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Fault Diagnosis

Papers

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Showing 101–125 of 375 papers

TitleStatusHype
A Federated Distributionally Robust Support Vector Machine with Mixture of Wasserstein Balls Ambiguity Set for Distributed Fault Diagnosis—0
A Cost-Sensitive Deep Belief Network for Imbalanced Classification—0
A Closer Look at Bearing Fault Classification Approaches—0
Constructive Incremental Learning for Fault Diagnosis of Rolling Bearings with Ensemble Domain Adaptation—0
Consultation on Industrial Machine Faults with Large language Models—0
Contrastive Multi-Modal Representation Learning for Spark Plug Fault Diagnosis—0
Cross-Domain Open-Set Machinery Fault Diagnosis Based on Adversarial Network With Multiple Auxiliary Classifiers—0
Data-driven design of fault diagnosis for three-phase PWM rectifier using random forests technique with transient synthetic features—0
Data-driven Machinery Fault Detection: A Comprehensive Review—0
Data-Driven Fault Diagnosis Analysis and Open-Set Classification of Time-Series Data—0
A BiLSTM-CNN based Multitask Learning Approach for Fiber Fault Diagnosis—0
Data-Folding and Hyperspace Coding for Multi-Dimensonal Time-Series Data Imaging—0
Data fusion techniques for fault diagnosis of industrial machines: a survey—0
DDMT: Denoising Diffusion Mask Transformer Models for Multivariate Time Series Anomaly Detection—0
Decimation analysis in the signal processing of current to detect broken bars in induction machine—0
Deep Fault Diagnosis for Rotating Machinery with Scarce Labeled Samples—0
Can Hessian-Based Insights Support Fault Diagnosis in Attention-based Models?—0
An improved CTGAN for data processing method of imbalanced disk failure—0
CADM: Confusion Model-based Detection Method for Real-drift in Chunk Data Stream—0
Deep Prototypical Networks Based Domain Adaptation for Fault Diagnosis—0
Deep Subspace Learning for Surface Anomaly Classification Based on 3D Point Cloud Data—0
Deep Transfer Network with Joint Distribution Adaptation: A New Intelligent Fault Diagnosis Framework for Industry Application—0
Brain-Inspired Spiking Neural Networks for Industrial Fault Diagnosis: A Survey, Challenges, and Opportunities—0
Designing a lightweight 1D convolutional neural network with Bayesian optimization for wheel flat detection using carbody accelerations:—0
An Explainable Artificial Intelligence Approach for Unsupervised Fault Detection and Diagnosis in Rotating Machinery—0
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Benchmark Results

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