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- 7 Bauwerkssicherheit (5)
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A strain-based automated operational modal analysis algorithm is proposed to track the long-term dynamic behavior of a horizontal wind turbine under operational conditions.
This algorithm is firstly validated by a scaled wind turbine model, and then it is applied to the dynamic strain responses recorded from a 5 MW wind turbine system. We observed variations in the fundamental frequency and 1f, 3f excitation frequencies due to the mass imbalance of the blades and aerodynamic excitation by the tower dam or tower wake. Inspection of the Campbell diagram revealed that the adverse resonance phenomenon and Sommerfeld effect causing excessive vibrations of the wind tower.

This paper proposes a novel method to estimate the lateral displacement of high-rise structures under wind loads. The coefficient β(x) is firstly derived, reflecting the relation between the structural lateral dynamic displacement and the inclination angle at the height x of a structure. If the angle is small, it is the ratio between the structural fundamental mode shape and its first-order derivative without influence of external loads. Several dynamic experiments of structures are performed based on a laser remote sensing vibrometer and an inclinometer, which shows that the fundamental mode is dominated in the structural displacement response under different types of excitations. Once the coefficient β(x) is curve-fitted by measuring both the structural lateral dynamic displacement and the inclination angle synchronously, the real-time structural lateral displacement under operational conditions is estimated by multiplying the coefficient β(x) with the inclination angle. The advantage of the proposed method is that the coefficient β(x) can be identified by lateral dynamic displacement measured in high resolution by the remote sensing vibrometer, which is useful to reconstruct the displacement accurately by the inclination angle under operational conditions

The implementation of continuous dynamic monitoring systems in two bridges, in Portugal, is enabled to detect the occurrence of very significant environmental and operational effects on the modal properties of these bridges, based on automated processing of massive amounts of monitoring data collected by a set of accelerometers and thermal sensors over several years.
In order to remove or mitigate such environmental/operational effects with the purpose of damage detection, two different statistical methods have been adopted. One of them is the multiple linear regression by performing nonlinear correlation analysis between measured modal properties and environmental/operational variables. Another one is principal component regression based on the identification of the linear subspace within the modal properties without using measured values of environmental and operational variables.
This paper presents a comparison of the performance of these two alternative approaches on the basis of continuous monitoring data acquired from two instrumented bridges and simulated damage scenarios. It is observed that different methods show similar capacity in removing environmental effects, and the multiple linear regression method is slightly more sensitive to structural damage.

The Westend Bridge is located on the A100 Highway in Berlin. An integrated continuous dynamic monitoring system, composed of 20 velocity sensors, 5 temperature sensors, 3 strain gauges, 1 crack sensor and 2 inclination sensors, was implemented by the Federal Institute for Materials Research and Testing in 2000. The system runs continuously with occasional intermittence and led to a huge amount of data over a 14-year span. In this article, variations of the strain, crack and inclination measurements during the last 14 years are presented. It is noted that the observed crack and inclination of the bridge are strongly influenced by seasonal temperature variation. It further induces change in the relationship between the strains measured in both concrete and prestressed tendon. Application of k-means cluster Analysis technique in both the crack and strain measurements can partition them into different seasonal phases by identifying ‘turning points’ that indicate annual periodical bridge change. In the period of these two ‘turning points’, a strong linear relation of the strains in two materials is observed. In the rest of the year, a nonlinear relationship between the strains recorded in both the concrete and the prestressed tendon is noted. The possible reason is the additional thermal load due to the change in temperature difference between the bridge’s surface and soffit. Finally, a health index in a Framework of regression model and process control theory is proposed by investigating the linear relationship between the strains in concrete and prestressed tendon. The tendency of the health index in the 14 years may suggest the long-term bridge change during that time frame.

This paper addresses operational modal analysis (OMA) and continuous dynamic monitoring (CDM) of two bridges. One of them is installed with Tuned Mass Dampers (TMDs) while another one is a normal bridge. Two ambient vibration tests were performed on these two bridges respectively. It is observed that not only installation of TMDs but also environmental factors influence the variations of structural frequencies, which may mask the subtle change induced by small structural changes. As a result, continuous dynamic monitoring systems were implemented on these two bridges, in order to evaluate efficiency of the TMD system, remove the environmental effects and build reliable damage indices that are only sensitive to structural changes. The results of CDM of these two bridges during several years are presented. Software systems developed for OMA and CDM are also introduced.