A Deep Learning Method for Bearing Fault Diagnosis through Stacked Residual Dilated Convolutions

An enhanced convolutional neural network with enlarged receptive fields for fault diagnosis of planetary gearboxes

(2019) Yan Han et al.   COMPUTERS IN INDUSTRY

A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method

(2018) Long Wen et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Time–frequency analysis based on ensemble local mean decomposition and fast kurtogram for rotating machinery fault diagnosis

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

A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load

(2018) Wei Zhang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Multiband Envelope Spectra Extraction for Fault Diagnosis of Rolling Element Bearings

(2018) Jie Duan et al.   SENSORS

A Convolutional Neural Network Based on a Capsule Network with Strong Generalization for Bearing Fault Diagnosis

(2018) Zhiyu Zhu et al.   NEUROCOMPUTING

Deep Learning Based Approach for Bearing Fault Diagnosis

(2017) Miao He et al.   IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS

A convolutional neural network based feature learning and fault diagnosis method for the condition monitoring of gearbox

(2017) Luyang Jing et al.   MEASUREMENT

A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals

(2017) Wei Zhang et al.   SENSORS

Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification

(2017) Chen Lu et al.   SIGNAL PROCESSING

An on-line condition monitoring system for induction motors via instantaneous power analysis

(2015) M. Irfan et al.   Journal of Mechanical Science and Technology

Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study

(2015) Wade A. Smith et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups

(2012) Geoffrey Hinton et al.   IEEE SIGNAL PROCESSING MAGAZINE

Noise resistant time frequency analysis and application in fault diagnosis of rolling element bearings

(2012) Guangming Dong et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A hybrid feature selection scheme for unsupervised learning and its application in bearing fault diagnosis

(2011) Yang Yang et al.   EXPERT SYSTEMS WITH APPLICATIONS

Rolling element bearing diagnostics—A tutorial

(2010) Robert B. Randall et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Rolling element bearing fault diagnosis based on the combination of genetic algorithms and fast kurtogram

(2009) Yongxiang Zhang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING