Comparative Study of Different Intelligent Algorithms in APU Rotor Blade Sorting

The auxiliary power unit (APU) of aircraft is an important part of the aviation power system. The assembly process is a key link in the production and manufacturing of APU, especially the assembly accuracy of the turbine rotor, which directly affects the working stability and life of the APU. The unbalance error of the rotor after assembly is one of the important indicators to evaluate the assembly quality. Aiming at the problems of low manual assembly efficiency and excessive unbalance of APU turbine rotor, a rotor unbalance error optimization model was established. Based on the blade mass, rotation radius, and the blade disk unbalance, the APU rotor unbalance error control optimization model was established. The overall rotor unbalance error was controlled by blade sorting. Then, the blades were sorted based on different heuristic optimization algorithms, and the performance of each sorting method was compared. Simulation experimental results demonstrate that intelligent algorithm-based blade sorting can reduce unbalance error and enhance assembly precision.