Research on Intelligent Fault Diagnosis of Rolling Bearing Based on Improved Deep Residual Network

Deep Spatiotemporal Convolutional-Neural-Network-Based Remaining Useful Life Estimation of Bearings

(2021) Xu Wang et al.   Chinese Journal of Mechanical Engineering

A Novel Fault Diagnosis Algorithm for Rolling Bearings Based on One-Dimensional Convolutional Neural Network and INPSO-SVM

(2020) Yang Shao et al.   Applied Sciences-Basel

Improved deep convolution neural network (CNN) for the identification of defects in the centrifugal pump using acoustic images

(2020) Anil Kumar et al.   APPLIED ACOUSTICS

A novel method based on nonlinear auto-regression neural network and convolutional neural network for imbalanced fault diagnosis of rotating machinery

(2020) Quan Zhou et al.   MEASUREMENT

Multisensor data fusion for gearbox fault diagnosis using 2-D convolutional neural network and motor current signature analysis

(2020) Moslem Azamfar et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Application of a new one-dimensional deep convolutional neural network for intelligent fault diagnosis of rolling bearings

(2020) Shenglong Xie et al.   SCIENCE PROGRESS

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

(2019) Zilong Zhuang et al.   Applied Sciences-Basel

Multiple wavelet regularized deep residual networks for fault diagnosis

(2019) Minghang Zhao et al.   MEASUREMENT

Deep Residual Networks With Dynamically Weighted Wavelet Coefficients for Fault Diagnosis of Planetary Gearboxes

(2018) Minghang Zhao et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

LiftingNet: A Novel Deep Learning Network With Layerwise Feature Learning From Noisy Mechanical Data for Fault Classification

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

The optimized deep belief networks with improved logistic Sigmoid units and their application in fault diagnosis for planetary gearboxes of wind turbines

(2018) Yi Qin et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Fault Diagnosis for Rotating Machinery Using Multiple Sensors and Convolutional Neural Networks

(2018) Min Xia et al.   IEEE-ASME TRANSACTIONS ON MECHATRONICS

A review on the application of deep learning in system health management

(2018) Samir Khan et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep convolutional neural network for latent fingerprint enhancement

(2018) Jian Li et al.   SIGNAL PROCESSING-IMAGE COMMUNICATION

Intelligent fault detection using raw vibration signals via dilated convolutional neural networks

(2018) Mohammad Azam Khan et al.   JOURNAL OF SUPERCOMPUTING

Deep learning and its applications to machine health monitoring

(2018) Rui Zhao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Aircraft Air Compressor Bearing Diagnosis Using Discriminant Analysis and Cooperative Genetic Algorithm and Neural Network Approaches

(2018) Ahmed Ouadine et al.   Applied Sciences-Basel

Bearing Fault Diagnosis under Variable Speed Using Convolutional Neural Networks and the Stochastic Diagonal Levenberg-Marquardt Algorithm

(2017) Viet Tra et al.   SENSORS

A method for the compound fault diagnosis of gearboxes based on morphological component analysis

(2016) Dejie Yu et al.   MEASUREMENT

Distributed bearing fault diagnosis based on vibration analysis

(2016) Boštjan Dolenc et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

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

Vibration signal analysis of a hydropower unit based on adaptive local iterative filtering

(2016) Xueli An et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE

Reliable Fault Diagnosis for Low-Speed Bearings Using Individually Trained Support Vector Machines With Kernel Discriminative Feature Analysis

(2015) Myeongsu Kang et al.   IEEE TRANSACTIONS ON POWER ELECTRONICS

Reliable fault diagnosis for incipient low-speed bearings using fault feature analysis based on a binary bat algorithm

(2015) Myeongsu Kang et al.   INFORMATION SCIENCES

Fault diagnosis method using supervised extended local tangent space alignment for dimension reduction

(2015) Zuqiang Su et al.   MEASUREMENT

Fault diagnosis of automobile hydraulic brake system using statistical features and support vector machines

(2015) R. Jegadeeshwaran et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A summary of fault modelling and predictive health monitoring of rolling element bearings

(2015) Idriss El-Thalji et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep learning

(2015) Yann LeCun et al.   NATURE

A new wind turbine fault diagnosis method based on ensemble intrinsic time-scale decomposition and WPT-fractal dimension

(2015) Aijun Hu et al.   RENEWABLE ENERGY

Fault diagnosis of rolling bearings using a genetic algorithm optimized neural network

(2014) Muhammet Unal et al.   MEASUREMENT

Fault diagnosis of rolling element bearing with intrinsic mode function of acoustic emission data using APF-KNN

(2013) D.H. Pandya et al.   EXPERT SYSTEMS WITH APPLICATIONS

Support vector machine based decision for mechanical fault condition monitoring in induction motor using an advanced Hilbert-Park transform

(2012) Samira Ben Salem et al.   ISA TRANSACTIONS

Gear fault diagnosis based on Gaussian correlation of vibrations signals and wavelet coefficients

(2011) Amir Hosein Zamanian et al.   APPLIED SOFT COMPUTING