A generalized adaptive variational mode decomposition method for nonstationary signals with mode overlapped components |
Liu, Jing-Liang
(College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University)
Qiu, Fu-Lian (College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University) Lin, Zhi-Ping (Fujian Expressway Group Co., LTD) Li, Yu-Zu (College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University) Liao, Fei-Yu (College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University) |
1 | Cempel, C. and Tabaszewski, M. (2007), "Multidimensional condition monitoring of machines in non-stationary operation", Mech. Syst. Sig. Pr., 21(3), 1233-1241. https://doi.org/10.1016/j.ymssp.2006.04.001 DOI |
2 | Bagheri, A., Ozbulut, O.E. and Harris, D.K. (2018), "Structural system identification based on variational mode decomposition", J. Sound Vib., 417, 182-197. https://doi.org/10.1016/j.jsv.2017.12.014 DOI |
3 | Chen, G.D. and Wang, Z.C. (2012), "A signal decomposition theorem with Hilbert transform and its application to narrowband time series with closely-spaced frequency components", Mech. Syst. Sig. Pr., 28, 258-279. https://doi.org/10.1016/j.ymssp.2011.02.002 DOI |
4 | Daubechies, I., Lu, J.F. and Wu, H.T. (2011), "Synchrosqueezed wavelet transforms: an empirical mode decomposition-like tool", Appl. Comput. Harmon. Anal., 30(2), 243-261. https://doi.org/10.1016/j.acha.2010.08.002 DOI |
5 | Chen, X.Y. and Cui, B.B. (2016), "Efficient modeling of fiber optic gyroscope drift using improved EEMD and extreme learning machine", Signal Process., 128, 1-7. https://doi.org/10.1016/j.sigpro.2016.03.016 DOI |
6 | Chen, S.Q., Yang, Y., Dong, X.J., Xing, G.P., Peng, Z.K. and Zhang, W.M. (2019), "Warped variational mode decomposition with application to vibration signals of varying-speed rotating machineries", IEEE Trans. Instrum. Meas., 68(8), 2755-2767. https://doi.org/10.1109/TIM.2018.2869440 DOI |
7 | Dragomiretskiy, K. and Zosso, D. (2014), "Variational mode decomposition", IEEE Trans. Sig. Pr., 62(3), 531-544. https://doi.org/10.1109/TSP.2013.2288675 DOI |
8 | Lahmiri, S. (2014), "Comparative study of ECG signal denoising by wavelet thresholding in empirical and variational mode decomposition domains", Healthc. Technol. Lett., 1, 104-109. https://doi.org/10.1049/htl.2014.0073 DOI |
9 | Feng, Z.P., Yu, X.N., Zhang, D. and Liang, M. (2020), "Generalized adaptive mode decomposition for nonstationary signal analysis of rotating machinery: Principle and applications", Mech. Syst. Sig. Pr., 136, 106530. https://doi.org/10.1016/j.ymssp.2019.106530 DOI |
10 | Mohanty, Gupta, K.K. and Raju, K.S. (2014), "Bearing fault analysis using variational mode decomposition", Proceedings of the 9th International Conference on Industrial and Information Systems, Gwalior, India, December, pp. 1-6. https://doi.org/10.1109/ICIINFS.2014.7036617 DOI |
11 | Liu, J.L., Wei, X.J., Qiu, R.H., Zheng, J.Y., Zhu, Y.J. and Laory, I. (2018), "Instantaneous frequency extraction in time-varying structures using a maximum gradient method", Smart Struct. Syst., Int. J.., 22(3), 359-368. https://doi.org/10.12989/sss.2018.22.3.359 DOI |
12 | Le, T.H. and Caracoglia, L. (2015), "High-order, closely-spaced modal parameter estimation using wavelet analysis", Struct. Eng. Mech., Int. J., 56(3), 423-442. https://doi.org/10.12989/sem.2015.56.3.423 DOI |
13 | Feldman, M. (2006), "Time-varying vibration decomposition and analysis based on the Hilbert transform", J. Sound Vib., 295(3-5), 518-530. https://doi.org/10.1016/j.jsv.2005.12.058 DOI |
