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Deep learning for smart manufacturing: Methods and applications

Journal of manufacturing systems, 2018-07, Vol.48, p.144-156

2018

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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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A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests

Journal of manufacturing science and engineering, 2017-07, Vol.139 (7)

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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Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook

Journal of manufacturing science and engineering, 2020-11, Vol.142 (11)

2020

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State of AI-Based Monitoring in Smart Manufacturing and Introduction to Focused Section

IEEE/ASME transactions on mechatronics, 2020-10, Vol.25 (5), p.2143-2154

2020

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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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Deep Learning-Driven Data Curation and Model Interpretation for Smart Manufacturing

Chinese journal of mechanical engineering, 2021-12, Vol.34 (1), p.1-21, Article 71

English ed., 2021

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A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing

Chinese journal of mechanical engineering, 2017-11, Vol.30 (6), p.1347-1356

English ed., 2017

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Performance enhancement of ensemble empirical mode decomposition

Mechanical systems and signal processing, 2010-10, Vol.24 (7), p.2104-2123

2010

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A multi-time scale approach to remaining useful life prediction in rolling bearing

Mechanical systems and signal processing, 2017-01, Vol.83, p.549-567

2017

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Digital Twin for rotating machinery fault diagnosis in smart manufacturing

International journal of production research, 2019-06, Vol.57 (12), p.3920-3934

2019

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DCNN-Based Multi-Signal Induction Motor Fault Diagnosis

IEEE transactions on instrumentation and measurement, 2020-06, Vol.69 (6), p.2658-2669

2020

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Deep learning-based tensile strength prediction in fused deposition modeling

Computers in industry, 2019-05, Vol.107, p.11-21

2019

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A New Intelligent Bearing Fault Diagnosis Method Using SDP Representation and SE-CNN

IEEE transactions on instrumentation and measurement, 2020-05, Vol.69 (5), p.2377-2389

2020

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An integrated fault diagnosis and prognosis approach for predictive maintenance of wind turbine bearing with limited samples

Renewable energy, 2020-01, Vol.145, p.642-650

2020

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Deep heterogeneous GRU model for predictive analytics in smart manufacturing: Application to tool wear prediction

Computers in industry, 2019-10, Vol.111, p.1-14

2019

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Multilevel Information Fusion for Induction Motor Fault Diagnosis

IEEE/ASME transactions on mechatronics, 2019-10, Vol.24 (5), p.2139-2150

2019

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Hybrid machine learning for human action recognition and prediction in assembly

Robotics and computer-integrated manufacturing, 2021-12, Vol.72, p.102184, Article 102184

2021

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Machine vision intelligence for product defect inspection based on deep learning and Hough transform

Journal of manufacturing systems, 2019-04, Vol.51, p.52-60

2019

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Recurrent neural network for motion trajectory prediction in human-robot collaborative assembly

CIRP annals, 2020, Vol.69 (1), p.9-12

2020

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A Novel Hybrid Error Criterion-Based Active Control Method for on-Line Milling Vibration Suppression with Piezoelectric Actuators and Sensors

Sensors (Basel, Switzerland), 2016-01, Vol.16 (1), p.68-68

2016

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WaveletKernelNet: An Interpretable Deep Neural Network for Industrial Intelligent Diagnosis

IEEE transactions on systems, man, and cybernetics. Systems, 2022-04, Vol.52 (4), p.2302-2312

2022

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AI-Enabled Monitoring, Diagnosis & Prognosis

Chinese journal of mechanical engineering, 2021-12, Vol.34 (1), p.1-2, Article 68

English ed., 2021

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Toward cognitive predictive maintenance: A survey of graph-based approaches

Journal of manufacturing systems, 2022-07, Vol.64, p.107-120

2022

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Deep learning for smart manufacturing: Methods and applications

Deep learning and its applications to machine health monitoring

A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests

Long short-term memory for machine remaining life prediction

Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook

State of AI-Based Monitoring in Smart Manufacturing and Introduction to Focused Section

Approximate Entropy as a diagnostic tool for machine health monitoring

Deep Learning-Driven Data Curation and Model Interpretation for Smart Manufacturing

A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing

Performance enhancement of ensemble empirical mode decomposition

A multi-time scale approach to remaining useful life prediction in rolling bearing

Digital Twin for rotating machinery fault diagnosis in smart manufacturing

DCNN-Based Multi-Signal Induction Motor Fault Diagnosis

Deep learning-based tensile strength prediction in fused deposition modeling

A New Intelligent Bearing Fault Diagnosis Method Using SDP Representation and SE-CNN

An integrated fault diagnosis and prognosis approach for predictive maintenance of wind turbine bearing with limited samples

Deep heterogeneous GRU model for predictive analytics in smart manufacturing: Application to tool wear prediction

Multilevel Information Fusion for Induction Motor Fault Diagnosis

Hybrid machine learning for human action recognition and prediction in assembly

Machine vision intelligence for product defect inspection based on deep learning and Hough transform

Recurrent neural network for motion trajectory prediction in human-robot collaborative assembly

A Novel Hybrid Error Criterion-Based Active Control Method for on-Line Milling Vibration Suppression with Piezoelectric Actuators and Sensors

WaveletKernelNet: An Interpretable Deep Neural Network for Industrial Intelligent Diagnosis

AI-Enabled Monitoring, Diagnosis & Prognosis

Toward cognitive predictive maintenance: A survey of graph-based approaches

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