Research on blade grouping method for array machining

Blades are the core component of aero-engines. The complexity of aero-engine blades deformation after multi-axis milling causes poor consistency in batch blades. In turn, the poor consistency of blades affects the aerodynamic performance of an aero-engine. Hence it is critical to ensure the consistency of blades before precise machining. This article proposes a clustering-based blade grouping strategy aiming to improve the consistency of the same group of blades automatically and efficiently. First, the feature vector of the blade and the distance between two blade surfaces are defined. Then the K-medoids clustering algorithm is used to group the blades. According to the maximum allowable distance between the blade surfaces and the Ray-Turi index, the ideal number of clusters, that is the number of groups, is determined. Finally, the clustering center of each cluster is selected as the blade processing model of each group. The experiment for aero-engine blade grouping and machining was performed to demonstrate the effectiveness of the proposed method and the results show that it can improve the consistency of the blades in each group. The geometric contour differences of the blades in the group are not more than 0.02 mm, which can satisfy the requirements of the following precise array machining.