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[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]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
[4]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
[5]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
[6]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
[7]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
[8]K. Yu, T. R. Lin, H. Ma, H. Li and J. Zeng, “A combined polynomial chirplet transform and synchroextracting technique for analyzing nonstationary signals of rotating machinery,” IEEE Trans. Instrum. Meas., vol. 69, no. 4, pp. 1505-1518, Apr. 2020.,2020
[9]K. Yu, H. Ma, J. Zeng, H. Han, H. Li and B. Wen, “Frobenius and nuclear hybrid norm penalized robust principal component analysis for transient impulsive feature detection of rolling bearings,” ISA Trans., vol. 100, pp. 373-386, May. 2020.,2020
[10]K. Yu, T.R. Lin and J. Tan, “A bearing fault and severity diagnostic technique using adaptive deep belief networks and Dempster–Shafer theory,” Struct. Health. Monit., vol. 19, no. 1, pp. 240-261, Jan. 2020.,2020
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