Monitoring and diagnosis of civil structures has become a popular topic in the last years, especially through the use of non-invasive tests and techniques. Moreover, the spread of operational modal analysis, that exploit ambient excitations of structures to estimate their modal parameters, allowed to reduce the costs associated to the dynamic identification. In this paper, a technique for the diagnosis of common civil structures, such as residential buildings or warehouses, is presented in order to identify local stiffness decreases that can potentially be associated to structural failures. The technique has been tested on a real warehouse built in 1960 and the results have been analyzed demonstrating the effectiveness of the methodology.
Several examples of control strategies for the seismic protection of civil structures, ranging from passive to active and semi-active have been presented in the scientific literature, and often applied in the market. However, none of them proved to be absent of high employment costs or burdensome installations. For this reason, the low-cost Active Mass Damper (AMD) shown in this work and capable of automated self-tuning, control and continuous monitoring of the structures represents an attractive solution. The device has been designed and tested on the numerical model of a scaled steel made three story building. In particular its working principle and the ISAAC algorithm for automatic identification are presented and its robustness against modelling and estimation errors is analyzed. The methodology allows to avoid the study of specific solutions for each case, thus making possible the adoption of such systems also for already existing and common structures.
In this work a completely automated output-only Modal Analysis procedure is presented and all its benefits are listed. Based on the merging of different Operational Modal Analysis methods and a statistical approach, the identification process has been improved becoming more robust and giving as results only the real natural frequencies, damping ratios and mode shapes of the system. The effect of the temperature can be taken into account as well, leading to the creation of a better tool for automated Structural Health Monitoring. The algorithm has been developed and tested on a numerical model of a scaled three-story steel building present in the laboratories of Politecnico di Milano.
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