Resonance freqnency estimation of time-series data by subspace method

Tomoko Hirao, Shuichi Adachi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper studies an estimation problem of a dominant resonance frequency from time-series data. We proposed an estimation method which incorporates system identification technique into time-series analysis. However, this method has a problem that the estimated resonance frequency is biased. In this paper, a new method which uses subspace method is proposed based on time-series data. The key idea of this method is to use an auto-covariance function of the time-series data instead of impulse response or ordinary input-output data. Hankel matrix of the time-series is constructed by the auto-covariance function. Then, subspace method is applied to the Hankel matrix, and the resonance frequency can he calculated. Effectiveness of the method is examined through numerical examples.

Original languageEnglish
Title of host publicationICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
Pages4913-4916
Number of pages4
Publication statusPublished - 2009 Dec 1
EventICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka, Japan
Duration: 2009 Aug 182009 Aug 21

Publication series

NameICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings

Other

OtherICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
CountryJapan
CityFukuoka
Period09/8/1809/8/21

Keywords

  • Resonance frequency
  • Singular value decomposition
  • Subspace method
  • Time-series data

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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  • Cite this

    Hirao, T., & Adachi, S. (2009). Resonance freqnency estimation of time-series data by subspace method. In ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings (pp. 4913-4916). [5334664] (ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings).