Mode shape correlation techniques have proven to be an excellent method for assessing the degree of similarity between a finite element model and a set of test data. Because mode shapes inherently contain spatial information on the mass and stiffness matrices of the model and are easily extracted from test data, this allows an overall similarity assessment as well as providing indications of localized areas of discrepancy. Although frequency response function (FRF) correlation contains the same information as used in mode shape correlation (both contain a collection of measurement points), FRF correlation has been found to be more difficult to use successfully. This difficulty is primarily because of the high sensitivity of frequency response functions to slight perturbations both in the boundary condition and in the excitation and response. As a result, the globally extracted mode shapes minimize the contamination due to testing perturbations, while frequency response functions maintain this sensitivity This sensitivity makes it possible to measure similarity, or lack thereof, in socalled identical components or assemblies.Sandia National Laboratories wishes to develop a quick testing process able to identify assembly errors in a complex structure with many joints while minimizing the structure's required downtime prior to its intended purpose. A frequency response function similarity approach was used where the structure was mounted on a test fixture and a limited number of responses were recorded with a single drive point. Because mode shape correlation techniques are widely used, the corresponding frequency response function correlation techniques have not been studied as much. For this paper, several different frequency response function correlation methods were assessed on a simplified structure to identify which technique(s) are best able to detect any assembly errors while being insensitive to other errors.

This paper presents the dynamic characterization of a CX-100 wind turbine blade using modal testing. Obtaining a thorough dynamic characterization of turbine blades is important because they are complex structures, making them very difficult to accurately model without supplementing with experimental data. The results of this dynamic characterization can be used to validate a numerical model and understand the effect of structural damage on the performance of the blades. Also covered is an exploration into Structural Health Monitoring (SHM) techniques employed on the blade surface to detect changes in the blade dynamic properties. SHM design parameters such as traveling distance of the wave were examined. Results obtained during modal and SHM testing will provide a baseline for future work in blade damage detection and mitigation.

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