Abstract
The State Representation Methodology (SRM) combined with the Frequency Slice Wavelet Transform (FSWT), which is a new time–frequency analysis tool, is proposed for assessing the condition of bridges on the basis of bridge monitoring data. First, this paper presents an overall description of the SRM method via FSWT analysis. It then shows, through numerical simulations, some novel characteristics and advantages of FSWT analysis in contrast to the conventional wavelet approach and the feature extraction accuracy of SRM analysis for the detection of bridge damage on the basis of monitoring data. The principal results obtained through this study can be summarized as follows: (1) details of a newly proposed SRM and its application to bridge condition assessment based on bridge monitoring data are introduced. The proposed SRM combined with the FSWT is validated as a novel time–frequency analysis tool for assessing bridge condition on the basis of bridge monitoring data. (2) New properties of FSWT analysis are demonstrated, and advantages in contrast to the traditional wavelet method are highlighted. Feature extraction in SRM analysis is precise for damage detection in a bridge system on the basis of monitoring data and using numerical simulations.
Highlights
Various structural health monitoring (SHM) approaches have been proposed with the aim of facilitating the maintenance of existing bridges, and many examples of such systems have been reported [1]
We discuss the charac‐ teristics of the State Representation Methodology (SRM) and Frequency Slice Wavelet Transform (FSWT) as performed by following the procedures shown in Fig. 2 and considering operational conditions associated with scale parameters and other factors affecting damage detection accuracy
Focusing on SRM, which is a newly developed method for rationally evaluating the present state of a structural system by analyzing a large amount of measure‐ ment data obtained continuously from a network of SHM system sensors and extracting useful information, this study evaluates the characteristics of SRM using bridge model girders
Summary
Various structural health monitoring (SHM) approaches have been proposed with the aim of facilitating the maintenance of existing bridges, and many examples of such systems have been reported [1]. The accu‐ mulation, over a long period, of measurement data related to the bridge of interest is of particular importance Such data include environmental conditions, such as temperature and humidity, as well as physical quantities directly related to structural characteristics, such as vibration, strain and displacement characteristics. These data are used for estimating the present health status and future deterioration (damage) of the bridge [2,3,4,5,6,7,8]. We discuss the charac‐ teristics of the SRM and FSWT as performed by following the procedures shown in Fig. 2 and considering operational conditions associated with scale parameters and other factors affecting damage detection accuracy
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