Structural Health Monitoring under Nonlinear Environmental or Operational Influences

Vibration-based structural health monitoring is based on detecting changes in the dynamic characteristics of the structure. It is well known that environmental or operational variations can also have an influence on the vibration properties. If these effects are not taken into account, they can resu...

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Main Author: Jyrki Kullaa
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2014/863494
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author Jyrki Kullaa
author_facet Jyrki Kullaa
author_sort Jyrki Kullaa
collection DOAJ
description Vibration-based structural health monitoring is based on detecting changes in the dynamic characteristics of the structure. It is well known that environmental or operational variations can also have an influence on the vibration properties. If these effects are not taken into account, they can result in false indications of damage. If the environmental or operational variations cause nonlinear effects, they can be compensated using a Gaussian mixture model (GMM) without the measurement of the underlying variables. The number of Gaussian components can also be estimated. For the local linear components, minimum mean square error (MMSE) estimation is applied to eliminate the environmental or operational influences. Damage is detected from the residuals after applying principal component analysis (PCA). Control charts are used for novelty detection. The proposed approach is validated using simulated data and the identified lowest natural frequencies of the Z24 Bridge under temperature variation. Nonlinear models are most effective if the data dimensionality is low. On the other hand, linear models often outperform nonlinear models for high-dimensional data.
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series Shock and Vibration
spelling doaj-art-026a3bc84f6e4f9ba611cc7f484e337d2025-08-20T03:55:32ZengWileyShock and Vibration1070-96221875-92032014-01-01201410.1155/2014/863494863494Structural Health Monitoring under Nonlinear Environmental or Operational InfluencesJyrki Kullaa0Department of Applied Mechanics, Aalto University, P.O. Box 14300, 00076 Espoo, FinlandVibration-based structural health monitoring is based on detecting changes in the dynamic characteristics of the structure. It is well known that environmental or operational variations can also have an influence on the vibration properties. If these effects are not taken into account, they can result in false indications of damage. If the environmental or operational variations cause nonlinear effects, they can be compensated using a Gaussian mixture model (GMM) without the measurement of the underlying variables. The number of Gaussian components can also be estimated. For the local linear components, minimum mean square error (MMSE) estimation is applied to eliminate the environmental or operational influences. Damage is detected from the residuals after applying principal component analysis (PCA). Control charts are used for novelty detection. The proposed approach is validated using simulated data and the identified lowest natural frequencies of the Z24 Bridge under temperature variation. Nonlinear models are most effective if the data dimensionality is low. On the other hand, linear models often outperform nonlinear models for high-dimensional data.http://dx.doi.org/10.1155/2014/863494
spellingShingle Jyrki Kullaa
Structural Health Monitoring under Nonlinear Environmental or Operational Influences
Shock and Vibration
title Structural Health Monitoring under Nonlinear Environmental or Operational Influences
title_full Structural Health Monitoring under Nonlinear Environmental or Operational Influences
title_fullStr Structural Health Monitoring under Nonlinear Environmental or Operational Influences
title_full_unstemmed Structural Health Monitoring under Nonlinear Environmental or Operational Influences
title_short Structural Health Monitoring under Nonlinear Environmental or Operational Influences
title_sort structural health monitoring under nonlinear environmental or operational influences
url http://dx.doi.org/10.1155/2014/863494
work_keys_str_mv AT jyrkikullaa structuralhealthmonitoringundernonlinearenvironmentaloroperationalinfluences