Uncertainty qualification analysis for torsional vibration of crankshaft based on generalized polynomial chaos expansion
* Presenting author
Torsional vibration is the main vibration form of crankshaft in power machine, which directly affects the operational reliability of power machine, especially for the case when some parameters are undetermined. In order to calculate the risk and improve the operational reliability efficiently, some of uncertainties have to be taking in account for a reliable analysis. In this research, a non-sampling probabilistic method based on generalized polynomial chaos (gPC) expansion is employed to torsional vibration analysis of crankshaft with uncertain geometrical and material parameters. At first, a probabilistic model of uncertainties is constructed using gPC to describe random parameters and to predict variabilities in torsional vibration response. The gPC expansion possessing random orthogonal basis is served as uncertain dynamic responses, while the calculation of the polynomial coefficients for uncertain parameters by using various procedures, e.g. Galerkin projection, collocation method, and moment method is presented. Then a comprehensive error and accuracy analysis of the method is discussed for various random variables and random processes compared with the exact solution or/and Monte Carlo simulations. In addition, the impact of parameter uncertainties on the torsional vibration of crankshaft is also investigated.