Automatic modal identification and variability in measured modal vectors of a cable-stayed bridge

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 for identifying 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 permanently installed on the cable-stayed Ting Kau Bridge. With the continuously identified results, variability in modal vectors due to varying environmental conditions and measurement errors is observed. Such an observation is very helpful for selection of appropriate measured modal vectors for structural health monitoring use.