UB Paderborn / Katalog / Suche / in CDI

Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning

IEEE transactions on industrial informatics, 2019-04, Vol.15 (4), p.2446-2455

2019

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Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks

Sensors (Basel, Switzerland), 2017-01, Vol.17 (2), p.273-273

2017

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LSTM-Based Auto-Encoder Model for ECG Arrhythmias Classification

IEEE transactions on instrumentation and measurement, 2020-04, Vol.69 (4), p.1232-1240

2020

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Remaining Useful Life Prediction of Rolling Bearings Using an Enhanced Particle Filter

IEEE transactions on instrumentation and measurement, 2015-10, Vol.64 (10), p.2696-2707

2015

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Machine Health Monitoring Using Local Feature-Based Gated Recurrent Unit Networks

IEEE transactions on industrial electronics (1982), 2018-02, Vol.65 (2), p.1539-1548

2018

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Multireceptive Field Graph Convolutional Networks for Machine Fault Diagnosis

IEEE transactions on industrial electronics (1982), 2021-12, Vol.68 (12), p.12739-12749

2021

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Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis

2023

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Deep learning and its applications to machine health monitoring

Mechanical systems and signal processing, 2019-01, Vol.115, p.213-237

2019

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Sparse Feature Identification Based on Union of Redundant Dictionary for Wind Turbine Gearbox Fault Diagnosis

IEEE transactions on industrial electronics (1982), 2015-10, Vol.62 (10), p.6594-6605

2015

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Convolutional Discriminative Feature Learning for Induction Motor Fault Diagnosis

IEEE transactions on industrial informatics, 2017-06, Vol.13 (3), p.1350-1359

2017

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Hilbert-Huang Transform-Based Vibration Signal Analysis for Machine Health Monitoring

IEEE transactions on instrumentation and measurement, 2006-12, Vol.55 (6), p.2320-2329

2006

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Permutation entropy: A nonlinear statistical measure for status characterization of rotary machines

Mechanical systems and signal processing, 2012-05, Vol.29, p.474-484

2012

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A deep learning-based approach to material removal rate prediction in polishing

CIRP annals, 2017, Vol.66 (1), p.429-432

2017

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Virtualization and deep recognition for system fault classification

Journal of manufacturing systems, 2017-07, Vol.44, p.310-316

2017

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Long short-term memory for machine remaining life prediction

Journal of manufacturing systems, 2018-07, Vol.48, p.78-86

2018

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Challenges and Opportunities of AI-Enabled Monitoring, Diagnosis & Prognosis: A Review

Chinese journal of mechanical engineering, 2021-12, Vol.34 (1), p.1-29, Article 56

English ed., 2021

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Bearing Degradation Evaluation Using Recurrence Quantification Analysis and Kalman Filter

IEEE transactions on instrumentation and measurement, 2014-11, Vol.63 (11), p.2599-2610

2014

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Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems

1, 2023

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Energy-Based Feature Extraction for Defect Diagnosis in Rotary Machines

IEEE transactions on instrumentation and measurement, 2009-09, Vol.58 (9), p.3130-3139

2009

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Approximate Entropy as a diagnostic tool for machine health monitoring

Mechanical systems and signal processing, 2007-02, Vol.21 (2), p.824-839

2007

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Energy-Aware Sensor Node Design With Its Application in Wireless Sensor Networks

IEEE transactions on instrumentation and measurement, 2013-05, Vol.62 (5), p.1183-1191

2013

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A Modified DF2016 Criterion for the Fracture Modeling from Shear to Equibiaxial Tension

Materials, 2024-02, Vol.17 (4), p.958

2024

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Denoising Fault-Aware Wavelet Network: A Signal Processing Informed Neural Network for Fault Diagnosis

Chinese journal of mechanical engineering, 2023-01, Vol.36 (1), p.9-18, Article 9

English ed., 2023

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ECG Arrhythmias Detection Using Auxiliary Classifier Generative Adversarial Network and Residual Network

IEEE access, 2019, Vol.7, p.100910-100922

2019

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Harmonic wavelet-based data filtering for enhanced machine defect identification

Journal of sound and vibration, 2010-07, Vol.329 (15), p.3203-3217

2010

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Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning

Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks

LSTM-Based Auto-Encoder Model for ECG Arrhythmias Classification

Remaining Useful Life Prediction of Rolling Bearings Using an Enhanced Particle Filter

Machine Health Monitoring Using Local Feature-Based Gated Recurrent Unit Networks

Multireceptive Field Graph Convolutional Networks for Machine Fault Diagnosis

Transfer Learning for Rotary Machine Fault Diagnosis and Prognosis

Deep learning and its applications to machine health monitoring

Sparse Feature Identification Based on Union of Redundant Dictionary for Wind Turbine Gearbox Fault Diagnosis

Convolutional Discriminative Feature Learning for Induction Motor Fault Diagnosis

Hilbert-Huang Transform-Based Vibration Signal Analysis for Machine Health Monitoring

Permutation entropy: A nonlinear statistical measure for status characterization of rotary machines

A deep learning-based approach to material removal rate prediction in polishing

Virtualization and deep recognition for system fault classification

Long short-term memory for machine remaining life prediction

Challenges and Opportunities of AI-Enabled Monitoring, Diagnosis & Prognosis: A Review

Bearing Degradation Evaluation Using Recurrence Quantification Analysis and Kalman Filter

Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems

Energy-Based Feature Extraction for Defect Diagnosis in Rotary Machines

Approximate Entropy as a diagnostic tool for machine health monitoring

Energy-Aware Sensor Node Design With Its Application in Wireless Sensor Networks

A Modified DF2016 Criterion for the Fracture Modeling from Shear to Equibiaxial Tension

Denoising Fault-Aware Wavelet Network: A Signal Processing Informed Neural Network for Fault Diagnosis

ECG Arrhythmias Detection Using Auxiliary Classifier Generative Adversarial Network and Residual Network

Harmonic wavelet-based data filtering for enhanced machine defect identification

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