Fault Diagnosis of Rolling Bearings of Different Working Conditions Based on Multi-Feature Spatial Domain Adaptation

Fault Diagnosis of Rolling Bearings of Different Working Conditions Based on Multi-Feature Spatial Domain Adaptation

The running state of rolling bearings is complex in operation, and the data are generally collected under different working conditions. However, when single-source domain adaptation is used to model the heterogeneously distributed data obtained under different working conditions, the domain-invarian...

Full description

Bibliographic Details
Main Authors:	Tao Wen, Renxiang Chen, Linlin Tang
Format:	Article
Language:	English
Published:	IEEE 2021-01-01
Series:	IEEE Access
Subjects:	Rolling bearing different working conditions multi-feature spatial domain adaptation fault diagnosis
Online Access:	https://ieeexplore.ieee.org/document/9389770/

Similar Items

A Cross Working Condition Multiscale Recursive Feature Fusion Method for Fault Diagnosis of Rolling Bearing in Multiple Working Conditions
by: Zhiqiang Zhang, et al.
Published: (2022-01-01)

Application of Time Domain Index and Kurtosis analysis Method in the Fault Diagnosis of Rolling Bearing
by: Guo Qingfeng, et al.
Published: (2016-01-01)

A Domain-Adversarial Multi-Graph Convolutional Network for Unsupervised Domain Adaptation Rolling Bearing Fault Diagnosis
by: Xinran Li, et al.
Published: (2022-12-01)

Semi-Supervised Adversarial Transfer Networks for Cross-Domain Intelligent Fault Diagnosis of Rolling Bearings
by: Baisong Pan, et al.
Published: (2023-02-01)

Deep Transfer Network with Multi-Space Dynamic Distribution Adaptation for Bearing Fault Diagnosis
by: Xiaorong Zheng, et al.
Published: (2022-08-01)

Rolling-Bearing Fault-Diagnosis Method Based on Multimeasurement Hybrid-Feature Evaluation
by: Jianghua Ge, et al.
Published: (2019-11-01)

Lightweight Convolutional Neural Network and Its Application in Rolling Bearing Fault Diagnosis under Variable Working Conditions
by: Hengchang Liu, et al.
Published: (2019-11-01)

Fault Diagnosis of Rolling Bearing based on MEEMD-DHENN
by: Wang Jinrui, et al.
Published: (2018-01-01)

A Novel Rolling Bearing Fault Diagnosis Method Based on Adaptive Feature Selection and Clustering
by: Jingbao Hou, et al.
Published: (2021-01-01)

Exploring the essence of compound fault diagnosis: A novel multi-label domain adaptation method and its application to bearings
by: Liuxing Chu, et al.
Published: (2023-03-01)

Fault Diagnosis of Rolling Element Bearing based on Angular Domain Empirical Wavelet Transform
by: Yang Changzheng
Published: (2017-01-01)

The Method of Rolling Bearing Fault Diagnosis Based on Multi-Domain Supervised Learning of Convolution Neural Network
by: Xuejun Liu, et al.
Published: (2022-06-01)

Multi-Representation Domain Adaptation Network with Duplex Adversarial Learning for Hot-Rolling Mill Fault Diagnosis
by: Rongrong Peng, et al.
Published: (2022-12-01)

AN INCIPIENT FAULT DIAGNOSIS METHOD FOR ROLLING BEARING BASED ON MCKD AND LMD
by: SUN Wei, et al.
Published: (2018-01-01)

Rolling Bearing Fault Diagnosis Based on WGWOA-VMD-SVM
by: Junbo Zhou, et al.
Published: (2022-08-01)

A Fault Diagnosis Solution of Rolling Bearing Based on MEEMD and QPSO-LSSVM
by: Fuzheng Liu, et al.
Published: (2020-01-01)

Pre-Processing Method to Improve Cross-Domain Fault Diagnosis for Bearing
by: Taeyun Kim, et al.
Published: (2021-07-01)

Fault Diagnosis of Bearings With the Common-Domain Data
by: Taeyun Kim, et al.
Published: (2022-01-01)

