Cargando…

A Bearing Fault Diagnosis Method Based on a Residual Network and a Gated Recurrent Unit under Time-Varying Working Conditions

The diagnosis of bearing faults is an important guarantee for the healthy operation of mechanical equipment. Due to the time-varying working conditions of mechanical equipment, it is necessary to achieve bearing fault diagnosis under time-varying working conditions. However, the superposition of the...

Descripción completa

Detalles Bibliográficos
Autores principales:	Wang, Zheng, Xu, Xiaoyang, Zhang, Yu, Wang, Zhongyao, Li, Yuting, Liu, Zhidong, Zhang, Yuxi
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2023
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422522/ https://www.ncbi.nlm.nih.gov/pubmed/37571514 http://dx.doi.org/10.3390/s23156730

Ejemplares similares

One-Dimensional Multi-Scale Domain Adaptive Network for Bearing-Fault Diagnosis under Varying Working Conditions
por: Wang, Kai, et al.
Publicado: (2020)

Incipient Fault Detection for Rolling Element Bearings under Varying Speed Conditions
por: Xue, Lang, et al.
Publicado: (2017)

A Multiscale Recursive Attention Gate Federation Method for Multiple Working Conditions Fault Diagnosis
por: Zhang, Zhiqiang, et al.
Publicado: (2023)

A Sound and Vibration Fusion Method for Fault Diagnosis of Rolling Bearings under Speed-Varying Conditions
por: Wan, Haibo, et al.
Publicado: (2023)

Color Recurrence Plots for Bearing Fault Diagnosis
por: Petrauskiene, Vilma, et al.
Publicado: (2022)

Fault Diagnosis in the Slip–Frequency Plane of Induction Machines Working in Time-Varying Conditions
por: Puche-Panadero, Ruben, et al.
Publicado: (2020)

Multilocation and Multiscale Learning Framework with Skip Connection for Fault Diagnosis of Bearing under Complex Working Conditions
por: Ban, Hongwei, et al.
Publicado: (2021)

Ball Bearing Fault Diagnosis Using Recurrence Analysis
por: Kecik, Krzysztof, et al.
Publicado: (2022)

Generative Adversarial Learning Enhanced Fault Diagnosis for Planetary Gearbox under Varying Working Conditions
por: Wen, Weigang, et al.
Publicado: (2020)

Rolling Bearing Fault Diagnosis Based on Markov Transition Field and Residual Network
por: Yan, Jialin, et al.
Publicado: (2022)

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

Lightweight Convolutional Neural Network and Its Application in Rolling Bearing Fault Diagnosis under Variable Working Conditions
por: Liu, Hengchang, et al.
Publicado: (2019)

Multiple time-frequency curve extraction Matlab code and its application to automatic bearing fault diagnosis under time-varying speed conditions
por: Huang, Huan, et al.
Publicado: (2019)

Tacholess Envelope Order Analysis and Its Application to Fault Detection of Rolling Element Bearings with Varying Speeds
por: Zhao, Ming, et al.
Publicado: (2013)

Intelligent Fault Diagnosis and Forecast of Time-Varying Bearing Based on Deep Learning VMD-DenseNet
por: Lin, Shih-Lin
Publicado: (2021)

Adaptive Multiclass Mahalanobis Taguchi System for Bearing Fault Diagnosis under Variable Conditions
por: Wang, Ning, et al.
Publicado: (2018)

A Semi-Supervised Approach to Bearing Fault Diagnosis under Variable Conditions towards Imbalanced Unlabeled Data
por: Chen, Xinan, et al.
Publicado: (2018)

A New Method of Wheelset Bearing Fault Diagnosis
por: Sun, Runtao, et al.
Publicado: (2022)

A Siamese Vision Transformer for Bearings Fault Diagnosis
por: He, Qiuchen, et al.
Publicado: (2022)

Bearing Fault Feature Extraction and Fault Diagnosis Method Based on Feature Fusion
por: Zhu, Huibin, et al.
Publicado: (2021)

Health Condition Estimation of Bearings with Multiple Faults by a Composite Learning-Based Approach
por: Inyang, Udeme, et al.
Publicado: (2021)

Fault Diagnosis of Rolling Bearings in Primary Mine Fans under Sample Imbalance Conditions
por: Cui, Wei, et al.
Publicado: (2023)

HUST bearing: a practical dataset for ball bearing fault diagnosis
por: Thuan, Nguyen Duc, et al.
Publicado: (2023)

Fault Diagnosis for Rolling Bearings under Variable Conditions Based on Visual Cognition
por: Cheng, Yujie, et al.
Publicado: (2017)

Fault Diagnosis of Rolling Bearings Based on a Residual Dilated Pyramid Network and Full Convolutional Denoising Autoencoder
por: Shi, Hongmei, et al.
Publicado: (2020)

A Bearing Fault Diagnosis Method Based on PAVME and MEDE
por: Yan, Xiaoan, et al.
Publicado: (2021)

Simulation of Friction Fault of Lightly Loaded Flywheel Bearing Cage and Its Fault Characteristics
por: Chen, Changrui, et al.
Publicado: (2022)

A New Monitoring Technology for Bearing Fault Detection in High-Speed Trains
por: Sun, Sitong, et al.
Publicado: (2023)

A New Universal Domain Adaptive Method for Diagnosing Unknown Bearing Faults
por: Yan, Zhenhao, et al.
Publicado: (2021)

Bearing Fault Diagnosis Based on Randomized Fisher Discriminant Analysis
por: Ye, Hejun, et al.
Publicado: (2022)

A Novel Fault Diagnosis Method of Rolling Bearings Based on AFEWT-KDEMI
por: Ge, Mingtao, et al.
Publicado: (2018)

A Rolling Bearing Fault Diagnosis Method Based on the WOA-VMD and the GAT
por: Wang, Yaping, et al.
Publicado: (2023)

An AVMD-DBN-ELM Model for Bearing Fault Diagnosis
por: Lei, Xue, et al.
Publicado: (2022)

A Reliable Health Indicator for Fault Prognosis of Bearings
por: Duong, Bach Phi, et al.
Publicado: (2018)

Synthesizing Rolling Bearing Fault Samples in New Conditions: A Framework Based on a Modified CGAN
por: Ahang, Maryam, et al.
Publicado: (2022)

Infrared Thermography Smart Sensor for the Condition Monitoring of Gearbox and Bearings Faults in Induction Motors
por: Alvarado-Hernandez, Alvaro Ivan, et al.
Publicado: (2022)

A New Fault Diagnosis of Rolling Bearing Based on Markov Transition Field and CNN
por: Wang, Mengjiao, et al.
Publicado: (2022)

Multi-Fault Detection of Rolling Element Bearings under Harsh Working Condition Using IMF-Based Adaptive Envelope Order Analysis
por: Zhao, Ming, et al.
Publicado: (2014)

A Rolling Bearing Fault Diagnosis Based on Conditional Depth Convolution Countermeasure Generation Networks under Small Samples
por: Peng, Cheng, et al.
Publicado: (2022)

A Novel Fault Diagnosis Approach for Chillers Based on 1-D Convolutional Neural Network and Gated Recurrent Unit
por: Wang, Zhuozheng, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_4arl630j40csu1dm2l64lmfpa9