Bias Errors due to Leakage Effects When Estimating Frequency Response Functions

Frequency response functions are often utilized to characterize a system's dynamic response. For a wide range of engineering applications, it is desirable to determine frequency response functions for a system under stochastic excitation. In practice, the measurement data is contaminated by noi...

Full description

Bibliographic Details
Main Authors: Andreas Josefsson, Kjell Ahlin, Göran Broman
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.3233/SAV-2012-0668
id doaj-ac227657256c43f0843d7fe21fd24ee5
record_format Article
spelling doaj-ac227657256c43f0843d7fe21fd24ee52020-11-24T22:25:50ZengHindawi LimitedShock and Vibration1070-96221875-92032012-01-011961257126610.3233/SAV-2012-0668Bias Errors due to Leakage Effects When Estimating Frequency Response FunctionsAndreas Josefsson0Kjell Ahlin1Göran Broman2School of Engineering, Blekinge Institute of Technology, Karlskrona, SwedenSchool of Engineering, Blekinge Institute of Technology, Karlskrona, SwedenSchool of Engineering, Blekinge Institute of Technology, Karlskrona, SwedenFrequency response functions are often utilized to characterize a system's dynamic response. For a wide range of engineering applications, it is desirable to determine frequency response functions for a system under stochastic excitation. In practice, the measurement data is contaminated by noise and some form of averaging is needed in order to obtain a consistent estimator. With Welch's method, the discrete Fourier transform is used and the data is segmented into smaller blocks so that averaging can be performed when estimating the spectrum. However, this segmentation introduces leakage effects. As a result, the estimated frequency response function suffers from both systematic (bias) and random errors due to leakage. In this paper the bias error in the H1 and H2-estimate is studied and a new method is proposed to derive an approximate expression for the relative bias error at the resonance frequency with different window functions. The method is based on using a sum of real exponentials to describe the window's deterministic autocorrelation function. Simple expressions are derived for a rectangular window and a Hanning window. The theoretical expressions are verified with numerical simulations and a very good agreement is found between the results from the proposed bias expressions and the empirical results.http://dx.doi.org/10.3233/SAV-2012-0668
collection DOAJ
language English
format Article
sources DOAJ
author Andreas Josefsson
Kjell Ahlin
Göran Broman
spellingShingle Andreas Josefsson
Kjell Ahlin
Göran Broman
Bias Errors due to Leakage Effects When Estimating Frequency Response Functions
Shock and Vibration
author_facet Andreas Josefsson
Kjell Ahlin
Göran Broman
author_sort Andreas Josefsson
title Bias Errors due to Leakage Effects When Estimating Frequency Response Functions
title_short Bias Errors due to Leakage Effects When Estimating Frequency Response Functions
title_full Bias Errors due to Leakage Effects When Estimating Frequency Response Functions
title_fullStr Bias Errors due to Leakage Effects When Estimating Frequency Response Functions
title_full_unstemmed Bias Errors due to Leakage Effects When Estimating Frequency Response Functions
title_sort bias errors due to leakage effects when estimating frequency response functions
publisher Hindawi Limited
series Shock and Vibration
issn 1070-9622
1875-9203
publishDate 2012-01-01
description Frequency response functions are often utilized to characterize a system's dynamic response. For a wide range of engineering applications, it is desirable to determine frequency response functions for a system under stochastic excitation. In practice, the measurement data is contaminated by noise and some form of averaging is needed in order to obtain a consistent estimator. With Welch's method, the discrete Fourier transform is used and the data is segmented into smaller blocks so that averaging can be performed when estimating the spectrum. However, this segmentation introduces leakage effects. As a result, the estimated frequency response function suffers from both systematic (bias) and random errors due to leakage. In this paper the bias error in the H1 and H2-estimate is studied and a new method is proposed to derive an approximate expression for the relative bias error at the resonance frequency with different window functions. The method is based on using a sum of real exponentials to describe the window's deterministic autocorrelation function. Simple expressions are derived for a rectangular window and a Hanning window. The theoretical expressions are verified with numerical simulations and a very good agreement is found between the results from the proposed bias expressions and the empirical results.
url http://dx.doi.org/10.3233/SAV-2012-0668
work_keys_str_mv AT andreasjosefsson biaserrorsduetoleakageeffectswhenestimatingfrequencyresponsefunctions
AT kjellahlin biaserrorsduetoleakageeffectswhenestimatingfrequencyresponsefunctions
AT goranbroman biaserrorsduetoleakageeffectswhenestimatingfrequencyresponsefunctions
_version_ 1725756066042478592