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The practice of long-term monitoring of structural vibrations increases its feasibility with affordability of sensors and applications of operational modal analysis (OMA) in civil engineering structures. In the context of vibration based structural health monitoring (VBSHM) of bridges, modal characteristic of structure is commonly considered as features correlated with changes on structural condition resulting from several reasons like age degradation or damages in structures. Modal characteristics are also sensitive to environmental variation like temperature, wind and humidity that can vary significantly even in single day. Such changes in modal characteristic can mask changes due to varying structural condition and can lead to misunderstanding the state of structure. This paper investigated the elimination of environmental effects from natural frequencies identified from an existing single span prestressed concrete bridge from long term vibration measurements in two different years (2016–2017) and (2021–2022), using gaussian process (GP) regression. A normalized distance which is sensitive to structural changes in bridge was developed to compare the two states of bridge with a time gap of five years. The effectiveness of proposed technique in detecting structural changes due to age degradation after removal of environmental variation was discussed.

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An Investigation of the Effect of Age Degradation on Natural Frequency of Single Span Prestressed Concrete Bridge Under Environmental Variation Using Gaussian Process Regression

  • 会议论文

  • 发表日期：

    2025年

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  • Haseeb Ahmad,
  • Yasunao Matsumoto

摘要

The practice of long-term monitoring of structural vibrations increases its feasibility with affordability of sensors and applications of operational modal analysis (OMA) in civil engineering structures. In the context of vibration based structural health monitoring (VBSHM) of bridges, modal characteristic of structure is commonly considered as features correlated with changes on structural condition resulting from several reasons like age degradation or damages in structures. Modal characteristics are also sensitive to environmental variation like temperature, wind and humidity that can vary significantly even in single day. Such changes in modal characteristic can mask changes due to varying structural condition and can lead to misunderstanding the state of structure. This paper investigated the elimination of environmental effects from natural frequencies identified from an existing single span prestressed concrete bridge from long term vibration measurements in two different years (2016–2017) and (2021–2022), using gaussian process (GP) regression. A normalized distance which is sensitive to structural changes in bridge was developed to compare the two states of bridge with a time gap of five years. The effectiveness of proposed technique in detecting structural changes due to age degradation after removal of environmental variation was discussed.