Dynamic Harmonic Analysis Through Taylor–Fourier Transform

A new dynamic harmonic estimator is presented as an extension of the fast Fourier transform (FFT), which assumes a fluctuating complex envelope at each harmonic. This estimator is able to estimate harmonics that are time varying inside the observation window. The extension receives the name “Taylor-Fourier transform (TFT)” since it is based on the McLaurin series expansion of each complex envelope. Better estimates of the dynamic harmonics are obtained due to the fact that the Fourier subspace is contained in the subspace generated by the Taylor-Fourier basis. The coefficients of the TFT have a physical meaning: they represent instantaneous samples of the first derivatives of the complex envelope, with all of them calculated at once through a linear transform. The Taylor-Fourier estimator can be seen as a bank of maximally flat finite-impulse-response filters, with the frequency response of ideal differentiators about each harmonic frequency. In addition to cleaner harmonic phasor estimates under dynamic conditions, among the new estimates are the instantaneous frequency and first derivatives of each harmonic. Two examples are presented to evaluate the performance of the proposed estimator.

[1]  O. Solomon The use of DFT windows in signal-to-noise ratio and harmonic distortion computations , 1993, 1993 IEEE Instrumentation and Measurement Technology Conference.

[2]  Jelena Kovacevic,et al.  Wavelets and Subband Coding , 2013, Prentice Hall Signal Processing Series.

[3]  Valentina D. A. Corino,et al.  Improved Time--Frequency Analysis of Atrial Fibrillation Signals Using Spectral Modeling , 2008, IEEE Transactions on Biomedical Engineering.

[4]  Alfredo Paolillo,et al.  Estimation of signal parameters in the frequency domain in the presence of harmonic interference: a comparative analysis , 2006, IEEE Transactions on Instrumentation and Measurement.

[5]  A. Ferrero,et al.  High accuracy Fourier analysis based on synchronous sampling techniques , 1992, [1992] Conference Record IEEE Instrumentation and Measurement Technology Conference.

[6]  Ignacio Santamaría,et al.  Improved procedures for estimating amplitudes and phases of harmonics with application to vibration analysis , 1998, IEEE Trans. Instrum. Meas..

[7]  S. Ikuno,et al.  Axisymmetric Simulation of Inductive Measurement Method for Critical Current Density in Bulk HTS: Relation Between Third Harmonic Voltage and Coil Current , 2009, IEEE Transactions on Applied Superconductivity.

[8]  T. Kuhn The structure of scientific revolutions, 3rd ed. , 1996 .

[9]  D. Petri,et al.  Interpolation techniques for real-time multifrequency waveform analysis , 1989, 6th IEEE Conference Record., Instrumentation and Measurement Technology Conference.

[10]  J. A. de la O Serna,et al.  Dynamic phasor estimates through maximally flat differentiators , 2008, PES 2008.

[11]  John G. Proakis,et al.  Digital Communications , 1983 .

[12]  M. Omair Ahmad,et al.  Complete characterization of systems for simultaneous Lagrangian upsampling and fractional-sample delaying , 2005, IEEE Transactions on Circuits and Systems I: Regular Papers.

[13]  G. Andria,et al.  Windows and interpolation algorithms to improve electrical measurement accuracy , 1989 .

[14]  José Antonio de la O. Serna,et al.  Maximally flat differentiators through WLS Taylor decomposition , 2011, Digit. Signal Process..

[15]  Fanghua Zhang,et al.  Selective Harmonic Elimination PWM Control Scheme on a Three-Phase Four-Leg Voltage Source Inverter , 2009, IEEE Transactions on Power Electronics.

[16]  Ignacio SantamarMember Improved Procedures for Estimating Amplitudes and Phases of Harmonics with Application to Vibration Analysis , 1998 .

[17]  Alfredo Paolillo,et al.  An intelligent FFT analyzer with harmonic interference effect correction and uncertainty evaluation , 2004, IEEE Transactions on Instrumentation and Measurement.

[18]  M. Kemal Kiymik,et al.  Comparison of STFT and wavelet transform methods in determining epileptic seizure activity in EEG signals for real-time application , 2005, Comput. Biol. Medicine.

[19]  José Antonio de la O. Serna,et al.  Dynamic Phasor Estimates for Power System Oscillations , 2007, IEEE Transactions on Instrumentation and Measurement.

[20]  José Antonio de la O. Serna,et al.  Dynamic Phasor and Frequency Estimates Through Maximally Flat Differentiators , 2010, IEEE Transactions on Instrumentation and Measurement.

[21]  Dennis Gabor,et al.  Theory of communication , 1946 .

[22]  Chi-Shan Yu,et al.  A new method for power signal harmonic analysis , 2005 .

[23]  J.A. de la O On the use of amplitude shaping pulses as windows for harmonic analysis , 2000, Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference [Cat. No. 00CH37066].

[24]  Amerigo Trotta,et al.  Flat-top windows for PWM waveform processing via DFT , 1988 .

[25]  A. Papoulis Signal Analysis , 1977 .

[26]  Arun G. Phadke,et al.  Power System Relaying , 1992 .

[27]  J.J. Tomic,et al.  A New Power System Digital Harmonic Analyzer , 2007, IEEE Transactions on Power Delivery.

[28]  I. Daubechies Ten Lectures on Wavelets , 1992 .