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Prognostics and Health Management of Rotating Machinery of Industrial Robot with Deep Learning Applications—A Review

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Trends in Smart Manufacturing: Role of Humans and Industrial Robots in Smart Factories
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Fault diagnosis of rolling bearings with recurrent neural network-based autoencoders
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Deep convolutional neural network based on adaptive gradient optimizer for fault detection in SCIM
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Attitude data-based deep hybrid learning architecture for intelligent fault diagnosis of multi-joint industrial robots
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One-dimensional convolutional auto-encoder-based feature learning for fault diagnosis of multivariate processes
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Convolutional Neural Network Based Fault Detection for Rotating Machinery
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Survey on Deep Neural Networks in Speech and Vision Systems
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Fault Diagnosis of Ball Screw in Industrial Robots Using Non-Stationary Motor Current Signals
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Application of Generalized Frequency Response Functions and Improved Convolutional Neural Network to Fault Diagnosis of Heavy-duty Industrial Robot
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Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction
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Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks
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Deep Convolutional and LSTM Recurrent Neural Networks for Rolling Bearing Fault Diagnosis Under Strong Noises and Variable Loads
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Deep Residual Learning for Image Recognition
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Multi-joint Industrial Robot Fault Identification using Deep Sparse Auto-Encoder Network with Attitude Data
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Rolling bearing fault diagnosis based on Deep Boltzmann machines
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Industrial Robot Rotate Vector Reducer Fault Detection Based on Hidden Markov Models
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Industrial Robot Fault Detection Based on Wavelet Transform and LabVIEW
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Satellite fault diagnosis using a bank of interacting Kalman filters
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Extended Kalman Filtering for Remaining-Useful-Life Estimation of Bearings
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Motor Bearing Fault Detection Using Spectral Kurtosis-Based Feature Extraction Coupled With K -Nearest Neighbor Distance Analysis
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Hidden Markov Models for the Prediction of Impending Faults
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Deep Model Based Domain Adaptation for Fault Diagnosis
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Estimation of Bearing Remaining Useful Life Based on Multiscale Convolutional Neural Network
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Macroscopic–Microscopic Attention in LSTM Networks Based on Fusion Features for Gear Remaining Life Prediction
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Distribution-Invariant Deep Belief Network for Intelligent Fault Diagnosis of Machines Under New Working Conditions
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Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning
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Anomaly Detection and Fault Prognosis for Bearings
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Multisensor Feature Fusion for Bearing Fault Diagnosis Using Sparse Autoencoder and Deep Belief Network
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A Motor Current Signal-Based Bearing Fault Diagnosis Using Deep Learning and Information Fusion
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Critical Wind Turbine Components Prognostics: A Comprehensive Review
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Using Deep Learning-Based Approach to Predict Remaining Useful Life of Rotating Components
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A Neural Network Integrated Decision Support System for Condition-Based Optimal Predictive Maintenance Policy
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A New Approach to the Challenge of Machinery Prognostics
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Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook
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Integrated multi-sensor package (IMSP) for unmanned vehicle operations
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MOBILE ROBOT MOTOR BEARING FAULT DETECTION AND CLASSIFICATION ON DISCRETE WAVELET TRANSFORM AND LSTM NETWORK
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Rolling Bearing Fault Diagnosis Based on STFT-Deep Learning and Sound Signals
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Reliable Fault Diagnosis of Rotary Machine Bearings Using a Stacked Sparse Autoencoder‐Based Deep Neural Network
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