Geometric mistuning identification and finite element model updating methods for bladed disks

Abstract

Dynamic analysis results of a blisk are sensitive to inevitable geometrical mistuning, and the high-fidelity finite element model (FEM) of real blisk is of paramount importance to accurately predict structural dynamics. However, it is still challenging to accurately identify geometric mistuning and obtain a high-fidelity FEM due to the complexity and stochastic nature of geometric mistuning. In this paper, considering various types of geometrical mistuning, both a novel geometric mistuning identification and automatic finite element model updating (FEMU) method for real blisk using measured point cloud data are presented to reduce the discrepancies between the real blisk and the numerical model. The geometric surface of the real blisk is digitized to the point cloud data by a non-contact optical measurement technique. Three implementation steps of the method are introduced: 1) morphological feature detection from measured point cloud data of blisk; 2) surface nodes space mapping of FEM using isoparametric transformation; and 3) mesh shape optimization for FEMU. Eventually, two experimental cases are investigated: a simplified blisk and an industry blisk. The robustness of pre-processing algorithms for geometrical feature detection with measurement noise is also conducted. Results show that the blades with small mistuning, large deformations, and damages in the tip and leading edges are accurately identified and updated using the proposed method. Compared with measured natural frequencies for updated FEM, the maximum error is less than 3.38‰.