Loughborough University
Browse
- No file added yet -

GNSS-aided accelerometer frequency domain integration approach to monitor structural dynamic displacements

Download (1.33 MB)
journal contribution
posted on 2021-11-18, 11:39 authored by Xu Liu, Jian Wang, Jie Zhen, Houzeng Han, Craig HancockCraig Hancock
The accelerometer frequency domain integration approach (FDIA) is being actively applied to calculate dynamic displacement responses of large engineering structures. However, it is a relative acceleration measurement as the initial position is unavailable. GNSS offers direct displacement measurements, but has the limitation of relatively low frequency of data compared with alternative measurement techniques. Therefore, this paper proposes an improved FDIA utilising the advantages of GNSS to gain accurate information about the initial position. The performance of the proposed approach is first validated through software simulation. Following the validation, a series of shaking table tests using various vibration frequencies (0.5 HZ, 1 HZ, 1.5 HZ, 2 HZ and 2.5 HZ) are performed at the south square of Beijing University of Civil Engineering and Architecture (BUCEA) using one GNSS receiver and one accelerometer. The results show that the proposed approach can effectively avoid the uncertainty of the initial value and thus enhance the direct measurement accuracy of the dynamic displacements of structures, with root mean square error (RMSE) decreasing from 11.4 mm to 6.8 mm.

Funding

National Natural Science Foundation of China [41874029]

National Key Research and Development Program of China [2016YFC0803103,2020YFD1100201]

History

School

  • Architecture, Building and Civil Engineering

Published in

International Journal of Image and Data Fusion

Volume

12

Issue

4

Pages

268 - 281

Publisher

Taylor & Francis

Version

  • AM (Accepted Manuscript)

Rights holder

© Taylor and Francis

Publisher statement

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Image and Data Fusion on 29 Aug 2021, available online: https://doi.org/10.1080/19479832.2021.1967468

Acceptance date

2021-08-09

Publication date

2021-08-29

Copyright date

2021

ISSN

1947-9824

eISSN

1947-9824

Language

  • en

Depositor

Dr Craig Hancock . Deposit date: 17 November 2021

Usage metrics

    Loughborough Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC