Remaining useful life prediction of bearing based on stacked autoencoder and recurrent neural network

Remaining useful life prediction of roller bearings based on improved 1D-CNN and simple recurrent unit

(2021) Dechen Yao et al.   MEASUREMENT

A novel approach for predicting tool remaining useful life using limited data

(2020) Hai Li et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A joint classification-regression method for multi-stage remaining useful life prediction

(2020) Ji-Yan Wu et al.   JOURNAL OF MANUFACTURING SYSTEMS

Remaining useful life prediction of induction motors using nonlinear degradation of health index

(2020) Feng Yang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A deep autoencoder feature learning method for process pattern recognition

(2019) Jianbo Yu et al.   JOURNAL OF PROCESS CONTROL

Fault diagnosis of rolling bearings with recurrent neural network-based autoencoders

(2018) Han Liu et al.   ISA TRANSACTIONS

Long short-term memory for machine remaining life prediction

(2018) Jianjing Zhang et al.   JOURNAL OF MANUFACTURING SYSTEMS

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

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

Machinery health prognostics: A systematic review from data acquisition to RUL prediction

(2018) Yaguo Lei et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

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

(2017) Dazhong Wu et al.   JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME

Multi-bearing remaining useful life collaborative prediction: A deep learning approach

(2017) Lei Ren et al.   JOURNAL OF MANUFACTURING SYSTEMS

A Model-Based Method for Remaining Useful Life Prediction of Machinery

(2016) Yaguo Lei et al.   IEEE TRANSACTIONS ON RELIABILITY

A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings

(2016) Akhand Rai et al.   TRIBOLOGY INTERNATIONAL

Bearing Health Monitoring Based on Hilbert–Huang Transform, Support Vector Machine, and Regression

(2015) Abdenour Soualhi et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Support vector machine based estimation of remaining useful life: current research status and future trends

(2015) Hong-Zhong Huang et al.   Journal of Mechanical Science and Technology

Bearing fault prognosis based on health state probability estimation

(2011) Hack-Eun Kim et al.   EXPERT SYSTEMS WITH APPLICATIONS

An artificial neural network method for remaining useful life prediction of equipment subject to condition monitoring

(2009) Zhigang Tian   JOURNAL OF INTELLIGENT MANUFACTURING