Research on temperature influences in long-span bridge eigenfrequencies identification

Ke Qing Fan, Yiqing Ni, Zan Ming Gao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

16 Citations (Scopus)

Abstract

Aimed at the problem that consecutive time series of eigenfrequencies identified from ambient exciting bridge structure responses are always influenced by temperature, a problem being paid much attention by bridge monitoring and health estimation applications, a research work with modeling eigenfrequency and temperatures was performed upon long term acquisitions of vibration and temperatures from the Ting Kou Bridge in Hong Kong. The research results show that eigenfrequencies vary not only followed atmospheric temperature fluctuation but also associated remarkably with the temperature distribution patterns over the structure. To eliminate temperature complications from eigenfrequency time series, an approach based on SVM nonlinear modeling algorithm was proposed in the paper. The effect of its application of 600 hours test data from Ting Kou Bridge was also described.
Original languageEnglish
Pages (from-to)67-73
Number of pages7
JournalZhongguo Gonglu Xuebao/China Journal of Highway and Transport
Volume19
Issue number2
Publication statusPublished - 1 Mar 2006

Keywords

  • Bridge engineering
  • Bridge state monitoring
  • Complex modal indicating function
  • Support vector machine
  • System identification

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation

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