Abstract
This paper presents results of the rate of change of frequency (ROCOF) estimation using Huang’s Empirical Mode Decomposition (EMD), Multivariate Empirical Mode Decomposition (MEMD) and Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD). On the generated test signals algorithms are performed and the obtained results are compared and discussed. The results are compared with actual values of the rate of change of frequency obtained by derivatization of the generated test signals as input data of the aforementioned algorithms. The performance of the algorithm are also tested using signals contaminated by zero-mean Gaussian noise. The results of rate of change of frequency estimation indicates that all three algorithms have great accuracy in the rate of change of frequency estimation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Daubechies, I., Lu, J., Wu, H.-T.: Synchrosqueezing wavelet transforms: an empirical mode decomposition-like tool. Appl. Comput. Harmon. Anal. 30(2), 243–261 (2011)
Huang, N.E., Shen, Z., Long, S.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.-C., Tung, C.C., Liu, H.H.: The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc. R. Soc. London A 454(1971), 903–995 (1998)
Hou, T.Y., Shi, Z.: Adaptive data analysis via sparse time–frequency representation. Adv. Adapt. Data Anal. 3(1), 1–28 (2011)
Hou, T.Y., Shi, Z.: Data driven time frequency analysis. Appl. Comput. Harmon. Anal. 35(2), 284–308 (2013)
Huang, N.E., Wu, Z., Long, S.R., Arnold, K.C., Chen, X., Blank, K.: On instantaneous frequency. Adv. Adapt. Data Anal. 1(2), 177–229 (2009)
Meeson Jr., R.N.: HHT sifting and filtering. In: Huang, N.E., Shen, S.S.S. (eds.) Hilbert–Huang Transform and Its Applications, pp. 75–105. World Scientific, Singapore (2005)
Looney, D., Mandic, D.P.: Multi-scale image fusion using complex EMD. IEEE Trans. Sig. Process. 57(4), 1626–1630 (2009)
Wu, Z., Huang, N.E.: Ensemble empirical mode decomposition: A noise-assisted data analysis method. Adv. Adapt. Data Anal. 1(1), 1–41 (2009)
Mandic, D.P., ur Rehman, N., Wu, Z., Huang, N.E.: Empirical mode decomposition-based time-frequency analysis of multivariate. IEEE Sig. Process. Mag. 30(6) (2013). https://doi.org/10.1109/msp.2013.2267931
Rehman, N., Mandic, D.P.: Multivariate empirical mode decomposition. Proc. Math. Phys. Eng. Sci. 466(2117), 1291–1302 (2009)
Rehman, N.U., Park, C., Huang, N.E., Mandic, D.P.: EMD via MEMD: multivariate noise aided computation of standard EMD. Adv. Adapt. Data Anal. 5(2), 1350007 (2013)
Rehman, N., Mandic, D.P.: Filterbank property of multivariate EMD. IEEE Trans. Sig. Process. 59(5), 2421–2426 (2011)
Dedović, M.M., Avdaković, S.: A new approach for df/dt and active power imbalance in power system estimation using Huang’s empirical mode decomposition. Int. J. Electr. Power Energ. Syst. 110, 62–71
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Dedović, M.M., Avdaković, S., Dautbašić, N., Mujezinović, A. (2020). ROCOF Estimation via EMD, MEMD and NA-MEMD. In: Avdaković, S., Mujčić, A., Mujezinović, A., Uzunović, T., Volić, I. (eds) Advanced Technologies, Systems, and Applications IV -Proceedings of the International Symposium on Innovative and Interdisciplinary Applications of Advanced Technologies (IAT 2019). IAT 2019. Lecture Notes in Networks and Systems, vol 83. Springer, Cham. https://doi.org/10.1007/978-3-030-24986-1_12
Download citation
DOI: https://doi.org/10.1007/978-3-030-24986-1_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-24985-4
Online ISBN: 978-3-030-24986-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)