Related references
Note: Only part of the references are listed.Conditional empirical wavelet transform with modified ratio of cyclic content for bearing fault diagnosis
Zhenling Mo et al.
ISA TRANSACTIONS (2023)
Gear Fault Diagnosis Based on Variational Modal Decomposition and Wide plus Narrow Visual Field Neural Networks
Menghui Wang et al.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2022)
Domain Adaptive Remaining Useful Life Prediction With Transformer
Xinyao Li et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2022)
Multiscale Residual Attention Convolutional Neural Network for Bearing Fault Diagnosis
Linshan Jia et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2022)
Weighted Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction
Kangkai Wu et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2022)
Intelligent Rolling Bearing Fault Diagnosis via Vision ConvNet
Yinjun Wang et al.
IEEE SENSORS JOURNAL (2021)
Fault Diagnosis of Rolling Bearings Based on an Improved Stack Autoencoder and Support Vector Machine
Mingliang Cui et al.
IEEE SENSORS JOURNAL (2021)
Deep Residual Networks With Adaptively Parametric Rectifier Linear Units for Fault Diagnosis
Minghang Zhao et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2021)
Cascade Convolutional Neural Network With Progressive Optimization for Motor Fault Diagnosis Under Nonstationary Conditions
Fei Wang et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)
Multiscale Convolutional Neural Network With Feature Alignment for Bearing Fault Diagnosis
Junbin Chen et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2021)
Rolling Bearing Fault Diagnosis Based on One-Dimensional Dilated Convolution Network With Residual Connection
Haopeng Liang et al.
IEEE ACCESS (2021)
Deep Dynamic Adaptive Transfer Network for Rolling Bearing Fault Diagnosis With Considering Cross-Machine Instance
Yuxuan Zhou et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2021)
Novel Adaptive Search Method for Bearing Fault Frequency Using Stochastic Resonance Quantified by Amplitude-Domain Index
Dawen Huang et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)
Optimal IMF selection and unknown fault feature extraction for rolling bearings with different defect modes
Jianhua Yang et al.
MEASUREMENT (2020)
Broad Convolutional Neural Network Based Industrial Process Fault Diagnosis With Incremental Learning Capability
Wanke Yu et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)
Deep Residual Shrinkage Networks for Fault Diagnosis
Minghang Zhao et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)
DCNN-Based Multi-Signal Induction Motor Fault Diagnosis
Siyu Shao et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)
Vibration-based fault diagnosis of the natural gas compressor using adaptive stochastic resonance realized by Generative Adversarial Networks
Dengji Zhou et al.
ENGINEERING FAILURE ANALYSIS (2020)
One-Dimensional Residual Convolutional Autoencoder Based Feature Learning for Gearbox Fault Diagnosis
Jianbo Yu et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)
Gearbox Fault Diagnosis Using a Deep Learning Model With Limited Data Sample
Syahril Ramadhan Saufi et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)
An optimized VMD method and its applications in bearing fault diagnosis
Hua Li et al.
MEASUREMENT (2020)
Multiscale Convolutional Neural Networks for Fault Diagnosis of Wind Turbine Gearbox
Guoqian Jiang et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (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)
Multiple Wavelet Coefficients Fusion in Deep Residual Networks for Fault Diagnosis
Minghang Zhao et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2019)
An improved deep convolutional neural network with multi-scale information for bearing fault diagnosis
Wenyi Huang et al.
NEUROCOMPUTING (2019)
A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method
Long Wen et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2018)
Deep Residual Networks With Dynamically Weighted Wavelet Coefficients for Fault Diagnosis of Planetary Gearboxes
Minghang Zhao et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2018)
A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals
Wei Zhang et al.
SENSORS (2017)