西南交通大学教师主页 liyang--Home-- Yang Li*, X Meng, F Xu, S Xiao. Intelligent fault diagnosis of hoisting systems under complex working conditions using deep graph convolutional generative adversarial networks with limited data

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Date of Birth: 1993-08-13

Date of Employment: 2022-12-26

Education Level: PhD graduate

Degree: Doctor of engineering

Gender: Male

Status: 在岗

Alma Mater: 东南大学

School/Department: 城市轨道交通学院（智慧城市与交通学院）

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Home > Research > Paper Publications

Yang Li*, X Meng, F Xu, S Xiao. Intelligent fault diagnosis of hoisting systems under complex working conditions using deep graph convolutional generative adversarial networks with limited data

Impact Factor:6.245
Journal:Structural Health Monitoring
Indexed by:SCI
Page Number:14759217241279789. (IF=6.245)
Translation or Not:no
Date of Publication:2024-10-10
Included Journals:SCI

Pre One:Yang Li*, Meng Xiangyin, Feiyun Xu（许飞云）, Xiao Shide. Persistent homology deep meta-transfer learning for intelligent fault diagnosis of storage stacking machinery under high-speed and heavy-load conditions

Next One:Yang Li, X Meng*, S Xiao, F Xu, CG Lee. Multivariate variational mode decomposition and generalized composite multiscale permutation entropy for multichannel fault diagnosis of hoisting machinery system