An Optimization Method for Stiffness and Damping Mistuning Identification From Blade Tip Timing Data

Abstract

System identification of dynamic properties is of large interest in the turbomachinery industry to create more accurate computational models and more effective designs. Previous identification techniques are able to accurately capture the blade variability, known as mistuning, in the stiffness as well as the average damping of all the blades. Mistuning is vital to accurately identify and study because the symmetry of the system is broken and can lead to vibration localization and high amplitudes. In this work, a new method is proposed to not only capture the stiffness mistuning values but also the blade-to-blade variability in damping. These damping mistuning values have been shown to have a significant effect on the dynamics of bladed disk systems. Incorporation of the damping mistuning into the computational model can be done utilizing an augmented component mode mistuning (CMM) method with either structural or proportional damping. The mistuning values for this new identification method were compared to a well-established direct method and a previously studied optimization method. Blade responses were then found using a harmonic analysis and the newly identified mistuning values. These blade responses were then compared to experimental tip timing data from full scale rotating experiments. These comparisons show that the new model is able to better reproduce experimental data using computational models that incorporate both stiffness and damping mistuning values.