The Ground Vibration Test (GVT) is one of the key milestones in the characterization of an aerospace
structure, allowing to describe its structural dynamic behavior. Moreover, a helicopter GVT is associated to
additional challenges deriving from the rotorcraft architecture, such as a high modal density and non-linear
phenomena. In this paper, these challenges are treated by presenting the extensive H145 GVT campaign
carried out in June 2017 by AHD and DLR, from its conception to the first analysis of results. Starting from a
H145 FE model, the pre-test analysis began with the selection of target modes from the initial numerical
modes set based on modal participation and energy considerations. An optimal sensor distribution was also
achieved as results of the implementation of sensor placement metrics like the Normal Displacement Method
and sensor elimination methods based on MAC analysis. An extensive description of the testing methods
and procedure is as well documented, from the use of a dedicated test rig to the excitation of the structure by
means of several exciter constellations using different force levels in order to assess non-linear behavior and
therefore identify the structural variability. After data acquisition, the efficient post-processing performed
using DLR correlation tool allowed the identification of modes family and the creation of a modal model. In
the first analysis of results, modal identification has shown the validity of the pre-test analysis by identifying
more than 40 modes for the first helicopter configuration and exhibiting an excellent data quality. Comparison
between two H/C configurations has given also a first sample of how structural variability can influence the
modal layout. Furthermore, focus has been put on the identification and analysis of non-linear phenomena,
proving how non-linear behavior can affect significantly the H/C dynamic response and the modal
identification. Finally, a comparison between FE and test results for one H/C configuration has been
performed, allowing an objective evaluation of the predictive capability of current FE models. On this basis,
the path for future works in the field of FE modal updating and structural optimization is clearly defined.
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