An ensemble and shared selective adversarial network for partial domain fault diagnosis of machinery

Joint pairwise graph embedded sparse deep belief network for fault diagnosis

(2021) Jie Yang et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

A double-layer attention based adversarial network for partial transfer learning in machinery fault diagnosis

(2021) Yafei Deng et al.   COMPUTERS IN INDUSTRY

Multiscale domain adaption models and their application in fault transfer diagnosis of planetary gearboxes

(2021) Qunwang Yao et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Tacho-less sparse CNN to detect defects in rotor-bearing systems at varying speed

(2021) Anil Kumar et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Bearing fault diagnosis with intermediate domain based Layered Maximum Mean Discrepancy: A new transfer learning approach

(2021) Sebastian Schwendemann et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

A personalized diagnosis method to detect faults in gears using numerical simulation and extreme learning machine

(2020) Xiaoyang Liu et al.   KNOWLEDGE-BASED SYSTEMS

A Personalized Diagnosis Method to Detect Faults in a Bearing Based on Acceleration Sensors and an FEM Simulation Driving Support Vector Machine

(2020) Xiaoyang Liu et al.   SENSORS

Long short-term memory neural network with weight amplification and its application into gear remaining useful life prediction

(2020) Sheng Xiang et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Partial transfer learning in machinery cross-domain fault diagnostics using class-weighted adversarial networks

(2020) Xiang Li et al.   NEURAL NETWORKS

A Novel Weighted Adversarial Transfer Network for Partial Domain Fault Diagnosis of Machinery

(2020) Weihua Li et al.   IEEE Transactions on Industrial Informatics

A Review of Single-Source Deep Unsupervised Visual Domain Adaptation

(2020) Sicheng Zhao et al.   IEEE Transactions on Neural Networks and Learning Systems

Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning

(2019) Xiang Li et al.   IEEE Transactions on Industrial Informatics

Knowledge Transfer for Rotary Machine Fault Diagnosis

(2019) Ruqiang Yan et al.   IEEE SENSORS JOURNAL

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

(2019) Xiang Li et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

A Review of Domain Adaptation without Target Labels

(2019) Wouter M. Kouw et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

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

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

Transfer learning with partial related “instance-feature” knowledge

(2018) Yunyun Wang et al.   NEUROCOMPUTING

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

(2018) Xiang Li et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Highly-Accurate Machine Fault Diagnosis Using Deep Transfer Learning

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

A novel adversarial learning framework in deep convolutional neural network for intelligent diagnosis of mechanical faults

(2018) Te Han et al.   KNOWLEDGE-BASED SYSTEMS

Multi-Layer domain adaptation method for rolling bearing fault diagnosis

(2018) Xiang Li et al.   SIGNAL PROCESSING

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

(2018) Liang Guo et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Deep Model Based Domain Adaptation for Fault Diagnosis

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

An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines

(2016) M. Amozegar et al.   NEURAL NETWORKS

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING