Automatic modal identification of cable-supported bridges instrumented with a long-term monitoring system | Zendy

YiQing Ni | Zendy; Ke Fan | Zendy; Gang Zheng | Zendy; Tommy H.T. Chan | Zendy; J.M. Ko | Zendy

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Automatic modal identification of cable-supported bridges instrumented with a long-term monitoring system

Author(s) -

YiQing Ni,

Ke Fan,

Gang Zheng,

Tommy H.T. Chan,

J.M. Ko

Publication year - 2003

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.482379

Subject(s) - modal , structural health monitoring , software , bridge (graph theory) , accelerometer , modal analysis , modal testing , computer science , identification (biology) , operational modal analysis , vibration , term (time) , continuous monitoring , engineering , structural engineering , acoustics , finite element method , programming language , operating system , medicine , chemistry , botany , physics , operations management , polymer chemistry , biology , quantum mechanics

An automatic modal identification program is developed for continuous extraction of modal parameters of three cablesupported bridges in Hong Kong which are instrumented with a long-term monitoring system. The program employs the Complex Modal Indication Function (CMIF) algorithm to identify modal properties from continuous ambient vibration\udmeasurements in an on-line manner. By using the LabVIEW graphical programming language, the software realizes the algorithm in Virtual Instrument (VI) style. The applicability and implementation issues of the developed software are demonstrated by using one-year measurement data acquired from 67 channels of accelerometers deployed on the cablestayed Ting Kau Bridge. With the continuously identified results, normal variability of modal vectors caused by varying environmental and operational conditions is observed. Such observation is very helpful for selection of appropriate measured modal vectors for structural health monitoring applications

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