A method in model updating using Miscorrelation Index sensitivity

This paper presents a new model updating method based on minimization of an index called Miscorrelation Index (MCI), which is introduced to localize the coordinates carrying error in a finite element (FE) model. MCI can be calculated from measured frequency response functions (FRFs) and dynamic stiffness matrix of the FE model for each coordinate as a function of frequency. Nonzero numerical values for MCI of a coordinate indicate errors in one or more elements of the system matrices corresponding to this coordinate. The sensitivity-driven model updating method presented in this study (MCI Sensitivity Method) is based on minimization of MCI. The application of the method is illustrated with four case studies. In the first and second examples a discrete system is considered, and computationally generated and polluted FRFs are used as pseudo-test data. In the third and fourth case studies, real test data is used and the performance of the method in practical applications is demonstrated on the benchmark structure built to simulate the dynamic behavior of an airplane, namely, GARTEUR SM-AG19 test bed. It is concluded that MCI Sensitivity Method yields successful results even when the measured responses of only a few coordinates are used, especially when miscorrelation is due to local errors.