Analysis of the dynamic response of a long span bridge using GPS/accelerometer/anemometer under typhoon loading. (1st September 2016)

• Record Type: Journal Article
• Authors: Han, Houzeng; Wang, Jian; Meng, Xiaolin; Liu, Hua
• Is Part Of: Engineering structures. Volume 122(2016:Sep. 01)
• Page Start: 238
• Page End: 250
• Publication Date: 2016-09-01
• Subjects: GPS -- Accelerometer -- Anemometer -- Wind loadings -- Bridge monitoring -- Displacement reconstruction -- Vondrak filter -- Recursive least squares (RLS) filter; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2016.04.041
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: A novel GPS/accelerometer/anemometer integration algorithm is developed. A Vondrak filter is utilized to de-noise raw signal and isolate low-frequency noise. A least-squares based displacement reconstruction scheme is employed. An adaptive RLS filter is adopted to separate the slow-varying movements. Abstract: Large flexible engineering structures, such as long span bridges or tall buildings, are susceptible to quasi-static and dynamic deformations caused by different loadings, thus accurate displacement measurements are desirable to assess the integrity and reliability of the structure. In this study, an integrated system that includes Global Positioning System (GPS), accelerometer and anemometer was developed to obtain the responses of a long span bridge to the extreme wind loadings. Spectral analysis based on the Fast Fourier Transform (FFT) algorithm was first carried out to detect the dominant frequencies of the middle pylon. Then the noisy GPS displacement measurements and accelerometer data are de-noised using the Vondrak filter, and the low frequency disturbance was separated from GPS displacement time series. A least-squares based displacement reconstruction scheme using noise-mitigated accelerations was employed, and the Tikhonov regularization scheme with optimal selected regularization factor was used to alleviate the ill-posedness. At last, an adaptive recursive least squares (RLS) filter was adopted to separate the slow-varying movements, and the total displacement with enhanced measurement accuracy was obtained from the combined quasi-static and high-frequency dynamic displacements. A field monitoring data set collected on the Erqi Yangtze River Bridge, a three-tower cable-stayed bridge located in Wuhan, China, was used to validate the effectiveness of the proposed integration processing scheme. The GPS/accelerometer/anemometer installed on the center supporting tower was used to characterize the interaction between the responses and the ambient wind loadings. The results demonstrate the proposed technique can significantly improve the measurement accuracy of pylon displacement under strong winds. The deformation accuracy with the amplitude of several millimeters can be successfully detected, and the spectrum of the pylon response obtained from both GPS data and accelerometer data reveals the identified first dominant frequency of the middle pylon is 0.172 Hz.