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Fault Detection

Papers

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Showing 326–350 of 511 papers

TitleStatusHype
Integrated Fault Diagnosis and Control Design for DER Inverters using Machine Learning Methods—0
An alternative paradigm of fault diagnosis in dynamic systems: orthogonal projection-based methods—0
Deep Convolutional Autoencoder for Assessment of Drive-Cycle Anomalies in Connected Vehicle Sensor Data—0
Fault Detection and Diagnosis with Imbalanced and Noisy Data: A Hybrid Framework for Rotating Machinery—0
Transfer Learning for Fault Diagnosis of Transmission Lines—0
Reconfigurable Control of a Class of Multicopters—0
Black-Box Testing of Deep Neural Networks Through Test Case DiversityCode0
Learnable Faster Kernel-PCA for Nonlinear Fault Detection: Deep Autoencoder-Based Realization—0
DeepDiagnosis: Automatically Diagnosing Faults and Recommending Actionable Fixes in Deep Learning ProgramsCode1
Smart Metering System Capable of Anomaly Detection by Bi-directional LSTM Autoencoder—0
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive LearningCode1
PreGAN: Preemptive Migration Prediction Network for Proactive Fault-Tolerant Edge ComputingCode1
In situ process quality monitoring and defect detection for direct metal laser melting—0
Semi-Supervised Surface Anomaly Detection of Composite Wind Turbine Blades From Drone Imagery—0
An improved bearing fault detection strategy based on artificial bee colony algorithm—0
A Natural Language Processing and Deep Learning based Model for Automated Vehicle Diagnostics using Free-Text Customer Service Reports—0
Fault Diagnosis of Nonlinear Systems Using a Hybrid-Degree Dual Cubature-based Estimation Scheme—0
HASHTAG: Hash Signatures for Online Detection of Fault-Injection Attacks on Deep Neural Networks—0
Fault-Tolerant Performance Enhancement of DC-DC Converters with High-Speed Fault Clearing-unit based Redundant Power Switch Configurations—0
StreaMulT: Streaming Multimodal Transformer for Heterogeneous and Arbitrary Long Sequential Data—0
DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration TestingCode1
CNN-DST: ensemble deep learning based on Dempster-Shafer theory for vibration-based fault recognition—0
MD Loss: Efficient Training of 3D Seismic Fault Segmentation Network under Sparse Labels by Weakening Anomaly AnnotationCode1
Non-Invasive Fault Detection of Stator Windings of Induction Motors—0
Data-driven Residual Generation for Early Fault Detection with Limited Data—0
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