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Computing Serviceability Vibration Predictors for an In Service Footbridge

 Computing Serviceability Vibration Predictors for an In Service Footbridge
Author(s):



Medium: conference paper
Language(s): English
Conference: Footbridge 2017 Berlin - Tell A Story, 6-8.9.2017, Technische Universität Berlin (TU Berlin)
Published in:
Year: 2017
DOI: 10.24904/footbridge2017.09694
Abstract:

In order to analyse the in-service response of a footbridge, several vibration predictors may be computed, such as peak acceleration, running Root Mean Square acceleration, Maximum Transient Vibration Value, Response Factors and Crest Factors. These predictors have been derived from controlled and uncontrolled tests on Veterinary Faculty Footbridge, sited in Madrid, using frequency weighted and unweighted raw data.

Prior to the in-service serviceability assessment, the structure has been analysed, firstly, using an FFT-mobile application (by obtaining the frequency spectrum as a first approach to natural frequency estimation), and secondly, from operational data (by applying operational modal analysis techniques) and free vibration response tests. In-service vibration analysis has been carried out employing only 2 sensors, placed on the structure according to modal shapes, weighted by means of frequency-dependent functions accounting for input frequency properties (dynamic loading factors of human loading) and output frequency perception (taken from ISO 2631-1). The vibration serviceability has been assessed and discussed from all the predictors, extracting conclusions about their convenience.

Keywords:
vibration serviceability assessment operational modal analysis vibration predictors sensor placement
License:

This creative work is copyrighted. The copyright holder(s) do(es) not grant any usage rights other than viewing and downloading the work for personal use. Further copying or publication requires the permission of the copyright holder(s).

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  • About this
    data sheet
  • Reference-ID
    10075339
  • Published on:
    01/09/2017
  • Last updated on:
    10/06/2021
 
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