Connected Components-based Colour Image Representations of Vibrations for a Two-stage Fault Diagnosis of Roller Bearings Using Convolutional Neural Networks

An unsupervised fault diagnosis method for rolling bearing using STFT and generative neural networks

(2020) Hongfeng Tao et al.   JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS

An enhanced convolutional neural network for bearing fault diagnosis based on time–frequency image

(2020) Ying Zhang et al.   MEASUREMENT

Fault Diagnosis of Active Magnetic Bearing–Rotor System via Vibration Images

(2019) Xunshi Yan et al.   SENSORS

A novel bearing fault diagnosis method based on 2-D image representation and transfer learning–convolutional neural network

(2019) Ping Ma et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Bearing performance degradation assessment using long short-term memory recurrent network

(2019) Bin Zhang et al.   COMPUTERS IN INDUSTRY

Rotor fault diagnosis using a convolutional neural network with symmetrized dot pattern images

(2019) Xiaoxun Zhu et al.   MEASUREMENT

An improved feature extraction method using texture analysis with LBP for bearing fault diagnosis

(2019) Kaplan Kaplan et al.   APPLIED SOFT COMPUTING

Rolling element bearing fault diagnosis using convolutional neural network and vibration image

(2018) Duy-Tang Hoang et al.   Cognitive Systems Research

Rolling bearing fault detection using continuous deep belief network with locally linear embedding

(2018) Haidong Shao 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

Scalable and Unsupervised Feature Engineering Using Vibration-Imaging and Deep Learning for Rotor System Diagnosis

(2018) Hyunseok Oh et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

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

(2018) Han Liu et al.   ISA TRANSACTIONS

Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse over-complete features

(2018) H.O.A. Ahmed et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Rolling Bearing Fault Diagnosis Using Modified LFDA and EMD With Sensitive Feature Selection

(2018) Xiao Yu et al.   IEEE Access

Bearing Fault Diagnosis Using Fully-Connected Winner-Take-All Autoencoder

(2018) Chuanhao Li et al.   IEEE Access

Three-stage Hybrid Fault Diagnosis for Rolling Bearings with Compressively-sampled data and Subspace Learning Techniques

(2018) Hosameldin Ahmed et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

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

(2018) Zhiyu Zhu et al.   NEUROCOMPUTING

Compressive Sampling and Feature Ranking Framework for Bearing Fault Classification With Vibration Signals

(2018) Hosameldin Ahmed et al.   IEEE Access

Bearing Fault Diagnosis under Variable Rotational Speeds Using Stockwell Transform-Based Vibration Imaging and Transfer Learning

(2018) Md Junayed Hasan et al.   Applied Sciences-Basel

A novel convolutional neural network based fault recognition method via image fusion of multi-vibration-signals

(2018) Huaqing Wang et al.   COMPUTERS IN INDUSTRY

Deep Learning Based Approach for Bearing Fault Diagnosis

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

Deep neural networks-based rolling bearing fault diagnosis

(2017) Zhiqiang Chen et al.   MICROELECTRONICS RELIABILITY

Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings

(2017) David Verstraete et al.   SHOCK AND VIBRATION

Motor Bearing Fault Detection Using Spectral Kurtosis-Based Feature Extraction Coupled With K-Nearest Neighbor Distance Analysis

(2016) Jing Tian et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

(2016) Nima Tajbakhsh et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Convolutional Neural Network Based Fault Detection for Rotating Machinery

(2016) Olivier Janssens et al.   JOURNAL OF SOUND AND VIBRATION

Hierarchical adaptive deep convolution neural network and its application to bearing fault diagnosis

(2016) Xiaojie Guo et al.   MEASUREMENT

Bearing fault diagnosis based on spectrum images of vibration signals

(2016) Wei Li et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data

(2016) Feng Jia et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Bearing Fault Diagnosis Based on Deep Belief Network and Multisensor Information Fusion

(2016) Jie Tao et al.   SHOCK AND VIBRATION

Fault Diagnosis for Rotating Machinery: A Method based on Image Processing

(2016) Chen Lu et al.   PLoS One

Vibration Spectrum Imaging: A Novel Bearing Fault Classification Approach

(2015) Muhammad Amar et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

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

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

Reliable Fault Diagnosis of Multiple Induction Motor Defects Using a 2-D Representation of Shannon Wavelets

(2014) Myeongsu Kang et al.   IEEE TRANSACTIONS ON MAGNETICS

Condition-based monitoring system for rolling element bearing using a generic multi-layer perceptron

(2014) Luis F de Almeida et al.   JOURNAL OF VIBRATION AND CONTROL

Convolutional Neural Networks for Speech Recognition

(2014) Ossama Abdel-Hamid et al.   IEEE-ACM Transactions on Audio Speech and Language Processing

Bearing Fault Detection by a Novel Condition-Monitoring Scheme Based on Statistical-Time Features and Neural Networks

(2012) Miguel Delgado Prieto et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Fault diagnosis and prognosis using wavelet packet decomposition, Fourier transform and artificial neural network

(2012) Zhenyou Zhang et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Outer race defect width measurement in taper roller bearing using discrete wavelet transform of vibration signal

(2012) Rajesh Kumar et al.   MEASUREMENT

A review on empirical mode decomposition in fault diagnosis of rotating machinery

(2012) Yaguo Lei et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Vibration analysis of rotating machinery using time–frequency analysis and wavelet techniques

(2011) F. Al-Badour et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Signal Model-Based Fault Detection and Diagnosis for Induction Motors Using Features of Vibration Signal in Two-Dimension Domain

(2011) Van Tuan Do et al.   STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING

Fault diagnosis of ball bearings using continuous wavelet transform

(2010) P.K. Kankar et al.   APPLIED SOFT COMPUTING

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