Cargando…

A Convolutional Neural Network for Electrical Fault Recognition in Active Magnetic Bearing Systems

Active magnetic bearings are complex mechatronic systems that consist of mechanical, electrical, and software parts, unlike classical rolling bearings. Given the complexity of this type of system, fault detection is a critical process. This paper presents a new and easy way to detect faults based on...

Descripción completa

Detalles Bibliográficos
Autores principales:	Donati, Giovanni, Basso, Michele, Manduzio, Graziano A., Mugnaini, Marco, Pecorella, Tommaso, Camerota, Chiara
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2023
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458593/ https://www.ncbi.nlm.nih.gov/pubmed/37631560 http://dx.doi.org/10.3390/s23167023

Ejemplares similares

Application of Convolutional Neural Network in Motor Bearing Fault Diagnosis
por: Zhou, Shuiqin, et al.
Publicado: (2022)

Bearing Fault Diagnosis Method Based on Convolutional Neural Network and Knowledge Graph
por: Li, Zhibo, et al.
Publicado: (2022)

An Ensemble Convolutional Neural Networks for Bearing Fault Diagnosis Using Multi-Sensor Data
por: Liu, Yang, et al.
Publicado: (2019)

Bearing fault diagnosis based on particle swarm optimization fusion convolutional neural network
por: Liu, Xian, et al.
Publicado: (2022)

Multi-Fault Classification and Diagnosis of Rolling Bearing Based on Improved Convolution Neural Network
por: Zhang, Xiong, et al.
Publicado: (2023)

An improved multi-scale branching convolutional neural network for rolling bearing fault diagnosis
por: Xu, Meng, et al.
Publicado: (2023)

Sensor Data-Driven Bearing Fault Diagnosis Based on Deep Convolutional Neural Networks and S-Transform
por: Li, Guoqiang, et al.
Publicado: (2019)

Bearing-Fault Diagnosis with Signal-to-RGB Image Mapping and Multichannel Multiscale Convolutional Neural Network
por: Xu, Ming, et al.
Publicado: (2022)

An Anti-Noise Convolutional Neural Network for Bearing Fault Diagnosis Based on Multi-Channel Data
por: Zhang, Wei-Tao, et al.
Publicado: (2023)

An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis
por: Li, Shaobo, et al.
Publicado: (2017)

Bearing Fault Diagnosis Method Based on Deep Convolutional Neural Network and Random Forest Ensemble Learning
por: Xu, Gaowei, et al.
Publicado: (2019)

A Deep Autoencoder-Based Convolution Neural Network Framework for Bearing Fault Classification in Induction Motors
por: Toma, Rafia Nishat, et al.
Publicado: (2021)

Bearing Fault Diagnosis Using Lightweight and Robust One-Dimensional Convolution Neural Network in the Frequency Domain
por: Hakim, Mohammed, et al.
Publicado: (2022)

MAB-DrNet: Bearing Fault Diagnosis Method Based on an Improved Dilated Convolutional Neural Network
por: Zhang, Feiqing, et al.
Publicado: (2023)

Fusion of Audio and Vibration Signals for Bearing Fault Diagnosis Based on a Quadratic Convolution Neural Network
por: Yan, Jin, et al.
Publicado: (2023)

Bearing Fault Diagnosis with a Feature Fusion Method Based on an Ensemble Convolutional Neural Network and Deep Neural Network
por: Li, Hongmei, et al.
Publicado: (2019)

Light convolutional neural network by neural architecture search and model pruning for bearing fault diagnosis and remaining useful life prediction
por: Ruan, Diwang, et al.
Publicado: (2023)

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

Research on a Bearing Fault Enhancement Diagnosis Method with Convolutional Neural Network Based on Adaptive Stochastic Resonance
por: Wang, Chen, et al.
Publicado: (2022)

Boosted Convolutional Neural Network Algorithm for the Classification of the Bearing Fault form 1-D Raw Sensor Data
por: Knap, Paweł, et al.
Publicado: (2023)

Application of a new one-dimensional deep convolutional neural network for intelligent fault diagnosis of rolling bearings
por: Xie, Shenglong, et al.
Publicado: (2020)

Bearing Fault Diagnosis under Variable Speed Using Convolutional Neural Networks and the Stochastic Diagonal Levenberg-Marquardt Algorithm
por: Tra, Viet, et al.
Publicado: (2017)

Intelligent Compound Fault Diagnosis of Roller Bearings Based on Deep Graph Convolutional Network
por: Chen, Caifeng, et al.
Publicado: (2023)

Fault Diagnosis for High-Speed Train Axle-Box Bearing Using Simplified Shallow Information Fusion Convolutional Neural Network
por: Luo, Honglin, et al.
Publicado: (2020)

A Bearing Fault Diagnosis Method Based on Wavelet Packet Transform and Convolutional Neural Network Optimized by Simulated Annealing Algorithm
por: He, Feng, et al.
Publicado: (2022)

A Novel End-To-End Fault Diagnosis Approach for Rolling Bearings by Integrating Wavelet Packet Transform into Convolutional Neural Network Structures
por: Xiong, Shoucong, et al.
Publicado: (2020)

A Bearing Fault Classification Framework Based on Image Encoding Techniques and a Convolutional Neural Network under Different Operating Conditions
por: Toma, Rafia Nishat, et al.
Publicado: (2022)

A Novel Deep Convolutional Neural Network Combining Global Feature Extraction and Detailed Feature Extraction for Bearing Compound Fault Diagnosis
por: Han, Shuzhen, et al.
Publicado: (2023)

Deep Learning-Based Adaptive Neural-Fuzzy Structure Scheme for Bearing Fault Pattern Recognition and Crack Size Identification
por: Piltan, Farzin, et al.
Publicado: (2021)

Fault Diagnosis of Wind Turbine Based on Convolution Neural Network Algorithm
por: Xiao, Wei, et al.
Publicado: (2022)

A graph neural network-based bearing fault detection method
por: Xiao, Lu, et al.
Publicado: (2023)

Convolutional-de-convolutional neural networks for recognition of surgical workflow
por: Chen, Yu-wen, et al.
Publicado: (2022)

A Novel Anti-Noise Fault Diagnosis Approach for Rolling Bearings Based on Convolutional Neural Network Fusing Frequency Domain Feature Matching Algorithm
por: Zhou, Xiangyu, et al.
Publicado: (2021)

A Novel Intelligent Fault Diagnosis Method for Rolling Bearings Based on Wasserstein Generative Adversarial Network and Convolutional Neural Network under Unbalanced Dataset
por: Tang, Hongtao, et al.
Publicado: (2021)

A Two-Stage, Intelligent Bearing-Fault-Diagnosis Method Using Order-Tracking and a One-Dimensional Convolutional Neural Network with Variable Speeds
por: Ji, Mengyu, et al.
Publicado: (2021)

Development of Compound Fault Diagnosis System for Gearbox Based on Convolutional Neural Network
por: Lin, Ming-Chang, et al.
Publicado: (2020)

Convolutional Neural Network-Based Transformer Fault Diagnosis Using Vibration Signals
por: Li, Chao, et al.
Publicado: (2023)

A Deep Neural Network-Based Feature Fusion for Bearing Fault Diagnosis
por: Hoang, Duy Tang, et al.
Publicado: (2021)

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

Fault Diagnosis of Active Magnetic Bearing–Rotor System via Vibration Images
por: Yan, Xunshi, et al.
Publicado: (2019)

Cannot write session to /tmp/vufind_sessions/sess_6h7a1glp40pbbkpqr9po5b1evu