Study on sensitivity analysis of blade airfoil characteristics against foreign object damage based on K-Means clustering

Abstract In order to solve the problem of the unclear relationship between the aerodynamic characteristics of aircraft engine fan blade airfoil (such as leading edge radius and wedge angle) and its resistance to foreign body damage (FOD) and the sensitivity analysis under data redundancy conditions that cannot be achieved by traditional data analysis methods, a sensitivity analysis method based on K-means clustering was proposed. First, simulated impact tests were conducted on TC4 titanium alloy specimens using an air cannon. The step-loading test method was used to assess the High cycle fatigue (HCF) strength of the damaged specimens. Then, K-means clustering was employed to categorize the experimental data and determine the number of clusters for the test regions. Finally, in the partition divided by the K-means method, under the condition of disordered experimental data, the influence of multiple factors on the HCF of fan blades at different stages was obtained, which provides an effective data analysis method and a solid theoretical basis for the subsequent design and finalization of fan blades.