Study on meshing design hyperparameters impact on edge detection accuracy in twin-screw compressors using the alpha-shape algorithm

Abstract

Twin-screw compressors, widely used in refrigeration, gas processing, and power industries, rely on precisely generated rotor profiles to ensure high efficiency and reliability. In recent years, the Alpha Shape algorithm has been increasingly applied for generating screw rotor profiles from discrete surface points; however, balancing geometric accuracy and computational cost within this method remains a major challenge due to its high sensitivity to parameter settings. This study systematically investigates the influence of key parameters—specifically the α radii and point density—on reconstruction accuracy and reliability. The symmetric and SRM-D rotor geometries are analyzed across multiple scales to capture geometric and dimensional effects. Results indicate that decreasing α and increasing point density can reduce reconstruction errors to below 2 and 10 μm for the symmetric and SRM-D profiles, respectively, though with longer computation times. Sensitivity analysis of maximum error provides quantitative insight into balancing accuracy and efficiency. The proposed parameter ranges and error distribution analysis offer practical guidelines for optimizing the Alpha Shape algorithm in the reverse engineering of twin-screw rotors.