Blade vibrations are one of the main cost drivers in turbomachinery. Computational blade vibration analysis facilitates an enormous potential to increase the productivity in the design of bladed components. Increasing computing power as well as improved modeling and simulation methods leads to comprehensive calculation results. This allows for a more precise prediction and assessment of experimental data. Usually, in the field of turbomachinery, identical blades are assumed to lower the required computational resources. However, mistuning is unavoidable, since small deviations due to the manufacturing process will lead to slightly different blade behavior. Potential effects such as mode localization and amplification can be treated statistically and have been thoroughly studied in the past. Since then, several reduced order models (ROMs) have been invented in order to calculate the maximum vibration amplitude of a fleet of mistuned blisks. Most commonly, mistuning is thereby modeled by small material deviations from blade to blade, e.g., Young's modulus or density. Nowadays, it is common knowledge that the level of manufacturing imperfection (referred as level of mistuning) significantly influences mode localization as well as vibration amplification effects. Optical measurements of the geometric deviations of manufactured blades and converting to a high-fidelity finite element (FE) model make huge progress. However, to the knowledge of the authors, there is no reliable method that derives a characteristic quantity from the geometric mistuning, that fits into the mentioned statistically approaches. Therefore, experimental data are needed to quantify the level of mistuning. Several approaches, which isolate blade individual parameters, are used to identify the dynamic behavior of axial compressors and turbines. These methods can be applied to medium-speed centrifugal turbine wheels but tend to fail to evaluate high-speed compressor with splitter blades. This paper briefly presents the original approach and discusses the reasons for failure. Thereafter, a new approach is proposed. Finally, the level of mistuning and important quantities to perform a statistical evaluation of a high-speed compressor is shown.

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