Stochastic Dynamic Responses of Telescopic Crane Multibody Systems via Integrating Simplified Dynamic Model and Polynomial Chaos Expansion

This study proposes a surrogate modeling method by combining a simplified dynamic model with polynomial chaos expansion (PCE) to evaluate the stochastic dynamic responses of telescopic crane multibody systems under multiple uncertain parameters. A simplified five-degree-of-freedom equation of motion is derived using Lagrange's equations and multibody dynamics techniques. This model effectively captures the coupled effects of boom vibrations and payload sway by incorporating equivalent spring-mass-damper systems and spatial suspension configurations, and its accuracy is validated against experimental data from a large-scale telescopic crane. To address uncertainties in parameters such as boom mass, stiffness, rope length, and payload mass, a surrogate modeling approach for uncertain dynamic analysis is developed. This approach integrates the PCE method with the validated deterministic dynamic framework, achieving a balance between computational efficiency and uncertainty quantification accuracy. Latin hypercube sampling is employed to systematically sample the uncertain parameters, while regression analysis is used to determine the polynomial coefficients that characterize the system's uncertainty. A comparative analysis with the Monte Carlo method is performed to evaluate the system's stochastic response characteristics. Furthermore, the effects of different types and magnitudes of uncertainty on the dynamic response are thoroughly investigated.