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Fault Diagnosis

Papers

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Showing 51–75 of 375 papers

TitleStatusHype
A crayfish-optimized wavelet filter and its application to fault diagnosis—0
Advancing machine fault diagnosis: A detailed examination of convolutional neural networks—0
Hybrid Resolver Model Generalization for Fault Condition Modeling: A Promising Tool for Reliability Study—0
AI Explainability for Power Electronics: From a Lipschitz Continuity Perspective—0
Class Incremental Fault Diagnosis under Limited Fault Data via Supervised Contrastive Knowledge DistillationCode0
Knowledge Distillation and Enhanced Subdomain Adaptation Using Graph Convolutional Network for Resource-Constrained Bearing Fault Diagnosis—0
A Multimodal Lightweight Approach to Fault Diagnosis of Induction Motors in High-Dimensional Dataset—0
Are GNNs Actually Effective for Multimodal Fault Diagnosis in Microservice Systems?—0
Multi-Condition Fault Diagnosis of Dynamic Systems: A Survey, Insights, and ProspectsCode0
Evaluating deep learning models for fault diagnosis of a rotating machinery with epistemic and aleatoric uncertainty—0
An Improved Fault Diagnosis Strategy for Induction Motors Using Weighted Probability Ensemble Deep Learning—0
Towards Fault Diagnosis in Induction Motor using Fractional Fourier Transform—0
SubstationAI: Multimodal Large Model-Based Approaches for Analyzing Substation Equipment Faults—0
Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics with Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis—0
TelApart: Differentiating Network Faults from Customer-Premise Faults in Cable Broadband Networks—0
A Review of Intelligent Device Fault Diagnosis Technologies Based on Machine Vision—0
Thermal Image-based Fault Diagnosis in Induction Machines via Self-Organized Operational Neural Networks—0
Granular Ball K-Class Twin Support Vector Classifier—0
Model-Agnostic Meta-Learning for Fault Diagnosis of Induction Motors in Data-Scarce Environments with Varying Operating Conditions and Electric Drive Noise—0
Uncertainty-Aware Artificial Intelligence for Gear Fault Diagnosis in Motor Drives—0
Explainable fault and severity classification for rolling element bearings using Kolmogorov-Arnold networksCode1
FD-LLM: Large Language Model for Fault Diagnosis of Machines—0
Residual Attention Single-Head Vision Transformer Network for Rolling Bearing Fault Diagnosis in Noisy Environments—0
NonSysId: A nonlinear system identification package with improved model term selection for NARMAX models—0
Domain Adaptation-based Edge Computing for Cross-Conditions Fault Diagnosis—0
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Benchmark Results

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