Title

An Experimental Study Of Resonance Frequency Detuning Applied To Blade Mistuning

Abstract

Turbomachinery blade technology has recently trended towards the use of monolithic bladed disks. Although offering a wealth of benefits, this construction removes the blade attachment interface present in the conventional design, thus unintentionally removing a source of friction-based damping needed to counteract large vibrations during resonance passages. This issue is further exacerbated for blade mistuning, which is well-known to induce vibration localization with correspondingly larger vibration magnitudes. Recently, an alternative method to reduce vibration, termed Resonance Frequency Detuning (RFD), utilizes the variable stiffness properties of piezoelectric materials embedded on-blade to detune the response when approaching a resonance crossing, thus resulting in reduced vibration. For a single-degree-of-freedom (SDOF) system, the vibration reduction performance and the optimal stiffness state switching is well-defined. Previously, RFD has been experimentally validated on a representative blade for a sufficiently well-separated vibration mode, thus satisfying the SDOF assumption. No such experimental validation currently exists for a system with closely-spaced modes or, more specifically, applied to blade mistuning. This work utilizes an academic blisk machined in the form of 8 blades attached to a central hub. Each blade incorporates two collocated piezoelectric patches located near the blade root: one patch provides the stiffness state modulation, while the other patch provides actuation to mimic engine order excitations. For the forcing configuration studied, experimental results show qualitative agreement to numerical results with the vibratory response associated with the optimal stiffness state switch showing reductions across all blades.

Publication Date

1-1-2018

Publication Title

Proceedings of the ASME Turbo Expo

Volume

7C

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1115/GT201876834

Socpus ID

85054010424 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85054010424

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