Structural Health Monitoring are frequently reported in the literature and a number of techniques exist for the assessment of the health state of a structure. Some of them aim at tracking changes in structural response directly or indirectly related to the mechanical characteristics (such as natural frequencies, etc.) of the structure before and after damage. Conversely, other procedures are based on the post-processing of measurement data to detect anomalies from measurements (ARMAV modeling, wavelet decomposition, etc.). In both cases, the trend is in using methods able to automate the detection process by taking advantage of the recent advances in information technologies. Considering the first group of techniques, one of the main drawbacks is related to the need of a user intervention in order to identify the modal parameters of the structure. This aspect does not fulfill the requirements of SHM system, which should be fully automated, in particular when several structures are monitored at the same time and a post-earthquake scenario is required. In the present paper, a procedure, implemented in LabView environment and able to overcome some typical drawbacks of classical operational modal analysis, is described. Such software can work as a stand alone application, based on previously recorded data or on data obtained during test from a data acquisition hardware, or as a part of a fully automated Structural Health Monitoring system. The algorithm and the software are briefly discussed and a number of case studies are reported, pointing out potentialities and limits of the proposed procedure in identifying the modal parameters of different typologies of structures (moment resisting r.c. frames, masonry bell tower, tuff vault, and so on). Data come from all previously mentioned sources and a specific case study, related to the integration of the software into fully automated SHM systems, will be analyzed.
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