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Organisationseinheit der BAM
- 7.2 Ingenieurbau (63) (entfernen)
Paper des Monats
- ja (5)
Die Grundidee einer Schwingungsminderung ist es eine tiefe Eigenfrequenz der Struktur zu erreichen, so dass höhere Frequenzen abgemindert werden. Das gilt für die Minderung an der Quelle, zum Beispiel einem Eisenbahngleis, und für die Minderung am Empfänger, dem Gebäude. Die Eigenfrequenz ermittelt man aus dem Verhältnis der Auflagersteifigkeit und der Masse. Wie ist die Masse bei einem Gebäude zu wählen? Und wie ist die Untergrundsteifigkeit zu berücksichtigen? Als Referenzsituation ohne Minderungsmaßnahme? Der Beitrag bringt Rechenergebnisse zu abgefederten Gebäuden mit einfachen und komplexen (FE-) Modellen, Mess- und Rechenergebnisse zur Schwingungsübertragung von unabgefederten Gebäuden. Es wird der Einfluss der Abstimmfrequenz, der Bodensteifigkeit und der „starren“ Gebäudemasse untersucht. Die komplexen Gebäudemodelle erlauben, neben der Berechnung einer elastischen Gebäudelagerung, auch die Variation von Gebäudeparametern zur Reduktion der Deckenschwingungen. Den Ergebnissen bei der Erschütterungs-übertragung in Gebäude werden zwei ähnliche Beispiele zur elastischen Maschinenlagerung und zur elastischen Gleislagerung gegenübergestellt.
The local asymptotic approach is promising for vibration-based fault diagnosis when associated to a subspace-based residual function and efficient hypothesis testing tools. It has the ability of detecting small changes in some chosen system parameters. In the residual function,the left null space of the observability matrix associated to a reference model is confronted to the Hankel matrix of output covariances estimated from test data. When this left null space is not perfectly known from a model, it should be replaced by an estimate from data to avoid model errors in the residual computation. In this paper, the asymptotic distribution of the resulting data-driven residual is analyzed and its covariance is estimated, which includes also the covariance related to the reference null space estimate. The advantages of the data-driven residual are demonstrated in a numerical study, and the importance of including the covariance of the reference null space estimate is shown, which increases the detection Performance.
This work describes a vibration-based structural health monitoring of a prestressed-concrete box girder bridge on the A100 Highway in Berlin by applying statistical pattern recognition technique to a huge amount of data continuously collected by an integrated monitoring system during the period from 2000 to 2013. Firstly, the general condition and potential damage of the bridge is described. Then, the dynamic properties are extracted from 20 velocity sensors. Environmental variability captured by five thermal transducers and traffic intensity approximately estimated by strain measurements are also reported. Nonlinear influences of temperature on natural frequencies are observed. Subsequently, the measurements during the first year are used to build a baseline health index. The multiple linear regression (MLR) method is used to characterize the nonlinear relationship between natural frequencies and temperatures. The Euclidean distance of the residual errors is calculated to build a statistical health index. Finally, the indices extracted from the following years gradually deviate; which may indicate structural deterioration due to loss of prestress in the prestressed tendons.