Towers, roller batteries, propelling cables and vehicles are the substructures of ropeway transportation systems. Highfidelity modeling of their dynamical interactions together with a reliable identification is a key step towards the prediction of the system response under various transit conditions as well as to investigate design optimization strategies. In this work, a nonlinear mechanical model for the dynamical description of cablecar ski lift systems is discussed. The investigation is focused on the modal features and the forced dynamic response caused by the vehicles transit across the so-called compression towers. The model is validated according to experimental data acquired via a custom-design sensor network. The Enhanced Frequency Domain Decomposition (EFDD) method is employed to identify the frequencies and damping ratios.
Dynamic response and identification of tower-cable-roller battery interactions in ropeways / Arena, Andrea; Carboni, Biagio; Lacarbonara, Walter; Babaz, Mathieu. - ELETTRONICO. - 6:(2017), p. V006T10A045. (Intervento presentato al convegno ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2017 tenutosi a usa nel 2017) [10.1115/DETC2017-67810].
Dynamic response and identification of tower-cable-roller battery interactions in ropeways
Arena, Andrea
;Carboni, Biagio;Lacarbonara, Walter;
2017
Abstract
Towers, roller batteries, propelling cables and vehicles are the substructures of ropeway transportation systems. Highfidelity modeling of their dynamical interactions together with a reliable identification is a key step towards the prediction of the system response under various transit conditions as well as to investigate design optimization strategies. In this work, a nonlinear mechanical model for the dynamical description of cablecar ski lift systems is discussed. The investigation is focused on the modal features and the forced dynamic response caused by the vehicles transit across the so-called compression towers. The model is validated according to experimental data acquired via a custom-design sensor network. The Enhanced Frequency Domain Decomposition (EFDD) method is employed to identify the frequencies and damping ratios.File | Dimensione | Formato | |
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