Optimal GPS/accelerometer integration algorithm for monitoring the vertical structural dynamics

Meng, Xiaolin and Wang, Jian and Han, Houzeng (2014) Optimal GPS/accelerometer integration algorithm for monitoring the vertical structural dynamics. Journal of Applied Geodesy, 8 (4). pp. 265-272. ISSN 1862-9024

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The vertical structural dynamics is a crucial factor for structural health monitoring (SHM) of civil structures such as high-rise buildings, suspension bridges and towers. This paper presents an optimal GPS/accelerometer integration algorithm for an automated multi-sensor monitoring system. The closed loop feedback algorithm for integrating the vertical GPS and accelerometer measurements is proposed based on a 5 state extended KALMAN filter (EKF) and then the narrow moving window Fast Fourier Transform (FFT) analysis is applied to extract structural dynamics. A civil structural vibration is simulated and the analysed result shows the proposed algorithm can effectively integrate the online vertical measurements produced by GPS and accelerometer. Furthermore, the accelerometer bias and scale factor can also be estimated which is impossible with traditional integration algorithms. Further analysis shows the vibration frequencies detected in GPS or accelerometer are all included in the integrated vertical defection time series and the accelerometer can effectively compensate the short-term GPS outages with high quality. Finally, the data set collected with a time synchronised and integrated GPS/accelerometer monitoring system installed on the Nottingham Wilford Bridge when excited by 15 people jumping together at its mid-span are utilised to verify the effectiveness of this proposed algorithm. Its implementations are satisfactory and the detected vibration frequencies are 1.720 Hz, 1.870 Hz, 2.104 Hz, 2.905 Hz and also 10.050 Hz, which is not found in GPS or accelerometer only measurements.

Item Type: Article
Keywords: Global Positioning System (GPS); accelerometer; integration; vibration; extended Kalman filter; dynamic defection monitoring
Schools/Departments: University of Nottingham UK Campus > Faculty of Engineering > Department of Civil Engineering
Identification Number: https://doi.org/10.1515/jag-2014-0024
Depositing User: Meng, Xiaolin
Date Deposited: 25 Jul 2016 11:07
Last Modified: 13 Sep 2016 18:20
URI: http://eprints.nottingham.ac.uk/id/eprint/35388

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