Data privacy preserving federated transfer learning in machinery fault diagnostics using prior distributions

Transfer learning using deep representation regularization in remaining useful life prediction across operating conditions

(2021) Wei Zhang et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

A novel unsupervised deep learning network for intelligent fault diagnosis of rotating machinery

(2020) Xiaoli Zhao et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

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

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

Bearing fault diagnosis based on teager energy entropy and mean-shift fuzzy C-means

(2020) Shuting Wan et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Data alignments in machinery remaining useful life prediction using deep adversarial neural networks

(2020) Xiang Li et al.   KNOWLEDGE-BASED SYSTEMS

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

(2020) Xiang Li et al.   NEURAL NETWORKS

Federated learning for machinery fault diagnosis with dynamic validation and self-supervision

(2020) Wei Zhang et al.   KNOWLEDGE-BASED SYSTEMS

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

(2020) Xiang Li et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Federated Machine Learning

(2019) Qiang Yang et al.   ACM Transactions on Intelligent Systems and Technology

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

(2019) Bin Yang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A bearing fault and severity diagnostic technique using adaptive deep belief networks and Dempster–Shafer theory

(2019) Kun Yu et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Fine-tuned variational mode decomposition for fault diagnosis of rotary machinery

(2019) Ali Dibaj et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Deep Coupled Dense Convolutional Network With Complementary Data for Intelligent Fault Diagnosis

(2019) Jinyang Jiao et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning

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

Intelligent Fault Diagnosis for Rotary Machinery Using Transferable Convolutional Neural Network

(2019) Zhuyun Chen et al.   IEEE Transactions on Industrial Informatics

A Semi-supervised Diagnostic Framework Based on the Surface Estimation of Faulty Distributions

(2018) Roozbeh Razavi-Far et al.   IEEE Transactions on Industrial Informatics

Privacy-Preserving Deep Learning via Additively Homomorphic Encryption

(2018) Le Trieu Phong et al.   IEEE Transactions on Information Forensics and Security

Fault Diagnosis for Rotating Machinery Using Multiple Sensors and Convolutional Neural Networks

(2018) Min Xia et al.   IEEE-ASME TRANSACTIONS ON MECHATRONICS

Fault diagnosis of rolling bearings with recurrent neural network-based autoencoders

(2018) Han Liu et al.   ISA TRANSACTIONS

Surface fatigue crack identification in steel box girder of bridges by a deep fusion convolutional neural network based on consumer-grade camera images

(2018) Yang Xu et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Deep residual learning-based fault diagnosis method for rotating machinery

(2018) Wei Zhang et al.   ISA TRANSACTIONS

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

Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification

(2017) Chen Lu et al.   SIGNAL PROCESSING

An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data

(2016) Yaguo Lei et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Gearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals

(2016) Chuan Li et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

An optimal fault detection threshold for early detection using Kullback–Leibler Divergence for unknown distribution data

(2016) Abdulrahman Youssef et al.   SIGNAL PROCESSING

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

(2015) Wade A. Smith et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING