MSWR-LRCN: A new deep learning approach to remaining useful life estimation of bearings

Remaining useful life prediction for ion etching machine cooling system using deep recurrent neural network-based approaches

(2021) Shimeng Wu et al.   CONTROL ENGINEERING PRACTICE

An improved ensemble fusion autoencoder model for fault diagnosis from imbalanced and incomplete data

(2020) Jing Yang et al.   CONTROL ENGINEERING PRACTICE

An audio-based intelligent fault diagnosis method for belt conveyor rollers in sand carrier

(2020) Chen Peng et al.   CONTROL ENGINEERING PRACTICE

CorNET: Deep Learning Framework for PPG-Based Heart Rate Estimation and Biometric Identification in Ambulant Environment

(2019) Dwaipayan Biswas et al.   IEEE Transactions on Biomedical Circuits and Systems

Rub-Impact Fault Diagnosis of Rotating Machinery Based on 1-D Convolutional Neural Networks

(2019) Xinya Wu et al.   IEEE SENSORS JOURNAL

Deep Residual Shrinkage Networks for Fault Diagnosis

(2019) Minghang Zhao et al.   IEEE Transactions on Industrial Informatics

A Prognostic Model Based on DBN and Diffusion Process for Degrading Bearing

(2019) Chang-Hua Hu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Estimation of Bearing Remaining Useful Life based on Multiscale Convolutional Neural Network

(2018) Jun Zhu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Bearing remaining useful life prediction based on deep autoencoder and deep neural networks

(2018) Lei Ren et al.   JOURNAL OF MANUFACTURING SYSTEMS

Remaining useful life estimation of engineered systems using vanilla LSTM neural networks

(2018) Yuting Wu et al.   NEUROCOMPUTING

Remaining useful life estimation in prognostics using deep convolution neural networks

(2018) Xiang Li et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Bidirectional handshaking LSTM for remaining useful life prediction

(2018) Ahmed Elsheikh et al.   NEUROCOMPUTING

Predicting remaining useful life of rolling bearings based on deep feature representation and long short-term memory neural network

(2018) Wentao Mao et al.   Advances in Mechanical Engineering

Study on fatigue growth of multi-surface flaws in shaft under rotary bending by S-FEM

(2017) Kazuhiro Suga et al.   ENGINEERING FRACTURE MECHANICS

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

(2017) Yuning Qian et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Bearing performance degradation assessment based on a combination of empirical mode decomposition and k-medoids clustering

(2017) Akhand Rai et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Data-driven hybrid remaining useful life estimation approach for spacecraft lithium-ion battery

(2017) Yuchen Song et al.   MICROELECTRONICS RELIABILITY

A recurrent neural network based health indicator for remaining useful life prediction of bearings

(2017) Liang Guo et al.   NEUROCOMPUTING

Intelligent bearing performance degradation assessment and remaining useful life prediction based on self-organising map and support vector regression

(2017) Akhand Rai et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE

A New Method Based on Stochastic Process Models for Machine Remaining Useful Life Prediction

(2016) Yaguo Lei et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Sequential Monte-Carlo sampling based on a committee of artificial neural networks for posterior state estimation and residual lifetime prediction

(2016) C. Sbarufatti et al.   INTERNATIONAL JOURNAL OF FATIGUE

Remaining life prediction of rolling bearing based on PCA and improved logistic regression model

(2016) Bei Wang et al.   Journal of Vibroengineering

An Improved Exponential Model for Predicting Remaining Useful Life of Rolling Element Bearings

(2015) Naipeng Li et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Dynamic Reliability Assessment for Multi-State Systems Utilizing System-Level Inspection Data

(2015) Yu Liu et al.   IEEE TRANSACTIONS ON RELIABILITY

An integrated unscented kalman filter and relevance vector regression approach for lithium-ion battery remaining useful life and short-term capacity prediction

(2015) Xiujuan Zheng et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Dynamic modelling of wear evolution in rolling bearings

(2015) Idriss El-Thalji et al.   TRIBOLOGY INTERNATIONAL

Condition assessment for the performance degradation of bearing based on a combinatorial feature extraction method

(2014) Sheng Hong et al.   DIGITAL SIGNAL PROCESSING

Discovering Prognostic Features Using Genetic Programming in Remaining Useful Life Prediction

(2013) Linxia Liao   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Combining Relevance Vector Machines and exponential regression for bearing residual life estimation

(2012) Francesco Di Maio et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Machine performance degradation assessment and remaining useful life prediction using proportional hazard model and support vector machine

(2012) Van Tung Tran et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING