4.8 Article

Subdomain Adaptation Transfer Learning Network for Fault Diagnosis of Roller Bearings

Related references

Note: Only part of the references are listed.
Article Mathematics, Applied

CONVERGENCE AND DYNAMICAL BEHAVIOR OF THE ADAM ALGORITHM FOR NONCONVEX STOCHASTIC OPTIMIZATION

Anas Barakat et al.

Summary: The paper introduces a continuous-time version and a version with decreasing step size of the Adam algorithm, proving their convergence under different conditions, analyzing their convergence rates, and fluctuations.

SIAM JOURNAL ON OPTIMIZATION (2021)

Article Automation & Control Systems

Deep Learning-Based Partial Domain Adaptation Method on Intelligent Machinery Fault Diagnostics

Xiang Li et al.

Summary: This article proposes a deep learning-based fault diagnosis method to address the partial domain adaptation problems, where the unsupervised target-domain training data do not cover the full machine health state label space. Conditional data alignment and unsupervised prediction consistency schemes are proposed to achieve partial domain adaptation.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2021)

Article Automation & Control Systems

Multiscale Convolutional Attention Network for Predicting Remaining Useful Life of Machinery

Biao Wang et al.

Summary: A new deep prognostics framework named multiscale convolutional attention network (MSCAN) is proposed for predicting the remaining useful life (RUL) of machinery. This framework utilizes self-attention modules and multiscale learning strategy to effectively fuse multisensor data and improve RUL prediction accuracy.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2021)

Article Engineering, Mechanical

Deep partial transfer learning network: A method to selectively transfer diagnostic knowledge across related machines

Bin Yang et al.

Summary: This paper introduces a deep partial transfer learning network (DPTL-Net) that can selectively transfer diagnostic knowledge across asymmetric domains, demonstrating better performance in two case studies.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2021)

Article Engineering, Multidisciplinary

Online detection for bearing incipient fault based on deep transfer learning

Wentao Mao et al.

MEASUREMENT (2020)

Article Computer Science, Artificial Intelligence

Transfer Learning with Dynamic Distribution Adaptation

Jindong Wang et al.

ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY (2020)

Article Engineering, Multidisciplinary

Network-combined broad learning and transfer learning: a new intelligent fault diagnosis method for rolling bearings

Yujing Wang et al.

MEASUREMENT SCIENCE AND TECHNOLOGY (2020)

Article Automation & Control Systems

Broad Convolutional Neural Network Based Industrial Process Fault Diagnosis With Incremental Learning Capability

Wanke Yu et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)

Article Automation & Control Systems

Multitask Convolutional Neural Network With Information Fusion for Bearing Fault Diagnosis and Localization

Sheng Guo et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)

Article Automation & Control Systems

A New Penalty Domain Selection Machine Enabled Transfer Learning for Gearbox Fault Recognition

Fei Shen et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)

Article Automation & Control Systems

SCSCN: A Separated Channel-Spatial Convolution Net With Attention for Single-View Reconstruction

Jiayi Ma et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)

Article Automation & Control Systems

A Novel Dynamic Weight Principal Component Analysis Method and Hierarchical Monitoring Strategy for Process Fault Detection and Diagnosis

Yang Tao et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)

Article Engineering, Multidisciplinary

Few-shot transfer learning for intelligent fault diagnosis of machine

Jingyao Wu et al.

MEASUREMENT (2020)

Article Automation & Control Systems

A Polynomial Kernel Induced Distance Metric to Improve Deep Transfer Learning for Fault Diagnosis of Machines

Bin Yang et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)

Article Engineering, Mechanical

An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings

Bin Yang et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2019)

Article Engineering, Electrical & Electronic

Multi-Layer domain adaptation method for rolling bearing fault diagnosis

Xiang Li et al.

SIGNAL PROCESSING (2019)

Article Automation & Control Systems

Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data

Liang Guo et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2019)

Article Computer Science, Artificial Intelligence

A robust intelligent fault diagnosis method for rolling element bearings based on deep distance metric learning

Xiang Li et al.

NEUROCOMPUTING (2018)

Article Computer Science, Information Systems

Transfer Learning With Neural Networks for Bearing Fault Diagnosis in Changing Working Conditions

Ran Zhang et al.

IEEE ACCESS (2017)