinsic Time-scale Decomposition and XGBoost Classifier—0
Pre-Processing-Free Gear Fault Diagnosis Using Small Datasets with Deep Convolutional Neural Network-Based Transfer Learning—0
Process mining-driven modeling and simulation to enhance fault diagnosis in cyber-physical systems—0
Process monitoring based on orthogonal locality preserving projection with maximum likelihood estimation—0
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Benchmark Results

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