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This paper aims the study of the accuracy provided by the identification of modal damping ratios based on ambient and free vibration tests. For that purpose, numerical simulations were developed to generate artificial experimental data concerning both types of tests. This simulated data allowed the illustration of the influence of factors like non-proportional damping or the proximity of natural frequencies on the quality of the estimates. The accuracy of two output-only identification algorithms (Enhanced Frequency Domain Decomposition and Covariance driven Stochastic Subspace Identification methods) and of two alternative procedures to process the free decays was also analyzed.

The paper reviews some of the most recent aspects involved in the dynamic testing and continuous monitoring of bridges. This includes a discussion of testing techniques, instrumentation, modal identification and damage detection. On the basis of their experience, the authors described several case studies in which some of the most recent developments have been used to accomplish different purposes: the

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Summary In the current state of development, it is very hard to remotely evaluate the actual condition of wind turbines structures. This makes it impossible for a wind farm owner to correctly deliberate about the need of retrofitting the current wind turbine structure, as well as to decide about the possible extension of its operating lifetime. Taking into account this problem, this paper introduces the main aspects in the development of a vibration‐based monitoring system for an onshore 2.0‐MW wind turbine based on the identification of the modal properties of the most important vibration modes. Initially, the wind turbine is introduced, as well as the implemented monitoring system. Then, the main steps of the monitoring system are briefly described. A detailed attention is given to the statistical procedure based on regression models used to minimize the influence of operational and environmental effects over the features used to detect structural changes in the wind turbine. Lastly, the suitability of the system to detect damages is thus assessed, through the analysis of three common damage scenarios: onshore foundation damage; damage by scour on an offshore foundation; and blade damage. It is concluded that the system is capable of detecting damage in onshore and offshore foundations, as well as in rotor blades. The most important contribution of the paper is the definition of monitoring framework for damage detection, its implementation, and validation with monitoring data collected during more than 1 year in a utility‐scale wind turbine.