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The assembly quality of an aero-engine directly determines its stability in high-speed operation. The coaxiality and unbalance out of tolerance caused by improper assembly may give rise to complicated vibration faults. To meet the requirements of the dual objective and reduce the test cost, it is necessary to predict the optimal assembly angles of the rotors at each stage during pre-assembly. In this study, we proposed an assembly optimization method for a multistage rotor of an aero-engine. Firstly, we developed a coordinate transmission model to calculate the coordinates of any point in the rotors at each stage during the assembly processes of a multistage rotor. Moreover, we proposed two different pieces of assembly optimization data for the coaxiality and unbalance, and established a dual objective evaluation function of that. Furthermore, we used the genetic algorithm to solve the optimal assembly angles of the rotors at each stage. Finally, the Monte Carlo simulation technique was used to investigate the effects of the geometric measured errors of each rotor on the proposed genetic algorithm. The simulation results show that the process of the dual objective optimization had good convergence, and the obtained optimal assembly angles of each rotor were not affected by the geometric measured errors. In addition, the dual objective optimization can ensure that both the coaxiality and unbalance can approach their respective optimal values to the most extent, and the experimental results also verified this conclusion. Therefore, the assembly optimization method proposed in this study can be used to guide the assembly processes of the multistage rotor of an aero-engine to achieve synchronous optimization for the coaxality and unbalance.

An Assembly Method for the Multistage Rotor of An Aero-Engine Based on the Dual Objective Synchronous Optimization for the Coaxality and Unbalance