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俞昆
( 讲师 )
赞
的个人主页 http://faculty.cumt.edu.cn/YK77/zh_CN/index.htm
讲师 硕士生导师
教师拼音名称:
yukun
电子邮箱:
6981ee171d049963ef68393cfb26398d69df9c0f6c49928ada19cb434e8b22ee4c6057fbb19203d5d46948542c47105c644bc6b7b1add1a1cd90979d4a6ccb2537a0dce89ac5d422a14e2ce67f1c017d36e92b2bc925543b02c70f2d770600c26693b3e988c90ecf787b0e674233fa877560b03ae18c149e9168a1b1de1f927c
所在单位:
信息与控制工程学院
职务:
讲师
学历:
博士研究生毕业
性别:
男
联系方式:
kunyu9198@126.com
学位:
博士
在职信息:
在岗
毕业院校:
东北大学
论文成果
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论文成果
[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]
俞昆,褚菲,王雪松,程玉虎.Frequency-Domain Energy-Concentrated Synchrosqueezing Transform for Frequency-Varying Signal With Linear Group Delay,2022,卷: 71
[4]
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
[5]
俞昆,王雪松,程玉虎.Post-Processing Method for Time-Reassigned Multisynchrosqueezing Transform and Its Application in Processing the Strong Frequency-Varying Signal,2021,卷: 70
[6]
Zhang, Yongchao,俞昆,Ren, Zhaohui,Zhou, Shihua.Joint Domain Alignment and Class Alignment Method for Cross-Domain Fault Diagnosis of Rotating Machinery,2021,v 70,
[7]
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
[8]
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
[9]
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
[10]
K. Yu, H. Ma, H. Han, J. Zeng, H. Li, X. Li, Z. Xu and B. Wen, “Second order multi-synchrosqueezing transform for rub-impact detection of rotor systems,” Mech. Mach. Theory, vol. 140, pp. 321-349, Oct. 2019.,2020
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