A novel approach for the structural identification and monitoring of a full-scale 17-storybuilding based on ambient vibration measurements

Abstract

For reliable and practical application of structural health monitoring approaches inconjunction with dense sensor arrays deployed on ‘smart’ systems, there is a need todevelop and evaluate alternate strategies for efficient problem decomposition to rapidlyand accurately determine the occurrence, location and level of small changesin the underlying structural characteristics of a monitored system based on itsvibrational signature. Furthermore, there is also a need to quantify the level ofuncertainties in the identified system characteristics so as to have a measurablelevel of confidence in the parameters to be relied on for the detection of genuinechanges (damage) in the monitored system. This study presents the results of twotime-domain identification techniques applied to a full-scale 17-story building, based onambient vibration measurements. The Factor building is a steel frame structurelocated on the UCLA campus. This building was instrumented permanently with adense array of 72-channel accelerometers, and the acceleration data are beingcontinuously recorded. The first identification method used in this study is theNExT/ERA, which is regarded as a global (or centralized) approach, since it dealswith the global dynamic properties of the structure. The second method is atime-domain identification technique for chain-like MDOF systems. Since in thismethod the identification of each link of the chain is performed independently,it is regarded as a local (or decentralized) identification methodology. For thesame reason, this method can be easily adopted for large-scale sensor networkarchitectures in which the centralized approaches are not feasible due to massivestorage, power, bandwidth and computational requirements. To have a statisticallymeaningful results, 50 days of recorded data are considered in this study. Themodal parameter and chain identification procedures are performed over timewindows of 2 h each and with 50% overlap. Using the NExT/ERA method, 12dominant modes of the building were identified. It was observed that variations in thefrequency estimation are relatively small; the coefficient of variation is about 1–2%for most of the estimated modal frequencies. Chain system identification wassuccessfully implemented using the output-only data acquired from the Factorbuilding. Probability distributions of the estimated coefficients of displacement andvelocity terms in the interstory restoring functions (which are the mass-normalizedlocal stiffness and damping values) that were found based on the chain systemidentification are presented. The variability of the estimated parameters due totemperature fluctuations is investigated. It is shown that there is a strong correlationbetween the modal frequency variations and the temperature variations in a 24 hperiod.