Cargando…

Bearing Fault Diagnosis via Improved One-Dimensional Multi-Scale Dilated CNN

Bearings are the key and important components of rotating machinery. Effective bearing fault diagnosis can ensure operation safety and reduce maintenance costs. This paper aims to develop a novel bearing fault diagnosis method via an improved multi-scale convolutional neural network (IMSCNN). In tra...

Descripción completa

Detalles Bibliográficos
Autores principales:	He, Jiajun, Wu, Ping, Tong, Yizhi, Zhang, Xujie, Lei, Meizhen, Gao, Jinfeng
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2021
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8588188/ https://www.ncbi.nlm.nih.gov/pubmed/34770636 http://dx.doi.org/10.3390/s21217319

Ejemplares similares

Intelligent Bearing Fault Diagnosis Based on Feature Fusion of One-Dimensional Dilated CNN and Multi-Domain Signal Processing
por: Dong, Kaitai, et al.
Publicado: (2023)

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

CNN Hardware Accelerator for Real-Time Bearing Fault Diagnosis
por: Chung, Ching-Che, et al.
Publicado: (2023)

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

Unsupervised Domain Adaptive 1D-CNN for Fault Diagnosis of Bearing
por: Shao, Xiaorui, et al.
Publicado: (2022)

Rolling Bearing Fault Diagnosis Using Multi-Sensor Data Fusion Based on 1D-CNN Model
por: Wang, Hongwei, 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)

Fault Diagnosis of Motor Bearings Based on a One-Dimensional Fusion Neural Network
por: Jian, Xianzhong, et al.
Publicado: (2019)

Combining Multi-Scale Wavelet Entropy and Kernelized Classification for Bearing Multi-Fault Diagnosis
por: Rodriguez, Nibaldo, et al.
Publicado: (2019)

Fault Diagnosis of Rolling Bearing Based on HPSO Algorithm Optimized CNN-LSTM Neural Network
por: Tian, He, et al.
Publicado: (2023)

Composite Multivariate Multi-Scale Permutation Entropy and Laplacian Score Based Fault Diagnosis of Rolling Bearing
por: Ying, Wanming, et al.
Publicado: (2022)

Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis
por: Yasir, Muhammad Naveed, et al.
Publicado: (2018)

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

Learning Attention Representation with a Multi-Scale CNN for Gear Fault Diagnosis under Different Working Conditions
por: Yao, Yong, et al.
Publicado: (2020)

Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability
por: Xie, Wenlang, et al.
Publicado: (2022)

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

An Intelligent Fault Diagnosis Method for Bearings with Variable Rotating Speed Based on Pythagorean Spatial Pyramid Pooling CNN
por: Guo, Sheng, et al.
Publicado: (2018)

The combination model of CNN and GCN for machine fault diagnosis
por: Zhang, Qianqian, et al.
Publicado: (2023)

Research on rolling bearing fault diagnosis based on multi-dimensional feature extraction and evidence fusion theory
por: Li, Jingchao, et al.
Publicado: (2019)

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

A Feature Extraction Method Using Improved Multi-Scale Entropy for Rolling Bearing Fault Diagnosis
por: Ju, Bin, et al.
Publicado: (2018)

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

Improving rolling bearing online fault diagnostic performance based on multi-dimensional characteristics
por: Yang, Chuanlei, et al.
Publicado: (2018)

A Rolling Bearing Fault Diagnosis Method Based on EEMD-WSST Signal Reconstruction and Multi-Scale Entropy
por: Ge, Jianghua, et al.
Publicado: (2020)

Bearing Fault Reconstruction Diagnosis Method Based on ResNet-152 with Multi-Scale Stacked Receptive Field
por: Yu, Hu, et al.
Publicado: (2022)

An Improved Incipient Fault Diagnosis Method of Bearing Damage Based on Hierarchical Multi-Scale Reverse Dispersion Entropy
por: Xing, Jiaqi, et al.
Publicado: (2022)

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

Sensor and Actuator Fault Diagnosis for Robot Joint Based on Deep CNN
por: Pan, Jinghui, et al.
Publicado: (2021)

Application of CNN-Based Machine Learning in the Study of Motor Fault Diagnosis
por: Peng, Xiuyan, et al.
Publicado: (2022)

An Imbalanced Fault Diagnosis Method Based on TFFO and CNN for Rotating Machinery
por: Zhang, Long, et al.
Publicado: (2022)

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

An Effective Bearing Fault Diagnosis Technique via Local Robust Principal Component Analysis and Multi-Scale Permutation Entropy
por: Ge, Mao, et al.
Publicado: (2019)

Time-Shift Multi-scale Weighted Permutation Entropy and GWO-SVM Based Fault Diagnosis Approach for Rolling Bearing
por: Dong, Zhilin, et al.
Publicado: (2019)

Rolling Bearing Fault Diagnosis Based on Refined Composite Multi-Scale Approximate Entropy and Optimized Probabilistic Neural Network
por: Ma, Jianpeng, et al.
Publicado: (2021)

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

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

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

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN
por: Liu, Chang, et al.
Publicado: (2018)

An Approach to Intelligent Fault Diagnosis of Cryocooler Using Time-Frequency Image and CNN
por: Gao, Sheng, et al.
Publicado: (2022)

Fault Diagnosis of the Dynamic Chemical Process Based on the Optimized CNN-LSTM Network
por: Chen, Honghua, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_8u1isutd5t98jvpoq0ce07tsde