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Automatic Identification of Bridge Vortex-Induced Vibration Using Random Decrement Method

1
Key Laboratory for Wind and Bridge Engineering of Hunan Province, College of Civil Engineering, Hunan University, Changsha 410082, China
2
Hunan Provincial Key Laboratory of Structures for Wind Resistance and Vibration Control, School of Civil Engineering, Hunan University of Science and Technology, Xiangtan 41120, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2019, 9(10), 2049; https://doi.org/10.3390/app9102049 (registering DOI)
Received: 27 February 2019 / Revised: 6 May 2019 / Accepted: 9 May 2019 / Published: 17 May 2019
(This article belongs to the Special Issue Structural Damage Detection and Health Monitoring)
PDF [2632 KB, uploaded 17 May 2019]

Abstract

Vortex-induced vibration (VIV) has been occasionally observed on a few long-span steel box-girder suspension bridges. The underlying mechanism of VIV is very complicated and reliable theoretical methods for prediction of VIV have not been established yet. Structural health monitoring (SHM) technology can provide a large amount of data for further understanding of VIV. Automatic identification of VIV events from massive, continuous long-term monitoring data is a non-trivial task. In this study, a method based on the random decrement technique (RDT) is proposed to identify the VIV response automatically from the massive acceleration response without manual intervention. The raw acceleration data is first processed by RDT and it is found that the RDT-processed data show different characteristics for the VIV response and conventional random response. A threshold based on the coefficient of variation (COV) of peak values of processed data is defined to distinguish between the two kinds of responses. Both random vibration and VIV for a three-DOF (degree-of-freedom) mass-spring-damper system are obtained by numerical simulation to verify the proposed method. The method is finally applied to the Xihoumen suspension bridge for identifying VIV response from three-month monitoring data. It is shown that the proposed method performs comparably with the method of novelty detection. A total of 60 VIV events have been successfully identified. Vortex-induced vibrations for the second to ninth vertical modes with modal frequency within 0.1~0.5 Hz occurs at wind velocity 5–18 m/s, with wind direction nearly perpendicular to bridge axis. Amplitude of VIV generally decreases with increase of wind turbulence intensity; however, noticeable VIV amplitude are still observed for turbulence intensity up to 13% in some cases.
Keywords: vortex-induced vibrations; random decrement method; long-span bridges; structural health monitoring vortex-induced vibrations; random decrement method; long-span bridges; structural health monitoring
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Huang, Z.; Li, Y.; Hua, X.; Chen , Z.; Wen, Q. Automatic Identification of Bridge Vortex-Induced Vibration Using Random Decrement Method. Appl. Sci. 2019, 9, 2049.

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