SOTAVerified

Fault Diagnosis

Papers

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Showing 151–175 of 375 papers

TitleStatusHype
Robust Knowledge Extraction from Large Language Models using Social Choice Theory—0
POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning—0
Fault Diagnosis and Prognosis Capabilities for Wind Turbine Hydraulic Pitch Systems—0
Time Series Diffusion Method: A Denoising Diffusion Probabilistic Model for Vibration Signal Generation—0
Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault DiagnosisCode1
Acoustic Signal Analysis with Deep Neural Network for Detecting Fault Diagnosis in Industrial Machines—0
Real-Time Vibration-Based Bearing Fault Diagnosis Under Time-Varying Speed ConditionsCode0
Line zonotopes: A tool for state estimation and fault diagnosis of unbounded and descriptor systemsCode0
Active Foundational Models for Fault Diagnosis of Electrical Motors—0
Brain-Inspired Spiking Neural Networks for Industrial Fault Diagnosis: A Survey, Challenges, and Opportunities—0
Application of a Dense Fusion Attention Network in Fault Diagnosis of Centrifugal Fan—0
TSViT: A Time Series Vision Transformer for Fault Diagnosis—0
ABIGX: A Unified Framework for eXplainable Fault Detection and Classification—0
Contrastive Multi-Modal Representation Learning for Spark Plug Fault Diagnosis—0
Generating HSR Bogie Vibration Signals via Pulse Voltage-Guided Conditional Diffusion ModelCode1
A Sparse Bayesian Learning for Diagnosis of Nonstationary and Spatially Correlated Faults with Application to Multistation Assembly Systems—0
A Novel Transfer Learning Method Utilizing Acoustic and Vibration Signals for Rotating Machinery Fault Diagnosis—0
Weighted Joint Maximum Mean Discrepancy Enabled Multi-Source-Multi-Target Unsupervised Domain Adaptation Fault Diagnosis—0
Federated Meta-Learning for Few-Shot Fault Diagnosis with Representation Encoding—0
DDMT: Denoising Diffusion Mask Transformer Models for Multivariate Time Series Anomaly Detection—0
An improved CTGAN for data processing method of imbalanced disk failure—0
EdgeFD: An Edge-Friendly Drift-Aware Fault Diagnosis System for Industrial IoT—0
A novel asymmetrical autoencoder with a sparsifying discrete cosine Stockwell transform layer for gearbox sensor data compression—0
A Closer Look at Bearing Fault Classification Approaches—0
An Intelligent Approach to Detecting Novel Fault Classes for Centrifugal Pumps Based on Deep CNNs and Unsupervised MethodsCode0
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Benchmark Results

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