## 7.2 Ingenieurbau

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Automated modal analysis for tracking structural change during construction and operation phases
(2019)

The automated modal analysis (AMA) technique has attracted significant interest over the last few years, because it can track variations in modal parameters and has the potential to detect structural changes. In this paper, an improved density-based spatial clustering of applications with noise (DBSCAN) is introduced to clean the abnormal poles in a stabilization diagram. Moreover, the optimal system model order is also discussed to obtain more stable poles. A numerical Simulation and a full-scale experiment of an arch bridge are carried out to validate the effectiveness of the proposed algorithm. Subsequently, the continuous dynamic monitoring system of the bridge and the proposed algorithm are implemented to track the structural changes during the construction phase. Finally, the artificial neural network (ANN) is used to remove the temperature effect on modal frequencies so that a health index can be constructed under operational conditions.

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.

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.

Measurements on the vehicle-track interaction and the excitation of railway-induced ground vibration
(2017)

Two railway measurement campaigns have been performed in Germany and Switzerland which yield insight in the vehicle-track-soil interaction. The campaign in Germany has included simultaneous measurement of vehicle, track, and soil vibrations during train runs with 16, 25, 40, 63, 80, 100, 125, 140, 160 km/h, and impulse measurements of the passenger car, three track sections and the soil. Two ballast tracks, one on the soil surface and one on a concrete bridge, have been investigated as well as a slab track in a tunnel. Ten different sites in Switzerland have been measured for soil properties and train-induced ground vibrations, which allow to determine the excitation forces of the railway traffic. New axle-box measurements at some of the Swiss sites have been analysed to get further experimental evidence. All these measurements have been evaluated to characterize the excitation processes. Relations between vehicle vibration and ground vibration can be observed. The vehicle vibrations, namely the accelerations of the wheelsets, yield the dynamic forces due to the passage over the irregularities of the vehicle and the track. The ground vibrations are correlated to these dynamic forces to a certain extent. Some mid-frequency ground vibration amplitudes, however, are higher than expected from the dynamic excitation forces. The experimental observations can be explained by an irregular response to the passage of the static loads, that means the passage of the static loads over an irregular ballast or soil. This correct understanding of the excitation processes is important for the prediction as well as for the mitigation of railway induced ground vibrations.

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.

Ground vibrations due to different technical sources are analysed in theory and experiment for the dispersion of Rayleigh waves and the admittance spectra. Both tasks are theoretically based on the same concept: The admittance function in frequencywavenumber domain yields the dispersion as its maxima, and the admittance function in space domain is obtained by integrating it over the wavenumbers. On the experimental side, many signal processing methods have been applied to many sites and have been developed by the authors in the last 35 years, i.e., time-domain methods, including the cross-correlation method, and frequency-domain methods such as the spectral analysis of surface waves with two or multiple sensors, the wavenumber-transform method, and the spatial autocorrelation method. All methods are presented by their basic formula and by at least one example site. Different sensor arrays and deterministic and stochastic sources have been tested for the spatial autocorrelation method and the wavenumber-transform method at several sites. In addition, all frequency-domain methods are presented for a specific layered site comparing their quality. The evaluated dispersion curves are very similar, but a somewhat higher frequency range has been found for the fastest method, i.e., the multi-sensor spectral-analysis-of-surface-waves method. The theoretical solutions have been used for the inversion of the measured dispersion to the soil profile of the specific layered soil. The theoretical soil model has subsequently been used to predict the ground vibration spectra of hammer and railway excitation that exhibit a good agreement with the corresponding measurements. Thus, the contribution shows the benefit of active and passive seismic methods for the prediction of railway vibration, including a new version of the spatial autocorrelation method for technical vibrations. On the other hand, technical and namely railway vibrations are considered a seismic source for the exploration of near surface soils.

The second part of these companion papers mainly researches environmental/operational influences on structural dynamic properties under normal operational conditions during two years, in order to extract a statistical based damage-sensitive indicator for health monitoring of a wind turbine system.
The correlation analyses between experimental identified frequencies, damping values as well as mode shapes and environmental/operational factors such as rotation speed of blades, wind speed, pitch angle, temperature and nacelle direction are presented. It is observed that the frequency estimates are influenced by the nacelle position, the activation of rotor, the rotation speed of blades and the wind speed as well as the temperature. Regarding to the damping estimates, they are mainly associated with variation of the aerodynamic damping due to the increasing wind speed. Besides, the resonance phenomenon is also observed in higher modes. The harmonic frequencies due to blades passing by tower are found and the corresponding damping value decreases. Moreover, the mode shapes in some modes are strongly affected by the position of the nacelle.
Subsequently, two types of simulated damage including the reduction of stiffness in both the rotor blade and the tubular tower are successfully detected by applying the Principal Component Analysis (PCA) based methods to these temperature-sensitive frequency estimates. Comparison of change of the extracted health features indicates that they are more sensitive with the tower damage.

Vibration-based structural health monitoring of a wind turbine system. Part I: Resonance phenomenon
(2015)

This paper is focused on a resonance phenomenon of a wind turbine system in 5 MW class, on the basis of dynamic signals acquired continuously from the tubular tower under normal operational conditions during two years.
Firstly, technique specifications of the wind turbine system are introduced and a finite element model is developed to characterize the structural dynamic properties. The following part describes the continuous dynamic monitoring system integrated with an automated operational modal analysis procedure using the poly-reference Least Squares Complex Frequency domain (p-LSCF) method. Subsequently, variations and mutual relationships of environmental/operational factors such as vibration amplitude, temperature, wind speed, rotation speed of blades, pitch angle and nacelle direction are also presented. Finally, significant resonance is observed due to the fundamental frequency of the tower matching with the harmonic frequency induced by the rotation of three blades. As the rotation speed of rotor approaches to 8 rpm, the vibration amplitude of the tower increases significantly and the corresponding damping value decreases. With the further rising wind velocity, the rotation speed of blades stops increasing and the input energy just contribute to accumulate the vibration amplitude of tower. Such observation indicates the Sommerfeld effect that aggravates the resonance phenomenon. A vibration control device is necessary to minimize the excessive structural responses.
A companion paper will further discuss the environmental/operational effects on dynamic properties of the wind turbine system under the operational conditions.