14 | Ferhatoglu, E., Cigeroglu, E. and Ozguven, H.N. (2018), "A new modal superposition method for nonlinear vibration analysis of structures using hybrid mode shapes", Mech. Syst. Sig. Pr., 107, 317-342. https://doi.org/10.1016/j.ymssp.2018.01.036 DOI |
15 | Isham, M.F., Leong, M.S., Lim, M.H. and Ahmad, Z.A. (2018), "Variational mode decomposition: mode determination method for rotating machinery diagnosis", J. Vib., 20(7), 2604-2621. https://doi.org/10.21595/jve.2018.19479 DOI |
16 | Lee, J.H., Kim, J. and Kim, H.J. (2001), "Development of enhanced wigner-ville distribution function", Mech. Syst. Sig. Pr., 15(2), 367-398. https://doi.org/10.1006/mssp.2000.1365 DOI |
17 | Thakur, G., Brevdo, E., Fuckar, N.S. and Wu, H.T. (2013), "The Synchrosqueezing algorithm for time-varying spectral analysis: Robustness properties and new paleoclimate applications", Signal Process., 93(5), 1079-1094. https://doi.org/10.1016/j.sigpro.2012.11.029 DOI |
18 | Zhu, J., Wang, C., Hu, Z.Y., Kong, F.R. and Liu, X.C. (2015), "Adaptive variational mode decomposition based on artificial fish swarm algorithm for fault diagnosis of rolling bearings", J. Mech. Eng. Sci., 231(4), 635-654. https://doi.org/10.1177/0954406215623311 DOI |
19 | Clausel, M., Oberlin, T. and Perrier, V. (2015), "The monogenic synchrosqueezed wavelet transform: A tool for the decomposition/demodulation of AM-FM images", Appl. Comput. Harmon. Anal., 39(3), 450-486. https://doi.org/10.1016/j.acha.2014.10.003 DOI |
20 | Olhede, S. and Walden, A.T. (2005), "A generalized demodulation approach to time-frequency projections for multicomponent signals", Proc. R. Soc. A., 461(2059), 2159-2179. https://doi.org/10.1098/rspa.2005.1455 DOI |
21 | Wang, C., Ren, W.X., Wang, Z.C. and Zhu, H.P. (2013), "Instantaneous frequency identification of time-varying structures by continuous wavelet transform", Eng. Struct., 52(9), 17-25. https://doi.org/10.1016/j.engstruct.2013.02.006 DOI |
22 | Oberlin, T., Meignen, S. and Perrier, V. (2015), "Second-order synchrosqueezing transform or invertible reassignment? Towards ideal time-frequency representations", IEEE Trans. Sig. Pr., 63(5), 1335-1344. https://doi.org/10.1109/TSP.2015.2391077 DOI |
23 | Li, C. and Liang, M. (2012), "A generalized synchrosqueezing transform for enhancing signal time-frequency representation", Signal Process., 92(9), 2264-2274. https://doi.org/10.1016/j.sigpro.2012.02.019 DOI |
24 | Liu, J.L., Wang, Z.C., Ren, W.X. and Li, X.X. (2015), "Structural time-varying damage detection using synchrosqueezing wavelet transform", Smart Struct. Syst., Int. J., 15(1), 119-133. https://doi.org/10.12989/sss.2015.15.1.119 DOI |
25 | Liu, J.L., Zheng, J.Y., Wei, X.J., Ren, W.X. and Laory, I. (2019), "A combined method for instantaneous frequency identification in low frequency structures", Eng. Struct., 194, 370-383. https://doi.org/10.1016/j.engstruct.2019.05.057 DOI |
26 | Auger, F. and Flandrin, P. (1995), "Improving the readability of time-frequency and time-scale representations by the reassignment method", IEEE Trans. Sig. Pr., 43(5), 1068-1089. https://doi.org/10.1109/78.382394 DOI |
27 | Poon, C.W. and Chang, C.C. (2007), "Identification of nonlinear elastic structures using empirical mode decomposition and nonlinear normal modes", Smart Struct. Syst., 3(4), 423-437. https://doi.org/10.12989/sss.2007.3.4.423 DOI |
28 | Smith, J.S. (2005), "The local mean decomposition and its application to EEG perception data", J. R. Soc. Interface, 2, 443-454. https://doi.org/10.1098/rsif.2005.0058 DOI |
29 | Huang, N.E., Shen, Z., Long, S.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.C., Tung, C.C. and Liu, H.H. (1998), "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis", Proc. Math. Phys. Eng. Sci., 454, 903-995. https://doi.org/10.1098/rspa.1998.0193 DOI |