This paper proposes a blade sorting method based on the cloud adaptive genetic algorithm (CAGA), which is used to optimize the unbalanced of asymmetric rotor of aero-engine. Firstly, by analyzing the unbalance of the arrangement caused by the deviation of the mass moment of the blade, and considering the concentricity of the disk, an optimization model of the unbalanced amount of the blade assembly was established. Secondly, the selection operator, crossover operator, and mutation operator of the algorithm were designed, and the cloud adaptive genetic algorithm was used to optimize the assembly unbalance. Thirdly, the mass moments of a group of aero-engine blades were weighed using a moment scale (MW0), and the blade mass moment distribution and assembly unbalance under the six blade arrangements were analyzed. Finally, by setting different disk concentricity, the corresponding blade arrangement and the final rotor unbalance were obtained. Through analysis, it was found that the unbalance of GA is at least 57.5% optimized relative to the weight sorted, sorting type 2, sorting type 4, and sorting-1/4 skip method, and the unbalance optimized by the CAGA is 95.7% optimized relative to GA. In the case of different initial concentricity of the disk, the effective algorithm accuracy is still maintained, which proves the effectiveness of the method for the arrangement of asymmetric rotor blades. This method establishes an effective asymmetric rotor blade arrangement model, uses the cloud adaptive genetic algorithm to sort the blade assembly, and effectively reduces the unbalanced amount of the asymmetric rotor.

To suppress the vibration of rotary parts, this paper established an unbalanced vibration response control model of rotary parts based on rotating axis coordinate system. This model considered the stacking transformation of geometric parameter errors and mass parameter errors of single stage rotor. First of all, the centroid transfer model based on the actual rotation axis was established, and the unbalanced excitation force vector of each stage of the rotor was studied. Secondly, the unbalanced excitation force vector of each stage of the rotor is substituted into the model of assembly vibration control based on the double constraints optimization strategy. Finally, the simulation analysis and the vibration experiment of three-stage rotor stacking assembly is carried out. The results show that the vibration of the engine rotor can be effectively suppressed by adjusting the assembly phase of the rotors, and the vibration amplitude of the combined rotor assembled by the double constraint optimization assembly strategy is 22.5% less than the vibration amplitude assembled by the direct assembly strategy. Besides, the coaxiality and the unbalance are reduced by 44.1% and 78.4%, which fully shows the advantages of the double constraint optimization assembly strategy.

The unbalanced exciting force of high-speed rotary asymmetric rotor equipment is the main factor causing rotor vibration. In order to effectively suppress the vibration of the asymmetric rotor equipment, the paper establishes a multistage asymmetric rotor coaxial measurement stacking method that minimizes the exciting force. By analyzing the propagation process of the centroid of the multistage asymmetric rotor assembly and analyzing the relationship between the geometric center and the centroid of a single asymmetric rotor, a multistage asymmetric unbalanced rotor propagation model based on geometric center stacking is established. The genetic algorithm is used to optimize the unbalance of the multistage asymmetric rotors. Combined with the vibration principle under the exciting force, the vibration amplitude of the left bearing at different rotation speeds under the minimization of the exciting force and the random assembly phase is analyzed. Finally, the experimental asymmetric rotors are dynamically measured, combined with the asymmetric rotors’ geometric error measurement experiment. The experimental results confirm that the vibration amplitude of the assembly phase with the minimum exciting force is smaller than the vibration amplitude under the random assembly phase at three-speed modes, and the optimization rate reached 73.2% at 9000 rpm, which proves the effectiveness of the assembly method in minimizing the exciting force.