Responses of weakly non-linear dynamical systems subjected to random parametric and external excitations

Menh, Nguyen Cao

doi:10.1016/s0022-460x(87)81335-4

Cited by 5 publications

(1 citation statement)

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“…To improve them, also nonlinear physical phenomena need to be taken into account; this is one of the reasons why nonlinear dynamic problems are receiving an always growing attention in literature [6][7][8][9][10][11][12][13][14]. The system analysis becomes more and more critical if the dynamic process involves also high speed moving elements: in fact, whether pure impact dynamics are a traditional trivial topic [15][16][17][18][19], the model parameters estimation requires as a result an accurate experimental and numerical investigation [20][21]. In this paper, the response of a nonlinear dynamic system to high speed stimuli will be considered, and the measurement techniques adopted to characterize the model parameters will be therefore described.…”

Section: Introductionmentioning

confidence: 99%

Measurement Techniques and Characterization of High Speed Moving Objects

Lancini

Amici

Breda

2010

The International Conference on Applied Mechanics and Mechanica

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Response to fast speed stimuli of non linear system is difficult to predict without a proper model whose parameter has been characterized in condition closer to the working ones, because assumptions and simplifications on component stiffness and damping, such as their linearity in the frequency domain, are no longer valid. To characterize a two degrees of freedom spring-mass-damper system reacting to a high speed impact a set of statistical techniques has been developed and applied to a set of experimental measurements obtained thanks to a high speed camera, a piezoelectric load cell and a set of piezoaccelerometers. Photogrammetric position accuracy has been improved using a least square estimator of a single position from different markers, therefore position and acceleration data have been fused together being weighted on the reciprocal of their uncertainties. Starting from load, position, velocity and acceleration data, spring-mass-damper systems with different degrees of freedom have been characterized in different configurations using genetic algorithms to minimize the square deviation of prediction from measured speed, although the term to be minimized has been again weighted on reverse of uncertainty to avoid false results. Eventually the whole process has been validated and automated in order to provide a new and efficient mean of characterizing dynamic parameters such as stiffness, damping, trigger length of elastic systems impacted by high speed 1 objects.

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