A rolling bearing fault diagnosis method using novel lightweight neural network-Reference-Cited by-同舟云学术

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A rolling bearing fault diagnosis method using novel lightweight neural network

Published:2021-08-25 Issue:12 Volume:32 Page:125102
ISSN:0957-0233
Container-title:Measurement Science and Technology
language:
Short-container-title:Meas. Sci. Technol.

Author:

He Deqiang^ORCID,Liu Chenyu,Chen Yanjun^ORCID,Jin Zhenzhen,Li Xianwang,Shan Sheng

Funder

Major Science and Technology Project of Guangxi Province of Chin

National Natural Science Foundation of China

Nanning Excellent Young Scientist Program

Guangxi Manufacturing Systems and Advanced Manufacturing Technology Key Laboratory Director Fund

Publisher

IOP Publishing

Subject

Applied Mathematics,Instrumentation,Engineering (miscellaneous)

Link

https://iopscience.iop.org/article/10.1088/1361-6501/ac1a5e/pdf

Reference27 articles.

1. Research of a fault diagnosis method for rolling bearing based on improved multiscale range entropy and hierarchical prototype;Zheng;Meas. Sci. Technol.,2021

2. Obstacle detection in the dangerous area of railway track based on convolutional neural network;He;Meas. Sci. Technol.,2021

3. Exploration of the correlation between welding flaw geometrical parameters and floating potential based on an ultrasonic duplex finite element model;He;Measurement,2021

4. An improved feature extraction method using texture analysis with LBP for bearing fault diagnosis;Kaplan;Appl. Soft Comput.,2020

5. Bearing fault diagnosis based on deep learning feature extraction and WOA-SVM state recognition;Shao;Vib. Shock,2019

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2. Improved metric-based meta learning with attention mechanism for few-shot cross-domain train bearing fault diagnosis;Measurement Science and Technology;2024-04-03

3. A lightweight improved residual neural network for bearing fault diagnosis;Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science;2024-03-28

4. A Lightweight Group Transformer-Based Time Series Reduction Network for Edge Intelligence and Its Application in Industrial RUL Prediction;IEEE Transactions on Neural Networks and Learning Systems;2024

5. LAFICNN: A Novel Convolutional Adaptive Fusion Framework for Fault Diagnosis of Rotating Machinery;IEEE Transactions on Instrumentation and Measurement;2024

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