An efficient method for imbalanced fault diagnosis of rotating machinery

Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions

(2021) Tianci Zhang et al.   ISA TRANSACTIONS

A case study of conditional deep convolutional generative adversarial networks in machine fault diagnosis

(2020) Jia Luo et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Applications of machine learning to machine fault diagnosis: A review and roadmap

(2020) Yaguo Lei et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Imbalanced sample fault diagnosis of rotating machinery using conditional variational auto-encoder generative adversarial network

(2020) You-ren Wang et al.   APPLIED SOFT COMPUTING

Data synthesis using dual discriminator conditional generative adversarial networks for imbalanced fault diagnosis of rolling bearings

(2020) Taisheng Zheng et al.   MEASUREMENT

A Fault Diagnosis Method of Rotating Machinery Based on One-Dimensional, Self-Normalizing Convolutional Neural Networks

(2020) Jingli Yang et al.   SENSORS

Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study

(2020) Zhibin Zhao et al.   ISA TRANSACTIONS

Improved generative adversarial network for vibration-based fault diagnosis with imbalanced data

(2020) Bingxi Zhao et al.   MEASUREMENT

Generative adversarial networks for data augmentation in machine fault diagnosis

(2019) Siyu Shao et al.   COMPUTERS IN INDUSTRY

Data augmentation in fault diagnosis based on the Wasserstein generative adversarial network with gradient penalty

(2019) Xin Gao et al.   NEUROCOMPUTING

Deep learning fault diagnosis method based on global optimization GAN for unbalanced data

(2019) Funa Zhou et al.   KNOWLEDGE-BASED SYSTEMS

A Novel Rolling Bearing Fault Diagnosis and Severity Analysis Method

(2019) Yinsheng Chen et al.   Applied Sciences-Basel

Deep learning enabled intelligent fault diagnosis: Overview and applications

(2018) Lixiang Duan et al.   JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

Multi-level wavelet packet fusion in dynamic ensemble convolutional neural network for fault diagnosis

(2018) Yan Han et al.   MEASUREMENT

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

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

An intelligent diagnosis scheme based on generative adversarial learning deep neural networks and its application to planetary gearbox fault pattern recognition

(2018) Zirui Wang et al.   NEUROCOMPUTING

An enhancement denoising autoencoder for rolling bearing fault diagnosis

(2018) Zong Meng 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

On the Characterization of Local Nash Equilibria in Continuous Games

(2016) Lillian J. Ratliff et al.   IEEE TRANSACTIONS ON AUTOMATIC CONTROL

Construction of hierarchical diagnosis network based on deep learning and its application in the fault pattern recognition of rolling element bearings

(2016) Meng Gan 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