Abstract: The operational modal analysis methods based on outputonly measurements are wellknown and applied in linear systems. However, they are not so well developed for nonlinear systems. Thus, this paper proposes an approach for ...

Abstract: One significant challenge in machine learning for Structural Health Monitoring (SHM) is reusing previously trained classifiers. A classifier might be suitable for one situation but not for another. Transfer learning ...

Abstract: This tutorial examines the failure theories of Tresca and von Mises, both of which are crucial for designing metallic structures. Conventionally, Tresca is regarded as more conservative than von Mises from a deterministic ...

Abstract: This paper investigates how to improve the performance of a classifier of tightening torque in bolted joints by applying transfer learning. The procedure uses vibration measurements to extract features and to train a ...

Abstract: This article demonstrates the Gaussian process regression model’s applicability combined with a nonlinear autoregressive exogenous (NARX) framework using experimental data measured with PZTs’ patches bonded in a composite ...

Abstract: AbstractTurbulent wind data measured by sonic anemometers installed at various heights on a 140-m-tall micrometeorological tower located at a coastal site are used to obtain vertical profiles of the velocity standard ...