An intelligent fault diagnosis method for rotating machinery based on data fusion and deep residual neural network

Understanding and Improving Deep Learning-Based Rolling Bearing Fault Diagnosis with Attention Mechanism

(2019) Xiang Li et al.   SIGNAL PROCESSING

Optimal data fusion based on information quality function

(2019) Shuang Liang et al.   APPLIED INTELLIGENCE

A Novel Deep Learning Method for Intelligent Fault Diagnosis of Rotating Machinery Based on Improved CNN-SVM and Multichannel Data Fusion

(2019) Gong et al.   SENSORS

A minimum entropy deconvolution-enhanced convolutional neural networks for fault diagnosis of axial piston pumps

(2019) Shuhui Wang et al.   SOFT COMPUTING

Using deep learning to preserve data confidentiality

(2019) Wei Li et al.   APPLIED INTELLIGENCE

Machine Health Monitoring Using Local Feature-Based Gated Recurrent Unit Networks

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

A Survey on Network Embedding

(2018) Peng Cui et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Convolutional neural network-based hidden Markov models for rolling element bearing fault identification

(2018) Shuhui Wang et al.   KNOWLEDGE-BASED SYSTEMS

Artificial intelligence for fault diagnosis of rotating machinery: A review

(2018) Ruonan Liu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

An automatic and robust features learning method for rotating machinery fault diagnosis based on contractive autoencoder

(2018) Changqing Shen et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Highly-Accurate Machine Fault Diagnosis Using Deep Transfer Learning

(2018) Siyu Shao et al.   IEEE Transactions on Industrial Informatics

A Multimodal Feature Fusion-Based Deep Learning Method for Online Fault Diagnosis of Rotating Machinery

(2018) Funa Zhou et al.   SENSORS

Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0

(2018) Alberto Diez-Olivan et al.   Information Fusion

Deep Model Based Domain Adaptation for Fault Diagnosis

(2017) Weining Lu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

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

(2017) Luyang Jing et al.   MEASUREMENT

Intelligent Manufacturing in the Context of Industry 4.0: A Review

(2017) Ray Y. Zhong et al.   Engineering

An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data

(2016) Yaguo Lei et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

A novel bearing fault diagnosis model integrated permutation entropy, ensemble empirical mode decomposition and optimized SVM

(2015) Xiaoyuan Zhang et al.   MEASUREMENT

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 learning

(2015) Yann LeCun et al.   NATURE

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

Fault Diagnosis of Rotating Machinery Based on Multisensor Information Fusion Using SVM and Time-Domain Features

(2014) Ling-li Jiang et al.   SHOCK AND VIBRATION