C Conferentia Proceedings
USM-2016-0008 Stochastic dynamics and random vibrations

Effects of a random loading emulating an irregular terrain in the nonlinear dynamics of a tower sprayer

Americo Cunha Jr1; Jorge Luis Palacios Felix2; José Manoel Balthazar3

1 Universidade do Estado do Rio de Janeiro; 2 Universidade Federal do Pampa; 3 Instituto Tecnológico de Aeronáutica

doi:10.20906/CPS/USM-2016-0008

Resumo

This paper deals with the nonlinear dynamics of a mechanical system which consists of an orchard tower sprayer, coupled with a vehicle suspension that is subject to random excitations due to soil irregularities. A deterministic mathematical model, where tower is considered as an inverted double pendulum over an vehicle suspension, with three degrees of freedom (one translation and two rotations) is constructed. To take into account the random loadings due to soil variabilities, a parametric probabilistic approach is employed, where the external force is assumed to be a harmonic random process. This stochastic process has random amplitude and frequency, which are modeled as random variables, and a sinusoidal shape in time. The distribution of these random parameters is consistently specified using the maximum entropy principle. The propagation of uncertainties through the stochastic model is computed using the Monte Carlo method. Numerical simulations show large discrepancies in the system response, when compared with nominal (deterministic) model, for the cases studied where the forcing frequency is random. Also, the results shown that the steady state probability distributions are completely different in all the case studied.

Palavras-chave: nonlinear dynamics; orchard tower sprayer; double inverted pendulum; uncertainty quantification; parametric probabilistic approach

Como citar

Americo Cunha Jr; Jorge Luis Palacios Felix; José Manoel Balthazar. “Effects of a random loading emulating an irregular terrain in the nonlinear dynamics of a tower sprayer”. 3rd International Symposium on Uncertainty Quantification and Stochastic Modeling. UNCERTAINTIES2016. 2016. DOI: 10.20906/CPS/USM-2016-0008