Analysis of windowed dynamical electrical signals through orthogonal basis and the Kalman Filter

Conference paper (2020)

Authors

E. Cortez The University of Guadalajara

F.A. Uribe The University of Guadalajara

P. Zuñiga The University of Guadalajara

Jose de Jesus Chavez Intelligent Electrical Power Grids -

Research Group

Intelligent Electrical Power Grids () (TU Delft)

Kalman filter Fourier series Correlation of signals Dynamical electrical signals Energy of signals Orthogonal vectors

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Published Date

2020

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Electrical Sustainable Energy

Research Group

Intelligent Electrical Power Grids

Abstract

An orthogonal vector analysis of windowed dynamical electrical signals with a Kalman filter tracking is proposed in this paper. Based on The Fourier Series Theory, the correlation of the signal coefficient that minimizes the error energy is obtained to extract the sinusoid component of the dynamical electrical signal. Further, The Kalman Filter is applied to track the hidden time-frequency behavior. The proposed algorithm is validated by comparing the response of The Kalman Filter estimation of the naive signal and the approximated one with the discrete Fourier transform. The results suggest that the proposed method is able to improve the Kalman response when treating with signals with non-linear dynamical properties.

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