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author:

Yu, Y. (Yu, Y..) [1] | Zong, Z. (Zong, Z..) [2] | Chen, B. (Chen, B..) [3] | Xia, Z. (Xia, Z..) [4]

Indexed by:

Scopus PKU CSCD

Abstract:

Aimed at the problem that the modal frequency of large span continuous pre-stressed rigid frame bridge is always influenced by environmental temperature, a statistical analysis with modal frequency and temperature is performed on the Xiabaishi bridge's health monitoring data. The ternary linear regression model between the environmental temperature and the modal frequency of this bridge is proposed, which has been verified to show a relatively high precision in fitting and prediction. And it can be used to predict and evaluate modal frequency data in the future. Furthermore, the temperature correctional model about modal frequency of Xiabaishi continuous rigid-framed bridge is presented. The model can effectively eliminate the effect of environmental temperature on the modal frequency, and make the frequency tend to be stabilized. It can provide temperature correction modal frequency data for the bridge health monitoring analyses, such as safety and durability evaluation, damage detection, updated finite element model, etc.

Keyword:

Bridge health monitoring; Continuous rigid-frame bridge; Environmental temperature; Mathematical statistics; Modal frequency

Community:

  • [ 1 ] [Yu, Y.]College of Civil Engineering, Fuzhou University, Fuzhou, 350108, China
  • [ 2 ] [Zong, Z.]School of Civil Engineering, Southeast University, Nanjing, 210096, China
  • [ 3 ] [Chen, B.]College of Civil Engineering, Fuzhou University, Fuzhou, 350108, China
  • [ 4 ] [Xia, Z.]College of Civil Engineering, Fuzhou University, Fuzhou, 350108, China

Reprint 's Address:

  • [Yu, Y.]College of Civil Engineering, Fuzhou University, Fuzhou, 350108, China

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Source :

Journal of Vibration, Measurement and Diagnosis

ISSN: 1004-6801

Year: 2014

Issue: 1

Volume: 34

Page: 69-76

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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