Abstract
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.
Highlights
Is the ultimate technical link during the manufacturing process of an aeroengine
A coordinate transmission model used for predicting the coordinates of the centroid and center-of-mass of the rotors at each stage after assembly is derived
For the third problem raised in the Introduction, we proposed a dual objective optimization model by using a genetic algorithm to achieve the synchronous minimization of the coaxiality and unbalance of a multistage rotor
Summary
Is the ultimate technical link during the manufacturing process of an aeroengine. The coaxiality and unbalance are two important indexes to evaluate the assembly quality of an aero-engine. Limited to the conventional assembly technology for an aero-engine, testing and dismounting need to be repeatedly conducted in most cases, making sure that the two indexes of the coaxiality and unbalance can be satisfied simultaneously [7,8]. Without a doubt, such a cumbersome process requires a long time and a high cost. Reasonable assembly optimization methods or error control approaches should be developed to improve the one-time assembly acceptance rate and assembly efficiency of an aero-engine
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