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Zivanovic, Miroslav

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https://academica-e.unavarra.es/handle/2454/50204

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Zivanovic

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Miroslav

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Ingeniería Eléctrica, Electrónica y de Comunicación

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ISC. Institute of Smart Cities

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0000-0001-8729-6657

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1948

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Author: Carlosena García, Alfonso ×

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Now showing 1 - 3 of 3
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    PublicationOpen Access
    Unified analysis of glottal source spectrum
    (ISCA, 2003) Arroabarren Alemán, Ixone; Zivanovic, Miroslav; Carlosena García, Alfonso; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
    The spectral study of the glottal excitation has traditionally been based on a single time-domain mathematical model of the signal, and the spectral dependence on its time domain parameters. Opposite to this approach, in this work the two most widely used time domain models have been studied jointly, namely the KLGLOTT88 and the LF models. Their spectra are analyzed in terms of their dependence on the general glottal source parameters: Open quotient, asymmetry coefficient and spectral tilt. As a result, it has been proved that even though the mathematical expressions for both models are quite different, they can be made to converge. The main difference found is that in the KLGLOTT88 model the asymmetry coefficient is not independent of the open quotient and the spectral tilt. Once this relationship has been identified and translated to LF model, both models are shown to be equivalent in both time and frequency domains.
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    PublicationOpen Access
    Two methods for nonparametric spectrum peak discrimination
    (2002) Zivanovic, Miroslav; Carlosena García, Alfonso; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
    The conventional DFT-oriented nonparametric interpolation methods, based on time windowing and the DTFT envelope curve resampling (zero padding, Chirp-z [1], frequency scale distortion [2], etc.), can improve the spectrum computational resolution. Two methods proposed herein involve some modification of the frequency domain representation and apparently improve the spectrum physical resolution.
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    PublicationOpen Access
    Instantaneous amplitude and phase signal modeling for harmonic removal in wind turbines
    (Elsevier, 2023) Zivanovic, Miroslav; Plaza Puértolas, Aitor; Iriarte Goñi, Xabier; Carlosena García, Alfonso; Ingeniería; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Ingeniaritza; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Gobierno de Navarra / Nafarroako Gobernua, 0011-1365-2021-000159.
    We present a novel approach to harmonic disturbance removal in single-channel wind turbine acceleration data by means of time-variant signal modeling. Harmonics are conceived as a set of quasi-stationary sinusoids whose instantaneous amplitude and phase vary slowly and continuously in a short-time analysis frame. These non-stationarities in the harmonics are modeled by low-degree time polynomials whose coefficients capture the instantaneous dynamics of the corresponding waveforms. The model is linear-in-parameters and is straightforwardly estimated by the linear least-squares algorithm. Estimates from contiguous analysis frames are further combined in the overlap-add fashion in order to yield overall harmonic disturbance waveform and its removal from the data. The algorithm performance analysis, in terms of input parameter sensitivity and comparison against three state-of-the-art methods, has been carried out with synthetic signals. Further model validation has been accomplished through real-world signals and stabilization diagrams, which are a standard tool for determining modal parameters in many time-domain modal identification algorithms. The results show that the proposed method exhibits a robust performance particularly when only the average rotational speed is known, as is often the case for stand-alone sensors which typically carry out data pre-processing for structural health monitoring. Moreover, for real-world analysis scenarios, we show that the proposed method delivers consistent vibration mode parameter estimates, which can straightforwardly be used for structural health monitoring.