Structural Health Monitoring of a 54-Story Steel-Frame Building Using a Wave Method and Earthquake Records

Abstract

The variations of identified wave velocities of vertically propagating waves through the structure are investigated for a 54-story steel-frame building in downtown Los Angeles, California, over a period of 19 years since construction (1992–2010), using records of six earthquakes. The set includes all significant earthquakes that shook this building, which produced maximum transient drift ∼0.3% and caused no reported damage. Wave velocity profiles β( z) are identified for the NS, EW, and torsional responses by fitting layered shear beam/torsional shaft models in the recorded responses, by waveform inversion of pulses in impulse response functions. The results suggest variations larger than the estimation error, with a coefficient of variation about 2–4.4%. About 10% permanent reduction of the building stiffness is detected, caused mainly by the Landers and Big Bear earthquake sequence of 28 June 1992, and the Northridge earthquake of 17 January 1994. Permanent changes of comparable magnitude were identified also in the first two apparent modal frequencies, f1; app, and f2; app, which were identified from the peaks of the transfer-function amplitudes.

Detection thresholds in structural health monitoring

“…Those estimates appear to be robust and are realistic for all buildings for which such 1-D modeling is possible, and where earthquake damage has been documented and can be used to verify the modeling assumptions. However, more-detailed building models can and do provide more accurate estimates of changes in f 1 [90,94,75,76,[77][78][79]28,29]. Buildings with large plan dimensions relative to their height will require two-and occasionally threedimensional models, preferably with anisotropic properties.…”

Time‐wave velocity analysis for early earthquake damage detection in buildings: application to a damaged full‐scale RC building

“…The velocities are identified by an interferometric algorithm, which involves least squares fit of pulses in impulse response functions. As far as accuracy is concerned, with the recently introduced waveform inversion fitting algorithm, it was shown on an example that the method (iv) is accurate enough to detect permanent change in the overall stiffness of a tall steel building that has shown no signs of damage [27]. The algorithm is applied to a 12-story RC building in Los Angeles, lightly damaged by the San Fernando 1971 earthquake.…”

“…The difference is interpreted to be due to softening of the soil-foundation system, to which the identified frequency of vibration is sensitive. [25,27].The wave method for structural system identification and health monitoring in this paper belongs to the class of interferometric wave imaging problems, which have application in many disciplines, such as geosciences, oceanography, atmospheric science, and nondestructive testing of tissues and other materials, across a wide range of scales [41].This paper is organized as follows. internal inhomogeneities [1,8,10,[18][19][20][21][22].…”

“…The higher modes are less sensitive to the SSI effects but less certain to estimate during an earthquake [16], as it will be seen later in this paper. [25,27]. However, no comparative analysis using the same benchmark data is available at this time to make a meaningful comparison.…”

Parametric Estimation of Wave Dispersion for System Identification of Building Structures

“…The velocity of shear waves, which are induced by seismic base excitation and propagating along the building height, can be estimated from the impulse response functions (IRFs) of the building structure, e.g., [1][2][3][4][5][6] to name only a few. Considering that the shear wave velocity is related to the lateral stiffness of the building structure, several studies have been able to detect structural damage in terms of loss of effective lateral stiffness by comparing estimated shear wave velocities from the pre-and post-damage IRFs (e.g., [7][8][9]). …”