Residual deep subdomain adaptation network: A new method for intelligent fault diagnosis of bearings across multiple domains
Authors:
- Zuoyi ChenZCZuoyi Chen
- Jun WuJWJun Wu
- Chao DengCDChao Deng
- Chao WangCWChao Wang
- Yuanhang WangYWYuanhang Wang
- 1 March 2022
- journal article
- research article
- Published by Elsevier in Mechanism and Machine Theory
- Vol. 169
Abstract
No abstract availableKeywords
This publication has 20 references indexed in Scilit:
- Deep Learning-Based Machinery Fault Diagnostics With Domain Adaptation Across Sensors at Different PlacesIEEE Transactions on Industrial Electronics, 2019
- An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearingsMechanical Systems and Signal Processing, 2019
- Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled DataIEEE Transactions on Industrial Electronics, 2018
- Cross-Domain Fault Diagnosis of Rolling Element Bearings Using Deep Generative Neural NetworksIEEE Transactions on Industrial Electronics, 2018
- Machine Health Monitoring Using Adaptive Kernel Spectral Clustering and Deep Long Short-Term Memory Recurrent Neural NetworksIEEE Transactions on Industrial Informatics, 2018
- A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault DiagnosisIEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017
- A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing ProcessesIEEE Transactions on Semiconductor Manufacturing, 2017
- A novel intelligent method for bearing fault diagnosis based on affinity propagation clustering and adaptive feature selectionKnowledge-Based Systems, 2017
- An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big DataIEEE Transactions on Industrial Electronics, 2016
- Domain Adaptation via Transfer Component AnalysisIEEE Transactions on Neural Networks, 2010