Study of Singular Spectrum Analysis as a data-driven technique for damage diagnosis. Comparison between the time or frequency domain

David Garcia, Irina Trendafilova

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

Vibration-based Structural Health Monitoring methodologies have been developed in many different applications with the aim of damage diagnosis. Recently, purely data-driven methods have been gained popularity because these methods do not assume any linearity or model in their analysis. Data-driven methods use the measured vibration signals as data-input to extract features that can conclude obtain useful information for the damage diagnosis. In this work a methodology based on Singular Spectrum Analysis (SSA) technique is presented which decomposes the measured vibration responses in a certain number of principal components which reveal the rotational patterns at any frequency in the motion. One of the steps of the methodology is to create a reference state where the observations can be compared for damage assessment. The data used to create the reference state determines how the information is represented in the reference state and therefore how meaningful and informative are the feature vectors for damage assessment. This study presents of the effect of the data representation considered on the creation of the reference state when the data is introduced in the time or frequency domain. The results obtained are different depending on the signal representation and hence they should have different interpretation when the state is created based on vibratory signals represented in the time or frequency domain.

Conference

ConferenceInternational Conference on Engineering Vibration
2017 (ICoEV 2017)
CountryBulgaria
CitySofia
Period4/09/177/09/17

Fingerprint

Spectrum analysis
Structural health monitoring

Keywords

  • singular spectrum analysis (SSA)
  • data-driven techniques

Cite this

Garcia, David ; Trendafilova, Irina. / Study of Singular Spectrum Analysis as a data-driven technique for damage diagnosis. Comparison between the time or frequency domain. Paper presented at International Conference on Engineering Vibration
2017 (ICoEV 2017), Sofia, Bulgaria.6 p.
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title = "Study of Singular Spectrum Analysis as a data-driven technique for damage diagnosis. Comparison between the time or frequency domain",
abstract = "Vibration-based Structural Health Monitoring methodologies have been developed in many different applications with the aim of damage diagnosis. Recently, purely data-driven methods have been gained popularity because these methods do not assume any linearity or model in their analysis. Data-driven methods use the measured vibration signals as data-input to extract features that can conclude obtain useful information for the damage diagnosis. In this work a methodology based on Singular Spectrum Analysis (SSA) technique is presented which decomposes the measured vibration responses in a certain number of principal components which reveal the rotational patterns at any frequency in the motion. One of the steps of the methodology is to create a reference state where the observations can be compared for damage assessment. The data used to create the reference state determines how the information is represented in the reference state and therefore how meaningful and informative are the feature vectors for damage assessment. This study presents of the effect of the data representation considered on the creation of the reference state when the data is introduced in the time or frequency domain. The results obtained are different depending on the signal representation and hence they should have different interpretation when the state is created based on vibratory signals represented in the time or frequency domain.",
keywords = "singular spectrum analysis (SSA), data-driven techniques",
author = "David Garcia and Irina Trendafilova",
note = "Published in MATEC Web Conf., Volume 148, 2018, International Conference on Engineering Vibration (ICoEV 2017). Article Number 14003.; International Conference on Engineering Vibration<br/>2017 (ICoEV 2017) ; Conference date: 04-09-2017 Through 07-09-2017",
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Garcia, D & Trendafilova, I 2018, 'Study of Singular Spectrum Analysis as a data-driven technique for damage diagnosis. Comparison between the time or frequency domain' Paper presented at International Conference on Engineering Vibration
2017 (ICoEV 2017), Sofia, Bulgaria, 4/09/17 - 7/09/17, . https://doi.org/10.1051/matecconf/201814814003

Study of Singular Spectrum Analysis as a data-driven technique for damage diagnosis. Comparison between the time or frequency domain. / Garcia, David; Trendafilova, Irina.

2018. Paper presented at International Conference on Engineering Vibration
2017 (ICoEV 2017), Sofia, Bulgaria.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Study of Singular Spectrum Analysis as a data-driven technique for damage diagnosis. Comparison between the time or frequency domain

AU - Garcia, David

AU - Trendafilova, Irina

N1 - Published in MATEC Web Conf., Volume 148, 2018, International Conference on Engineering Vibration (ICoEV 2017). Article Number 14003.

PY - 2018/2/2

Y1 - 2018/2/2

N2 - Vibration-based Structural Health Monitoring methodologies have been developed in many different applications with the aim of damage diagnosis. Recently, purely data-driven methods have been gained popularity because these methods do not assume any linearity or model in their analysis. Data-driven methods use the measured vibration signals as data-input to extract features that can conclude obtain useful information for the damage diagnosis. In this work a methodology based on Singular Spectrum Analysis (SSA) technique is presented which decomposes the measured vibration responses in a certain number of principal components which reveal the rotational patterns at any frequency in the motion. One of the steps of the methodology is to create a reference state where the observations can be compared for damage assessment. The data used to create the reference state determines how the information is represented in the reference state and therefore how meaningful and informative are the feature vectors for damage assessment. This study presents of the effect of the data representation considered on the creation of the reference state when the data is introduced in the time or frequency domain. The results obtained are different depending on the signal representation and hence they should have different interpretation when the state is created based on vibratory signals represented in the time or frequency domain.

AB - Vibration-based Structural Health Monitoring methodologies have been developed in many different applications with the aim of damage diagnosis. Recently, purely data-driven methods have been gained popularity because these methods do not assume any linearity or model in their analysis. Data-driven methods use the measured vibration signals as data-input to extract features that can conclude obtain useful information for the damage diagnosis. In this work a methodology based on Singular Spectrum Analysis (SSA) technique is presented which decomposes the measured vibration responses in a certain number of principal components which reveal the rotational patterns at any frequency in the motion. One of the steps of the methodology is to create a reference state where the observations can be compared for damage assessment. The data used to create the reference state determines how the information is represented in the reference state and therefore how meaningful and informative are the feature vectors for damage assessment. This study presents of the effect of the data representation considered on the creation of the reference state when the data is introduced in the time or frequency domain. The results obtained are different depending on the signal representation and hence they should have different interpretation when the state is created based on vibratory signals represented in the time or frequency domain.

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