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。Effective Fault Diagnosis Based on Wavelet and Convolutional Attention Neural Network for Induction Motors
Minh-Quang Tran et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2022)
SDA: Regularization with Cut-Flip and Mix-Normal for machinery fault diagnosis under small dataset
Haixin Lv et al.
ISA TRANSACTIONS (2021)
A General Transfer Framework Based on Industrial Process Fault Diagnosis Under Small Samples
Jinhai Liu et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)
SASLN: Signals Augmented Self-Taught Learning Networks for Mechanical Fault Diagnosis Under Small Sample Condition
Tianci Zhang et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2021)
A Novel Bearing Fault Classification Method Based on XGBoost: The Fusion of Deep Learning-Based Features and Empirical Features
Jingsong Xie et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2021)
A novel bearing intelligent fault diagnosis framework under time-varying working conditions using recurrent neural network
Zenghui An et al.
ISA TRANSACTIONS (2020)
Gearbox Fault Diagnosis Using a Deep Learning Model With Limited Data Sample
Syahril Ramadhan Saufi et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)
A Novel Health Indicator Based on Information Theory Features for Assessing Rotating Machinery Performance Degradation
Akhand Rai et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)
Multisensor data fusion for gearbox fault diagnosis using 2-D convolutional neural network and motor current signature analysis
Moslem Azamfar et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2020)
Fault Detection and Diagnosis Using Combined Autoencoder and Long Short-Term Memory Network
Pangun Park et al.
SENSORS (2019)
Limited Data Rolling Bearing Fault Diagnosis With Few-Shot Learning
Ansi Zhang et al.
IEEE ACCESS (2019)
A Deep Transfer Nonnegativity-Constraint Sparse Autoencoder for Rolling Bearing Fault Diagnosis With Few Labeled Data
Xingqiu Li et al.
IEEE ACCESS (2019)
A New Approach for Fault Classification in Microgrids Using Optimal Wavelet Functions Matching Pursuit
Tamer S. Abdelgayed et al.
IEEE TRANSACTIONS ON SMART GRID (2018)
Wireless Network Design for Control Systems: A Survey
Pangun Park et al.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2018)
Artificial intelligence for fault diagnosis of rotating machinery: A review
Ruonan Liu et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
A review on the application of deep learning in system health management
Samir Khan et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load
Wei Zhang et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
A review on data-driven fault severity assessment in rolling bearings
Mariela Cerrada et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data
Osama Abdeljaber et al.
NEUROCOMPUTING (2018)
Preprocessing-Free Gear Fault Diagnosis Using Small Datasets With Deep Convolutional Neural Network-Based Transfer Learning
Pei Cao et al.
IEEE ACCESS (2018)
Wavelet Speech Enhancement Based on Nonnegative Matrix Factorization
Syu-Siang Wang et al.
IEEE SIGNAL PROCESSING LETTERS (2016)
Convolutional Neural Network Based Fault Detection for Rotating Machinery
Olivier Janssens et al.
JOURNAL OF SOUND AND VIBRATION (2016)
Wavelet transform based on inner product in fault diagnosis of rotating machinery: A review
Jinglong Chen et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2016)
From sample similarity to ensemble similarity: Probabilistic distance measures in reproducing kernel Hilbert space
SK Zhou et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2006)
分享论文
