相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning
Xiang Li et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)
Intelligent Fault Diagnosis for Rotary Machinery Using Transferable Convolutional Neural Network
Zhuyun Chen et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)
Online Fault Diagnosis Method Based on Transfer Convolutional Neural Networks
Gaowei Xu et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)
Open Set Domain Adaptation for Image and Action Recognition
Pau Panareda Busto et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2020)
Machinery fault diagnosis with imbalanced data using deep generative adversarial networks
Wei Zhang et al.
MEASUREMENT (2020)
A Combined Polynomial Chirplet Transform and Synchroextracting Technique for Analyzing Nonstationary Signals of Rotating Machinery
Kun Yu et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)
Knowledge Transfer for Rotary Machine Fault Diagnosis
Ruqiang Yan et al.
IEEE SENSORS JOURNAL (2020)
Deep Learning-Based Machinery Fault Diagnostics With Domain Adaptation Across Sensors at Different Places
Xiang Li et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)
A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis
Long Wen et al.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2019)
The Optimized Deep Belief Networks With Improved Logistic Sigmoid Units and Their Application in Fault Diagnosis for Planetary Gearboxes of Wind Turbines
Yi Qin et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2019)
A Semi-Supervised Diagnostic Framework Based on the Surface Estimation of Faulty Distributions
Roozbeh Razavi-Far et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2019)
Cross-Domain Fault Diagnosis of Rolling Element Bearings Using Deep Generative Neural Networks
Xiang Li et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2019)
Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning
Siyu Shao et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2019)
Learning transferable features in deep convolutional neural networks for diagnosing unseen machine conditions
Te Han et al.
ISA TRANSACTIONS (2019)
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)
Supervised dictionary-based transfer subspace learning and applications for fault diagnosis of sucker rod pumping systems
Ao Zhang et al.
NEUROCOMPUTING (2019)
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)
A Hierarchical Deep Domain Adaptation Approach for Fault Diagnosis of Power Plant Thermal System
Xiaoxia Wang et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2019)
Research on vibration performance of the nonlinear combined support-flexible rotor system
Zhong Luo et al.
NONLINEAR DYNAMICS (2019)
Deep residual learning-based fault diagnosis method for rotating machinery
Wei Zhang et al.
ISA TRANSACTIONS (2019)
Cross-Domain Fault Diagnosis Using Knowledge Transfer Strategy: A Review
Huailiang Zheng et al.
IEEE ACCESS (2019)
Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization
Feng Jia et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
A robust intelligent fault diagnosis method for rolling element bearings based on deep distance metric learning
Xiang Li et al.
NEUROCOMPUTING (2018)
Deep Model Based Domain Adaptation for Fault Diagnosis
Weining Lu et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2017)
Convolutional Discriminative Feature Learning for Induction Motor Fault Diagnosis
Wenjun Sun et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2017)
Deep Learning Based Approach for Bearing Fault Diagnosis
Miao He et al.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS (2017)
Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification
Chen Lu et al.
SIGNAL PROCESSING (2017)
Review on dynamics of cracked gear systems
Hui Ma et al.
ENGINEERING FAILURE ANALYSIS (2015)
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)
Motor Bearing Fault Diagnosis Using Trace Ratio Linear Discriminant Analysis
Xiaohang Jin et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2014)
分享论文
