---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- AUTHORS: Cristiano Martinelli (University of Strathclyde, University of Glasgow), Andrea Coraddu (TU Delft), Andrea Cammarano (University of Glasgow) EMAIL (personal): cristiano.martinelli@outlook.com EMAIL (institutional): cristiano.martinelli@strath.ac.uk, andrea.cammarano@glasgow.ac.uk, a.coraddu@tudelft.nl Cite as: Martinelli, C., Coraddu, A., Cammarano, A. (2023). Experimental Analysis of a Nonlinear Piecewise Multi-Degrees of Freedom System. Advances in Nonlinear Dynamics. NODYCON Conference Proceedings Series. Springer. ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Dataset description: The dataset contains the experimental dynamic measurements of a nonlinear Multi-Degree of Freedom System featuring hardening and piecewise stiffness characteristics. The system was studied in different ways: a linear analysis was performed with low-amplitude random excitation while a second nonlinear analysis was performed via stepped sine excitation. The nonlinear analysis was repeated with and without the stoppers (which approximate a piecewise stiffness characteristic) to better understand the nature of the system. Folders description: the data consisted of two folders: the folder "1-LinearAnalysis" contains the data about the underlying linear system, while the folder "2-NonlinearAnalysis" contains the data about the nonlinear system, with and without the presence of the stopper. The full description of the system is provided in the paper Martinelli, C., Coraddu, A., Cammarano, A. (2023). Experimental Analysis of a Nonlinear Piecewise Multi-Degrees of Freedom System. Advances in Nonlinear Dynamics. NODYCON Conference Proceedings Series. Data format: All the data are stored in MAT and CSV (excel) files which are accessible with MATLAB and Python codes (attached to the dataset). Software versions: - MATLAB (version 2021b) - Python (version 3.8.5)