Construction of damage-free digital twin of damaged aero-engine blades for repair volume generation in remanufacturing

Accurate repair volume generation from 3D scan data of damaged aero-engine blades is of great importance in additive or hybrid remanufacturing for restoring the blades to a like-new condition. In addition to material-missing damages, the blade's surface also deforms due to working in harsh environments, which makes it deviate from the nominal design geometry. Therefore, the Boolean operation between the nominal CAD model and the scanned point cloud of the damaged blade does not yield an accurate repair volume. This paper presents a new methodology to construct an accurate damage-free digital twin model of the defective blades that contains the deformations of the blade's undamaged regions. The Boolean difference between the scan data of the damaged blade and its damage-free digital twin yields the repair volume with a smooth geometric transition at the interface of the repair patch and unrepaired regions. At first, the data points of damaged regions of the blade surface are detected and eliminated from the scan through a region growing segmentation. Then, a CAD-to-scan non-rigid registration algorithm deforms the nominal CAD model of the blade to best match it to the scanned point cloud in the undamaged regions. The non-rigid registration algorithm iteratively minimizes the distance between two datasets under the local rigidity constraint to avoid shrinkage and expansion of the deformed CAD model. A constrained point-to-surface weighted correspondence search method is proposed to reduce the influence of noise and unreliable correspondences on the non-rigid registration. The results of numerical and experimental case studies have demonstrated that the proposed method is accurate and robust to noise, and it can be effectively applied to construct a damage-free digital twin model for repair volume generation.