Rolling Bearings Fault Diagnosis Method Integrating CEEMDAN-SVD and Cepstrum
by: Jinni ZHENG, et al.
Published: (2021-05-01)

Rolling Bearing Fault Diagnosis Based on Time-Frequency Feature Extraction and IBA-SVM
by: Mei Zhang, et al.
Published: (2022-01-01)

An Improved Feature Extraction Method for Rolling Bearing Fault Diagnosis Based on MEMD and PE
by: Zhang Hu, et al.
Published: (2018-08-01)

Rolling Bearing Incipient Fault Diagnosis Method Based on Improved Transfer Learning with Hybrid Feature Extraction
by: Zhengni Yang, et al.
Published: (2021-11-01)

Advancing Early Fault Diagnosis for Multi-Domain Agricultural Machinery Rolling Bearings through Data Enhancement
by: Fengyun Xie, et al.
Published: (2024-01-01)

Extracting spatially global and local attentive features for rolling bearing fault diagnosis in electrical machines using attention stream networks
by: Yannis L. Karnavas, et al.
Published: (2021-07-01)

An Early Fault Diagnosis Method of Rolling Bearings on the Basis of Adaptive Frequency Window and Sparse Coding Shrinkage
by: Shuting Wan, et al.
Published: (2019-06-01)

Rolling Bearing Diagnosis Based on Composite Multiscale Weighted Permutation Entropy
by: Xiong Gan, et al.
Published: (2018-10-01)

Fault Diagnosis Method for Rolling Bearings Based on Composite Multiscale Fluctuation Dispersion Entropy
by: Xiong Gan, et al.
Published: (2019-03-01)

A Survey on Fault Diagnosis of Rolling Bearings
by: Bo Peng, et al.
Published: (2022-09-01)

An Adaptive Generalized Demodulation Method for Multimedia Spectrum Analysis is Applied in Rolling Bearing Fault Diagnosis
by: Zengqiang Ma, et al.
Published: (2020-01-01)

Fault Diagnosis of Rolling Bearing Based on a Priority Elimination Method
by: Chuan Xiang, et al.
Published: (2023-02-01)

ROLLING BEARING FAULT DIAGNOSIS BASED ON FUSION CNN AND PSO-SVM
by: WANG YongDing, et al.
Published: (2021-01-01)

Rolling Element Bearing Fault Diagnosis Using Improved Manifold Learning
by: Beibei Yao, et al.
Published: (2017-01-01)

The Partial Reconstruction Symplectic Geometry Mode Decomposition and Its Application in Rolling Bearing Fault Diagnosis
by: Yanfei Liu, et al.
Published: (2023-08-01)

A Transfer Learning Framework with a One-Dimensional Deep Subdomain Adaptation Network for Bearing Fault Diagnosis under Different Working Conditions
by: Ruixin Zhang, et al.
Published: (2022-02-01)

Intelligent Fault Diagnosis of Rolling Bearings Based on a Complete Frequency Range Feature Extraction and Combined Feature Selection Methodology
by: Zhengkun Xue, et al.
Published: (2023-10-01)

FAULT DIAGNOSIS METHOD OF ROLLING BEARINGS BASED ON ELMD AND KERNEL DENSITY ESTIMATION
by: WU HaiYan, et al.
Published: (2017-01-01)

Rolling Bearing Fault Diagnosis across Operating Conditions Based on Unsupervised Domain Adaptation
by: Zhidan Zhong, et al.
Published: (2023-09-01)

Fault Diagnosis of Rolling Bearings based on VMD and Symmetric Difference Energy Operator Demodulation
by: Qin Bo, et al.
Published: (2017-01-01)

Rolling bearing fault diagnosis based on fine-grained multi-scale Kolmogorov entropy and WOA-MSVM
by: Bing wang, et al.
Published: (2024-03-01)

A New Fault Diagnosis of Rolling Bearing Based on Markov Transition Field and CNN
by: Mengjiao Wang, et al.
Published: (2022-05-01)