Language :
English
中文
中文
YU KUN
Home
Scientific Research
Research Field
Paper Publications
Patents
Published Books
Research Projects
Teaching Research
Teaching Resources
Teaching Information
Teaching Achievement
Awards and Honours
Enrollment Information
Student Information
My Album
Blog
Recommended MA Supervisor
MOBILE Version
Paper Publications
Current position:
Home
>
Scientific Research
>
Paper Publications
[1]K. Yu, F. Chu, X. Wang and Y. Cheng, “Frequency domain energy-concentrated synchrosqueezing transform for frequency-varying signal with linear group delay,” IEEE Trans. Instrum. Meas., Accepted.
[2]K. Yu, X. Wang and Y. Cheng, “A post-processing method for time-reassigned multisynchrosqueezing transform and its application in processing the strong frequency-varying signal,” IEEE Trans. Instrum. Meas., DOI: 10.1109/TIM.2021.3112223.IEEE Transactions on Instrumentation and Measurement
[3]YU KUN,李岩,战启冉,张永超,邢镔.Intelligent Fault Diagnosis for Cross-Domain Few-Shot Learning of Rotating Equipment Based on Mixup Data Augmentation,2025,卷: 13期: 9
[4]YU KUN,chufei,wangxuesong,chengyuhu.Frequency-Domain Energy-Concentrated Synchrosqueezing Transform for Frequency-Varying Signal With Linear Group Delay,2022,卷: 71
[5]K. Yu, Q. Fu, H. Ma, T. R. Lin, and X. Li, “Simulation data driven weakly supervised adversarial domain adaptation approach for intelligent cross-machine fault diagnosis,” Struct. Health. Monit., DOI: 10.1177/1475921720980718.,2021
[6]Zhang, Yongchao,YU KUN,Ren, Zhaohui,Zhou, Shihua.Joint Domain Alignment and Class Alignment Method for Cross-Domain Fault Diagnosis of Rotating Machinery,2021,v 70,
[7]YU KUN,wangxuesong,chengyuhu.Post-Processing Method for Time-Reassigned Multisynchrosqueezing Transform and Its Application in Processing the Strong Frequency-Varying Signal,2021,卷: 70
[8]K. Yu, T. R. Lin, H. Ma, X. Li and X. Li, “A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning,” Mech. Syst. Signal Process., vol. 146, 107043, Jan. 2021.,2021
[9]K. Yu, H. Ma, T. R. Lin, and X. Li, “A consistency regularization based semi-supervised learning approach for intelligent fault diagnosis of rolling bearing,” Measurement, vol. 165, 107987, Dec. 2020.,2020
[10]K. Yu, H. Han, Q. Fu, H. Ma and J. Zeng, “Symmetric co-training based unsupervised domain adaptation approach for intelligent fault diagnosis of rolling bearing,” Meas. Sci. Technol., vol. 31, no. 11, 115008 (15pp), Aug. 2020.,2020
total19 1/2
first
previous
next
last
Page
