A spectral estimation case study in frequency-domain by subspace methods

Author

Akcay, Huseyin ; Turkay, Semiha

Author_Institution

Dept. of Electr. & Electron. Eng., Anadolu Univ., Eskisehir, Turkey

fYear

2013

fDate

17-19 July 2013

Firstpage

2404

Lastpage

2409

Abstract

In this paper, the properties of two recently proposed frequency-domain subspace-based algorithms to estimate discrete-time cross-power spectral density (cross-PSD) and auto-power spectral density (auto-PSD) matrices of vector auto-regressive moving-average and moving-average (ARMAMA) models from sampled values of the Welch cross-PSD and auto-PSD estimators on uniform grids of frequencies, are illustrated by numerical and real-life application examples. The latter is concerned with the modeling of acoustic spectra for detecting faults in induction motors.

Keywords

autoregressive moving average processes; discrete time systems; fault diagnosis; induction motors; machine control; matrix algebra; ARMAMA models; Welch cross-PSD; acoustic spectra; auto-PSD estimators; auto-PSD matrices; auto-power spectral density; cross-PSD matrices; discrete-time cross-power spectral density; fault detection; frequency-domain subspace-based algorithms; induction motors; spectral estimation case study; vector auto-regressive moving-average and moving-average models; Arrays; Computational modeling; Estimation; Frequency estimation; Induction motors; Numerical models; Permanent magnet motors; Welch estimator; acoustic spectra; dynamic factor model; power spectrum; subspace identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (ECC), 2013 European

Conference_Location

Zurich

Type

conf

Filename

6669114