An automated reverse engineering process is developed that uses a structured light optical measurement system to collect dense point cloud geometry representations. The modeling process is automated through integration of software for point cloud processing, reverse engineering, solid model creation, grid generation, and structural solution. Process uncertainties are quantified on a calibration block and demonstrated on an academic transonic integrally bladed rotor. These uncertainties are propagated through physics-based models to assess impacts on predicted modal and mistuned forced response. Process details are discussed and recommendations made on reducing uncertainty. Reverse engineered parts averaged a deviation of 0.0002 in. (5 μm) which did not significantly impact low and mid-range frequency responses. High frequency modes were found to be sensitive to these uncertainties demonstrating the need for future refinement of reverse engineering processes.

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