Research on Fault Diagnosis of Rolling Bearings Based on Progressive Grid Optimization ResNet-Reference-Cited by-同舟云学术

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Research on Fault Diagnosis of Rolling Bearings Based on Progressive Grid Optimization ResNet

Published:2023-08-11 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Image Processing and Computer Applications (ICIPCA)
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Author:

Kang Okai¹,Xu Haochao²,Wang Chunli³

Affiliation:

1. School of Mechanical Engineering, Dalian Jiaotong University,Dalian,Liaoning Province,China

2. School of Mechanical Engineering, Northeastern University,Qinhuangdao,Hebei Province,China

3. School of Mechanical and Electrical Engineering, Harbin Engineering University,Harbin,Heilongjiang Province,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10256676/10257667/10257961.pdf?arnumber=10257961

Reference11 articles.

1. The Use of Fast Multivariate Empirical Mode Decomposition for Oscillation Monitoring in Noisy Process Plant[J];lang;Industrial & Engineering Chemistry Research,2020

2. Optimal Fractional Fourier Filtering for Graph Signals[J];ozturk;IEEE Transactions on Signal Processing,2021

3. Application of BP Neural Network and Convolutional Neural Network (CNN) in Bearing Fault Diagnosis

4. A survey and classification of incipient fault diagnosis approaches

5. A novel mechanical fault signal feature extraction method based on unsaturated piecewise tri-stable stochastic resonance[J];zhao;Measurement,2020

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