Fault Diagnosis of Rolling Bearings Based on the Improved Symmetrized Dot Pattern Enhanced Convolutional Neural Networks

被引：0
作者：
Xiaoping Liu
Lijian Xia
Jian Shi
Lijie Zhang
Shaoping Wang
机构：
[1] Beihang University,School of Automation Science and Electrical Engineering
[2] Yanshan University,Key Laboratory of Advanced Forging and Stamping Technology and Science of Ministry of Education of China
[3] Yanshan University,Hebei Key Laboratory of Heavy Machinery Fluid Power Transmission and Control
来源：
Journal of Vibration Engineering & Technologies | 2024年 / 12卷
关键词：
Convolutional neural networks; Symmetrized dot pattern; Fault diagnosis; Rolling bearing;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：1897 / 1908
页数：11
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共 124 条
  • [21] Tang Y(2016)Real-time motor fault detection by 1-D convolutional neural networks[J] IEEE Trans Industr Electron 63 7067-446
  • [22] Zhang X(2017)Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks[J] J Sound Vib 388 154-535
  • [23] Qin G(2021)A fault diagnosis method based on one-dimensional data enhancement and convolutional neural network[J] Measurement 180 109532-10
  • [24] Sun Y(2022)Application of generalized frequency response functions and improved convolutional neural network to fault diagnosis of heavy-duty industrial robot[J] Robot Comp-Integra Manufact 73 102228-327
  • [25] Li S(2017)A new convolutional neural network-based data-driven fault diagnosis method[J] IEEE Trans Industr Electron 65 5990-14190
  • [26] Wang Y(2019)Bearing fault diagnosis method based on deep convolutional neural network and random forest ensemble learning[J] Sensors 19 1088-undefined
  • [27] Wang S(2018)A novel fault diagnosis method for rotating machinery based on a convolutional neural network[J] Sensors 18 1429-undefined
  • [28] Wang H(2018)Highly accurate machine fault diagnosis using deep transfer learning[J] IEEE Trans Industr Inf 15 2446-undefined
  • [29] Zhou Y(2017)Deep learning enabled fault diagnosis using time-frequency image analysis of rolling element bearings[J] Shock Vib 2017 5067651-undefined
  • [30] Tran V(2019)Fault diagnosis of reciprocating compressor based on convolutional neural networks with multisource raw vibration signals[J] Math Probl Eng 2019 6921975-undefined
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