Research on the Initial Fault Prediction Method of Rolling Bearings Based on DCAE-TCN Transfer Learning

Research on the Initial Fault Prediction Method of Rolling Bearings Based on DCAE-TCN Transfer Learning

In actual working conditions, the initial faults of rolling bearings are difficult to effectively predict due to the lack of evolution knowledge, weak fault information, and strong noise interference. In this paper, a rolling bearing initial fault prediction model that is based on transfer learning...

Full description

Saved in:

Bibliographic Details
Main Authors:	Huaitao Shi, Yajun Shang, Xiaochen Zhang, Yinghan Tang
Format:	Article
Language:	English
Published:	Wiley 2021-01-01
Series:	Shock and Vibration
Online Access:	http://dx.doi.org/10.1155/2021/5587756
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Rolling Bearing Fault Diagnosis Method Based on MCMF and SAIMFE
by: Dejun Meng, et al.
Published: (2022-01-01)

Application of RSSD-OCYCBD Strategy in Enhanced Fault Detection of Rolling Bearing
by: Xiaolong Wang, et al.
Published: (2020-01-01)

Vibration Images-Driven Fault Diagnosis Based on CNN and Transfer Learning of Rolling Bearing under Strong Noise
by: Hongwei Fan, et al.
Published: (2021-01-01)

The Fault Diagnosis of Rolling Bearing Based on Improved Deep Forest
by: Xiwen Qin, et al.
Published: (2021-01-01)

Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis
by: Jinde Zheng, et al.
Published: (2014-01-01)

The Hybrid KICA-GDA-LSSVM Method Research on Rolling Bearing Fault Feature Extraction and Classification
by: Jiyong Li, et al.
Published: (2015-01-01)

Research on Fault Feature Extraction Method of Rolling Bearing Based on NMD and Wavelet Threshold Denoising
by: Maohua Xiao, et al.
Published: (2018-01-01)

Rolling Bearing Fault Diagnosis Based on a Synchrosqueezing Wavelet Transform and a Transfer Residual Convolutional Neural Network
by: Zihao Zhai, et al.
Published: (2025-01-01)

Intelligent fault diagnosis method for rolling bearings based on flexible residual neural network
by: Chuang CHEN, et al.
Published: (2025-03-01)

A study on rolling bearing fault diagnosis using RIME-VMD
by: Zhenrong Ma, et al.
Published: (2025-02-01)

Rolling Bearing Fault Diagnosis Based on ELCD Permutation Entropy and RVM
by: Jiang Xingmeng, et al.
Published: (2016-01-01)

An Improved Method of EWT and Its Application in Rolling Bearings Fault Diagnosis
by: Zhicheng Qiao, et al.
Published: (2020-01-01)

Multitask Convolutional Neural Network for Rolling Element Bearing Fault Identification
by: Mingxing Jia, et al.
Published: (2020-01-01)

Normalization-Guided and Gradient-Weighted Unsupervised Domain Adaptation Network for Transfer Diagnosis of Rolling Bearing Faults Under Class Imbalance
by: Hao Luo, et al.
Published: (2025-01-01)

Peak-Based Mode Decomposition for Weak Fault Feature Enhancement and Detection of Rolling Element Bearing
by: Zhi Xu, et al.
Published: (2020-01-01)

The Crack Propagation Trend Analysis in Ceramic Rolling Element Bearing considering Initial Crack Angle and Contact Load Effect
by: Zhe Yuan, et al.
Published: (2021-01-01)

Rolling Bearing Fault Diagnosis Based on Sensitive Feature Transfer Learning and Local Maximum Margin Criterion under Variable Working Condition
by: Shiyuan Liu, et al.
Published: (2020-01-01)

Rolling Element Bearing Fault Diagnosis Based on Multiscale General Fractal Features
by: Weigang Wen, et al.
Published: (2015-01-01)

Fault Diagnosis for Rolling Bearing under Variable Conditions Based on Image Recognition
by: Bo Zhou, et al.
Published: (2016-01-01)

Improved VMD‐KFCM algorithm for the fault diagnosis of rolling bearing vibration signals
by: Yong Chang, et al.
Published: (2021-06-01)

Rolling Bearing Fault Diagnosis Based on STFT-Deep Learning and Sound Signals
by: Hongmei Liu, et al.
Published: (2016-01-01)

Fault diagnosis of mining rolling bearings based on Superlet Transform and OD-ConvNeXt-ELA
by: WU Xinzhong, et al.
Published: (2024-12-01)

Research on the Feature Selection of Rolling Bearings’ Degradation Features
by: Yaolong Li, et al.
Published: (2019-01-01)

Research on Mechanical Aging Behavior of Grease in Rolling Bearing
by: Jialong Yang, et al.
Published: (2025-01-01)

MCRCNet: A Bearing Fault Diagnosis Method for Unknown Faults Based on Transfer Learning
by: Guangyuan Xu, et al.
Published: (2025-01-01)

Rolling Bearing Fault Diagnosis Method Based on Multisynchrosqueezing S Transform and Faster Dictionary Learning
by: Guodong Sun, et al.
Published: (2021-01-01)

Fault Frequency Identification of Rolling Bearing Using Reinforced Ensemble Local Mean Decomposition
by: Bo Qin, et al.
Published: (2021-01-01)

Mutual Information-Assisted Wavelet Function Selection for Enhanced Rolling Bearing Fault Diagnosis
by: Ruqiang Yan, et al.
Published: (2015-01-01)

Fault Diagnosis Method for Rolling Bearing Based on Sparse Principal Subspace Discriminant Analysis
by: Hongdi Zhou, et al.
Published: (2022-01-01)

Rolling Element Bearing Fault Recognition Approach Based on Fuzzy Clustering Bispectrum Estimation
by: W.Y. Liu, et al.
Published: (2013-01-01)

The Fault Feature Extraction of Rolling Bearing Based on EMD and Difference Spectrum of Singular Value
by: Te Han, et al.
Published: (2016-01-01)

Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE Algorithm
by: Yuanyuan Li, et al.
Published: (2022-01-01)

Multistage Fault Feature Extraction of Consistent Optimization for Rolling Bearings Based on Correlated Kurtosis
by: Long Zhang, et al.
Published: (2020-01-01)

A Novel Approach of Impulsive Signal Extraction for Early Fault Detection of Rolling Element Bearing
by: Hu Aijun, et al.
Published: (2017-01-01)

Rolling Bearing Fault Diagnostic Method Based on VMD-AR Model and Random Forest Classifier
by: Te Han, et al.
Published: (2016-01-01)

Intelligent Diagnosis of Rolling Bearing Fault Based on Improved Convolutional Neural Network and LightGBM
by: Yanwei Xu, et al.
Published: (2021-01-01)

Rolling-Element Bearing Fault Data Automatic Clustering Based on Wavelet and Deep Neural Network
by: Yanli Yang, et al.
Published: (2018-01-01)

A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse Representation
by: Xing Yuan, et al.
Published: (2022-01-01)

Rolling bearing fault diagnosis based on parameter optimized VMD and improved GoogLeNet
by: LI Haoran, et al.
Published: (2025-01-01)

Research on TCN Model Based on SSARF Feature Selection in the Field of Human Behavior Recognition
by: Wei Zhang, et al.
Published: (2024-01-01)