4.7 Article

Adversarial Multiple-Target Domain Adaptation for Fault Classification

Related references

Note: Only part of the references are listed.
Article Automation & Control Systems

Distribution-Invariant Deep Belief Network for Intelligent Fault Diagnosis of Machines Under New Working Conditions

Saibo Xing et al.

Summary: DIDBN is a deep learning model that directly learns distribution-invariant features from raw vibration data, achieving higher diagnosis accuracies in fault recognition. By utilizing a locally connected RBM and MDM-RBM layer, DIDBN is able to capture features with close distributions under varying working conditions.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2021)

Article Automation & Control Systems

Intelligent Fault Diagnosis for Rotary Machinery Using Transferable Convolutional Neural Network

Zhuyun Chen et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)

Article Engineering, Electrical & Electronic

A New Two-Level Hierarchical Diagnosis Network Based on Convolutional Neural Network

Long Wen et al.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)

Article Engineering, Electrical & Electronic

Online Fault Diagnosis Method Based on Transfer Convolutional Neural Networks

Gaowei Xu et al.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)

Article Engineering, Electrical & Electronic

A New Intelligent Bearing Fault Diagnosis Method Using SDP Representation and SE-CNN

Hui Wang et al.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)

Article Engineering, Electrical & Electronic

Knowledge Transfer for Rotary Machine Fault Diagnosis

Ruqiang Yan et al.

IEEE SENSORS JOURNAL (2020)

Article Automation & Control Systems

Deep Learning-Based Machinery Fault Diagnostics With Domain Adaptation Across Sensors at Different Places

Xiang Li et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)

Article Engineering, Electrical & Electronic

Fault Diagnosis of Rotary Machine Bearings Under Inconsistent Working Conditions

Muhammad Sohaib et al.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)

Article Engineering, Electrical & Electronic

Intelligent Fault Diagnosis via Semisupervised Generative Adversarial Nets and Wavelet Transform

Pengfei Liang et al.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)

Article Automation & Control Systems

Retraining Strategy-Based Domain Adaption Network for Intelligent Fault Diagnosis

Yan Song et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)

Article Automation & Control Systems

Cross-Domain Fault Diagnosis of Rolling Element Bearings Using Deep Generative Neural Networks

Xiang Li et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2019)

Article Automation & Control Systems

Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning

Siyu Shao et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2019)

Article Computer Science, Artificial Intelligence

A convolutional neural network based on a capsule network with strong generalization for bearing fault diagnosis

Zhiyu Zhu et al.

NEUROCOMPUTING (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 Automation & Control Systems

A Hierarchical Deep Domain Adaptation Approach for Fault Diagnosis of Power Plant Thermal System

Xiaoxia Wang et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2019)

Article Engineering, Mechanical

Deep learning and its applications to machine health monitoring

Rui Zhao et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2019)

Article Engineering, Electrical & Electronic

Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning

Jiedi Sun et al.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2018)

Article Computer Science, Artificial Intelligence

ACDIN: Bridging the gap between artificial and real bearing damages for bearing fault diagnosis

Yuanhang Chen et al.

NEUROCOMPUTING (2018)

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, Artificial Intelligence

On Better Exploring and Exploiting Task Relationships in Multitask Learning: Joint Model and Feature Learning

Ya Li et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2018)

Proceedings Paper Computer Science, Artificial Intelligence

ComboGAN: Unrestrained Scalability for Image Domain Translation

Asha Anoosheh et al.

PROCEEDINGS 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW) (2018)

Article Automation & Control Systems

Deep Model Based Domain Adaptation for Fault Diagnosis

Weining Lu et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2017)

Article Engineering, Mechanical

Intelligent Fault Diagnosis of Rotary Machinery Based on Unsupervised Multiscale Representation Learning

Guo-Qian Jiang et al.

CHINESE JOURNAL OF MECHANICAL ENGINEERING (2017)

Article Automation & Control Systems

Heterogeneous Feature Models and Feature Selection Applied to Bearing Fault Diagnosis

Thomas W. Rauber et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2015)

Review Engineering, Mechanical

Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study

Wade A. Smith et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2015)

Article Computer Science, Artificial Intelligence

Domain Adaptation via Transfer Component Analysis

Sinno Jialin Pan et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS (2011)

Article Computer Science, Artificial Intelligence

A Survey on Transfer Learning

Sinno Jialin Pan et al.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2010)