<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>More and more attention has been paid to the research on bridge structure health monitoring and state analysis technology, especially the theory and technology of time series analysis based on bridge deflection information. In this paper, multi-fractal de-trend analysis (MF-DFA) is used to analysis the deflection information of bridges. The deformation characteristic parameters can be obtained by the multi-fractal de-trend fluctuation method, which can effectively identify the deformation degree of bridges. The analysis result shows that the multi-fractal de-trend fluctuation analysis method provides the theoretical basis and implementation approach for the health monitoring of the bridge.</p>
</abstract>

More and more attention has been paid to the research on bridge structure health monitoring and state analysis technology, especially the theory and technology of time series analysis based on bridge deflection information. In this paper, multi-fractal de-trend analysis (MF-DFA) is used to analysis the deflection information of bridges. The deformation characteristic parameters can be obtained by the multi-fractal de-trend fluctuation method, which can effectively identify the deformation degree of bridges. The analysis result shows that the multi-fractal de-trend fluctuation analysis method provides the theoretical basis and implementation approach for the health monitoring of the bridge.

Health status diagnosis of the bridges based on multi-fractal de-trend fluctuation analysis

State Key Laboratory of Bridge Engineering Structural Dynamics

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

More and more attention has been paid to the research on bridge structure health monitoring and state analysis technology, especially the theory and technology...

Health status diagnosis of the bridges based on multi-fractal de-trend fluctuation analysis

Online veröffentlicht: 19. Okt. 2021

Seitenbereich: 187 - 194

Eingereicht: 19. März 2021

Akzeptiert: 10. Mai 2021

DOI: https://doi.org/10.2478/amns.2021.2.00035

Schlüsselwörter
deflection signal, Multi-fractal, De-trend analysis, health monitoring of bridge

© 2023 Ling Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Health status diagnosis of the bridges based on multi-fractal de-trend fluctuation analysis

Online veröffentlicht: 19. Okt. 2021

Seitenbereich: 187 - 194

Eingereicht: 19. März 2021

Akzeptiert: 10. Mai 2021

DOI: https://doi.org/10.2478/amns.2021.2.00035

Schlüsselwörterdeflection signal, Multi-fractal, De-trend analysis, health monitoring of bridge

© 2023 Ling Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Schlüsselwörter
deflection signal, Multi-fractal, De-trend analysis, health monitoring of bridge