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Fault Detection

Papers

Showing 125 of 511 papers

TitleStatusHype
Multi-scale Quaternion CNN and BiGRU with Cross Self-attention Feature Fusion for Fault Diagnosis of BearingCode2
TFPred: Learning Discriminative Representations from Unlabeled Data for Few-Label Rotating Machinery Fault DiagnosisCode2
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency ConsistencyCode2
Self-Supervised Log ParsingCode2
Online Isolation ForestCode1
Integrating Physics and Data-Driven Approaches: An Explainable and Uncertainty-Aware Hybrid Model for Wind Turbine Power PredictionCode1
FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and DiagnosisCode1
Explainable fault and severity classification for rolling element bearings using Kolmogorov-Arnold networksCode1
Gaussian process-based online health monitoring and fault analysis of lithium-ion battery systems from field dataCode1
DKDL-Net: A Lightweight Bearing Fault Detection Model via Decoupled Knowledge Distillation and Low-Rank Adaptation Fine-tuningCode1
USD: Unsupervised Soft Contrastive Learning for Fault Detection in Multivariate Time SeriesCode1
A probabilistic estimation of remaining useful life from censored time-to-event dataCode1
PHMD: An easy data access tool for prognosis and health management datasetsCode1
Exploring Sound vs Vibration for Robust Fault Detection on Rotating MachineryCode1
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly GenerationCode1
Prediction of wind turbines power with physics-informed neural networks and evidential uncertainty quantificationCode1
DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT SystemsCode1
BALANCE: Bayesian Linear Attribution for Root Cause LocalizationCode1
Zero-Shot Motor Health Monitoring by Blind Domain TransitionCode1
Self-Supervised Masked Convolutional Transformer Block for Anomaly DetectionCode1
SensorSCAN: Self-Supervised Learning and Deep Clustering for Fault Diagnosis in Chemical ProcessesCode1
CIPCaD-Bench: Continuous Industrial Process datasets for benchmarking Causal Discovery methodsCode1
Explainable AI Algorithms for Vibration Data-based Fault Detection: Use Case-adadpted Methods and Critical EvaluationCode1
DeepDiagnosis: Automatically Diagnosing Faults and Recommending Actionable Fixes in Deep Learning ProgramsCode1
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive LearningCode1
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