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A hybrid CNN-BiLSTM approach-based variational mode decomposition for tool wear monitoring

International journal of advanced manufacturing technology, 2022-03, Vol.119 (5-6), p.3803-3817

2022

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Tool wear condition monitoring based on continuous wavelet transform and blind source separation

International journal of advanced manufacturing technology, 2018-08, Vol.97 (9-12), p.3311-3323

2018

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Intelligent prognostics of bearings based on bidirectional long short-term memory and wavelet packet decomposition

International journal of advanced manufacturing technology, 2021-05, Vol.114 (1-2), p.145-157

2021

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Gearbox Failure Diagnosis Using a Multisensor Data-Fusion Machine-Learning-Based Approach

Entropy (Basel, Switzerland), 2021-06, Vol.23 (6), p.697

2021

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ANFIS-based Framework for the Prediction of Bearing’s Remaining Useful Life

International journal of prognostics and health management, 2024-01, Vol.15 (1)

2024

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Bearing Fault Event-Triggered Diagnosis Using a Variational Mode Decomposition-Based Machine Learning Approach

IEEE transactions on energy conversion, 2022-03, Vol.37 (1), p.466-474

2022

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Advancing bearing fault diagnosis under variable working conditions: a CEEMDAN-SBS approach with vibro-electric signal integration

International journal of advanced manufacturing technology, 2024-05, Vol.132 (5-6), p.2753-2772

2024

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Crack localisation in composite cantilever beams using natural frequency measurements

Nondestructive testing and evaluation, 2024-10, Vol.39 (7), p.1807-1830

2024

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Damage assessment of composite material based on variational mode decomposition and BiLSTM

International journal of advanced manufacturing technology, 2023-11, Vol.129 (3-4), p.1801-1815

2023

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A hybrid approach for gearbox fault diagnosis based on deep learning techniques

International journal of advanced manufacturing technology, 2024-07, Vol.133 (5-6), p.2861-2874

2024

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New health indicators for the monitoring of bearing failures under variable loads

Structural health monitoring, 2024-09, Vol.23 (5), p.2922-2941

2024

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Rotating machine bearing health prognosis using a data driven approach based on KS‐density and BiLSTM

IET science, measurement & technology, 2024-08

2024

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Enhancing bearing and gear fault diagnosis: A VMD-PSO approach with multisensory signal integration

Journal of vibration and control, 2024-09

2024

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Tool wear condition monitoring based on wavelet transform and improved extreme learning machine

Proceedings of the Institution of Mechanical Engineers. Part C, Journal of mechanical engineering science, 2020-03, Vol.234 (5), p.1057-1068

2020

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Deep convolutional neural networks for Bearings failure predictionand temperature correlation

Journal of Vibroengineering, 2018-12, Vol.20 (8), p.2878-2891

2018

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Crack Detection through the Change in the Normalized Frequency Shape

Vibration, 2018-09, Vol.1 (1), p.56-68

2018

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Artificial Intelligence Facing COVID-19 Pandemic for Decision Support in Algeria

2020 4th International Symposium on Informatics and its Applications (ISIA), 2020, p.1-6

2020

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Intelligent prognostics based on empirical mode decomposition and extreme learning machine

2016 8th International Conference on Modelling, Identification and Control (ICMIC), 2016, p.943-947

2016

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Deep Learning for Fault Diagnosis based on short-time Fourier transform

2018 International Conference on Smart Communications in Network Technologies (SaCoNeT), 2018, p.288-293

2018

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Tool condition monitoring based on mel-frequency cepstral coefficients and support vector regression

2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B), 2017, p.1-5

2017

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Gearbox Fault Diagnosis Based on Mel-Frequency Cepstral Coefficients and Support Vector Machine

Computational Intelligence and Its Applications, 2018, Vol.522, p.220-231

2018

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Tool Wear Condition Monitoring Based on Blind Source Separation and Wavelet Transform

Advanced Control Engineering Methods in Electrical Engineering Systems, 2019, Vol.522, p.377-389

2019

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Fault prognostic of bearings by using support vector data description

2012 IEEE Conference on Prognostics and Health Management, 2012, p.1-7

2012

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A hybrid CNN-BiLSTM approach-based variational mode decomposition for tool wear monitoring

Tool wear condition monitoring based on continuous wavelet transform and blind source separation

Intelligent prognostics of bearings based on bidirectional long short-term memory and wavelet packet decomposition

Gearbox Failure Diagnosis Using a Multisensor Data-Fusion Machine-Learning-Based Approach

ANFIS-based Framework for the Prediction of Bearing’s Remaining Useful Life

Bearing Fault Event-Triggered Diagnosis Using a Variational Mode Decomposition-Based Machine Learning Approach

Advancing bearing fault diagnosis under variable working conditions: a CEEMDAN-SBS approach with vibro-electric signal integration

Crack localisation in composite cantilever beams using natural frequency measurements

Damage assessment of composite material based on variational mode decomposition and BiLSTM

A hybrid approach for gearbox fault diagnosis based on deep learning techniques

New health indicators for the monitoring of bearing failures under variable loads

Rotating machine bearing health prognosis using a data driven approach based on KS‐density and BiLSTM

Enhancing bearing and gear fault diagnosis: A VMD-PSO approach with multisensory signal integration

Tool wear condition monitoring based on wavelet transform and improved extreme learning machine

Deep convolutional neural networks for Bearings failure predictionand temperature correlation

Crack Detection through the Change in the Normalized Frequency Shape

Artificial Intelligence Facing COVID-19 Pandemic for Decision Support in Algeria

Intelligent prognostics based on empirical mode decomposition and extreme learning machine

Deep Learning for Fault Diagnosis based on short-time Fourier transform

Tool condition monitoring based on mel-frequency cepstral coefficients and support vector regression

Gearbox Fault Diagnosis Based on Mel-Frequency Cepstral Coefficients and Support Vector Machine

Tool Wear Condition Monitoring Based on Blind Source Separation and Wavelet Transform

Fault prognostic of bearings by using support vector data description

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