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Algorithm for simultaneous parameter estimation of a multi-harmonic signal

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Języki publikacji
PL
Abstrakty
EN
Estimating the fundamental frequency and harmonic parameters is basic for signal modelling in a power supply system. Differing from the existing parameter estimation algorithms either in power quality monitoring or in harmonic compensation, the proposed algorithm enables a simultaneous estimation of the fundamental frequency, the amplitudes and phases of harmonic waves. A pure sinusoid is obtained from an input multi-harmonic input signal by finite-impulse-response (FIR) comb filters. Proposed algorithm is based on the use of partial derivatives of the processed signal and the weighted estimation procedure to estimate the fundamental frequency, the amplitude and the phase of a multi-sinusoidal signal. The proposed algorithm can be applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The simulation results verify the effectiveness of the proposed algorithm.
Rocznik
Strony
693--702
Opis fizyczny
Bibliogr. 19 poz., rys., tab., wykr.
Twórcy
  • University of Kragujevac, Technical Faculty Čačak, Svetog Save 65, 32000 Čačak, Serbia, predragp@tfc.kg.ac.rs
Bibliografia
  • [1] Wang, F., Bollen, M. (2004). Frequency response characteristics and error estimation in RMS measurement. IEEE Trans. Power Delivery, 19(4), 1569-1578.
  • [2] Duda, K. (2010). Accurate, Guaranteed-Stable, Sliding DFT. IEEE Signal Processing Mag., 124-127.
  • [3] Jacobsen, E., Lyons, R. (2003). The sliding DFT. IEEE Signal Processing Mag., 20(2), 74-80.
  • [4] Wu, R.C., Chiang, C.T. (2010). Analysis of the Exponential Signal by the Interpolated DFT Algorithm. IEEE Trans. Instrum. Meas., 59(12), 3306-3317.
  • [5] Duda, K. (2011). Interpolation Algorithms of DFT for Parameters Estimation of Sinusoidal and Damped Sinusoidal Signals. chapter in Fourier Transform Book, In Tech. - Open Access Publisher.
  • [6] Wand, M, Sun, Y. (2004). A practical, precise method for frequency tracking and phasor estimation. IEEE Trans. Power Delivery, 19(4), 1547-1552.
  • [7] Terzija, V.V. (2003). Improved recursive Newton-type algorithms for frequency and spectra estimation in power systems. IEEE Trans. Instrum. Meas., 52(5), 1654-1659.
  • [8] Sidhu, T.T. (1999). Accurate measurement of power system frequency using a digital signal processing technique. IEEE Trans. Instrum. Meas., 48(1), 75-81.
  • [9] Arpaia, P., Cruz Serra, A., Daponte, P., Monteiro, C.L. (2001). A critical note to IEEE 1057-94 standard on hysteretic ADC dynamic testing. IEEE Trans. Instrum. Meas., 50(4), 941-948.
  • [10] Kuseljevic, M.D. (2008). A simple method for design of adaptive filters for sinusoidal signals. IEEE Trans. Instrum. Meas., 57(10), 2242-2249.
  • [11] Wu, J., Long, J., Wang, J. (2005). High-accuracy, wide-range frequency estimation methods for power system signals under nonsinusoidal conditions. IEEE Trans. Power Delivery, 20(1), 366-374.
  • [12] So, H.C., Chan, K.W., Chan, Y.T., Ho, K.C. (2005). Linear prediction approach for efficient frequency estimation of multiple real sinusoids: algorithms and analyses. IEEE Trans. Signal Process., 53(7), 2290-2305.
  • [13] Klein, J.D. (2006). Fast algorithms for single frequency estimation. IEEE Trans. Signal Process., 54(5), 1762-1770.
  • [14] El-Shafey, M.H, Mansour, M.M. (2006). Application of a new frequency estimation technique to power systems. IEEE Trans. Power Delivery, 21(3), 1045-1053.
  • [15] Trapero, J.R., Sira-Ramirez, H., Batlle, V.F. (2007). An algebraic frequency estimator for a biased and noisy sinusoidal signal. Signal Processing, 87(6), 1188-1201.
  • [16] Tan, L., Wang, L. (2011). Oversampling Technique for Obtaining Higher Order Derivative of Low-Frequency Signals. IEEE Trans. Instrum. and Meas., 60(11), 3677-3684.
  • [17] Tse, N.C.F., Lai, L.L. (2007). Wavelet-Based Algorithm for Signal Analysis. EURASIP Journal on Advances in Signal Processing.
  • [18] Schoukens, J., Rolain, Y., Simon, G., Pintelon, R. (2003). Fully Automated Spectral Analysis of Periodic Signals. IEEE Trans. Instrum. Meas., 52(4), 1021-1024.
  • [19] Hidalgo, R.M., Fernandez, J.G., Rivera, R.R., Larrondo, H.A. (1996). A Simple Adjustable Window Algorithm to Improve FFT Measurements. IEEE Trans. Instrum. Meas., 51(1), 31-36.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW1-0106-0006
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