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

Y. Q. Ni; K. Q. Fan; G. Zheng; T. H. T. Chan; J. M. Ko

doi:10.1117/12.482379

18 August 2003 Automatic modal identification of cable-supported bridges instrumented with a long-term monitoring system

Y. Q. Ni, K. Q. Fan, G. Zheng, T. H. T. Chan, J. M. Ko

Author Affiliations +

Proceedings Volume 5057, Smart Structures and Materials 2003: Smart Systems and Nondestructive Evaluation for Civil Infrastructures; (2003) https://doi.org/10.1117/12.482379
Event: Smart Structures and Materials, 2003, San Diego, California, United States

Abstract

An automatic modal identification program is developed for continuous extraction of modal parameters of three cable-supported 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 measurements 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 cable-stayed 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.

Citation Download Citation

Y. Q. Ni, K. Q. Fan, G. Zheng, T. H. T. Chan, and J. M. Ko "Automatic modal identification of cable-supported bridges instrumented with a long-term monitoring system", Proc. SPIE 5057, Smart Structures and Materials 2003: Smart Systems and Nondestructive Evaluation for Civil Infrastructures, (18 August 2003); https://doi.org/10.1117/12.482379

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available