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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 Log ParsingCode2
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency ConsistencyCode2
Gaussian process-based online health monitoring and fault analysis of lithium-ion battery systems from field dataCode1
Online Forecasting and Anomaly Detection Based on the ARIMA ModelCode1
Online Isolation ForestCode1
Exploring Sound vs Vibration for Robust Fault Detection on Rotating MachineryCode1
GPLA-12: An Acoustic Signal Dataset of Gas Pipeline LeakageCode1
FaultNet: A Deep Convolutional Neural Network for bearing fault classificationCode1
DeepDiagnosis: Automatically Diagnosing Faults and Recommending Actionable Fixes in Deep Learning ProgramsCode1
Machine Learning-Based Unbalance Detection of a Rotating Shaft Using Vibration DataCode1
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly GenerationCode1
DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration TestingCode1
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive LearningCode1
Explainable AI Algorithms for Vibration Data-based Fault Detection: Use Case-adadpted Methods and Critical EvaluationCode1
MD Loss: Efficient Training of 3D Seismic Fault Segmentation Network under Sparse Labels by Weakening Anomaly AnnotationCode1
A probabilistic estimation of remaining useful life from censored time-to-event dataCode1
BALANCE: Bayesian Linear Attribution for Root Cause LocalizationCode1
Bearing Fault Diagnosis Base on Multi-scale CNN and LSTM ModelCode1
FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and DiagnosisCode1
CIPCaD-Bench: Continuous Industrial Process datasets for benchmarking Causal Discovery methodsCode1
DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT SystemsCode1
DKDL-Net: A Lightweight Bearing Fault Detection Model via Decoupled Knowledge Distillation and Low-Rank Adaptation Fine-tuningCode1
Ellipsotopes: Combining Ellipsoids and Zonotopes for Reachability Analysis and Fault DetectionCode1
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