Aero-engine blade profile reconstruction based on adaptive step size bat algorithm and visualization of machining error

Abstract

High-precision profile reconstruction is a key issue in the profile detection and visualization of aero-engine blades. A method based on adaptive step size bat algorithm (ASSBA) for blade profile reconstruction and an adaptive mesh model for visualization analysis of the key machining errors are proposed. Firstly, the original bat algorithm (BA) is improved to introduce the global stage and local search stage. Then, combined with the node layer characteristics of the blade measurement data, the ASSBA is used to fit the optimal surface. Further, the adaptive mesh is planned on the blade profile to extract various evaluation parameters. Finally, the algorithm analysis and verification are carried out based on a certain type of blade. The results show this reconstruction method can get the fitted surface more quickly and accurately than other iterative methods. Simultaneously, the visualization method and corresponding software system can intuitively visualize the blade profile error, the twist deformation error, the swept deformation error, the bending deformation error and the cross-section line profile error.