Fault prediction of rolling bearings using a multi-scale convolutional neural network with parallel BiLSTM for noise environment

被引：0
|
作者：
Li, Junxing [1 ,2 ,3 ,4 ]
Xu, Hang [1 ]
Fan, Jiahui [1 ]
Zhuang, Jichao [4 ,5 ]
机构：
[1] School of Mechatronical Engineering, Henan University of Science and Technology, Luoyang,471003, China
[2] Collaborative Innovation Center of Hennan Province for Advanced Manufacturing of Machinery and Equipment, Luoyang,471003, China
[3] Collaborative Innovation Center of Hennan Province for High-End Bearing, Luoyang,471003, China
[4] Industrial Systems Engineering and Management, National University of Singapore, Singapore, Singapore
[5] School of Mechanical Engineering, Southeast University, Nanjing,211189, China
来源：
Journal of Mechanical Science and Technology | 2024年 / 38卷 / 11期
基金：
中国国家自然科学基金;
关键词：
Convolution - Empirical mode decomposition - Long short-term memory - Multilayer neural networks - Problem solving - Roller bearings;
D O I：
10.1007/s12206-024-1009-9
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：5867 / 5883
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