Research on the prediction method of unbalance responses of dual-rotor system based on surrogate models

Abstract

In this work, the prediction methods of unbalance responses based on the surrogate models were studied, where the simulation data of vibration responses of a dual-rotor system with four disks and five supportings were involved. Firstly, based on the Latin hypercube sampling and random sampling with uniform distribution of unbalance distribution of the fan disc and the hyper-compressor disc, the input variables of the training samples and the testing samples were respectively obtained. According to the sampling results, the multi-body dynamics simulations were conducted to extract the vibration responses at the corresponding measuring points as the output variables of the sample space. Then, the algorithms of multivariate adaptive regression splines (MARS), radial basis function (RBF) and Kriging, were selected to respectively construct the response-predicted models of the rotor system. Finally, predicted vibration responses were figured out by surrogate models and the prediction accuracies were verified by comparison with output parameters in the testing samples. The results showed that the prediction methods of unbalance responses based on MARS, RBF and Kriging enjoyed high prediction accuracies according to the standards, which were proved to be feasible in theoretically.