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Learning Professional Ways of Beingnt vibration tests were performed on the footbridge to extract the modal parameters of the structure such as natural frequencies, damping ratios, and mode shapes. The modal properties were identified from ambient vibration tests adopting the Stochastic Subspace Identification (SSI) technique. The av

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Learning with Damaged Colonial Places civil structures, such as thermal and nuclear power plants. Acoustic emission (AE) detection can be potentially used to establish the real-time passive SHM method. Conventional AE sensors are made from piezoelectric materials, whose operational temperature is limited up to 200?°C. Hence, it is diff

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Conclusions and Policy Implications,hose data to the web server. The developed sensor unit consists of Raspberry Pi 3B, digital MEMS accelerometer and Low Power Wide Area (LPWA) network device. Having the transmitted data volume limitation, LPWA network device advantageously enables long-distance communication with such a low power as

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https://doi.org/10.1057/9780333982990f each analyzed viaduct span, as well as the characterization of the trains travelling on the line. Through the adoption of an operation modal analysis (OMA) technique, it was then possible to construct a large database of the dynamic features concerning the studied viaducts. This database may be ex

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https://doi.org/10.1007/978-1-4419-0582-6of numerous measurement locations for its identification (Cao et al. in Smart Mater Struct 26:043001, 2017). In this study, amplitude dependence of damping ratio was also investigated, since a change in the modal damping ratio can be used for damage identification but its dependence on amplitude rem