利用稳健特征值法(REM)，通过一系列实验建立了平面参数与航空发动机高压压气机(HPC)转子零/组件同心度之间的偏差传递模型；通过对比各级零件偏心距以及止口端面圆跳动量的计算值与实测值，验证了所建模型的可靠性，并对其贡献率进行分析.为了有效提高HPC转子零/组件同心度，采用遗传算法(GA)确定各级零件的最佳安装角.结果表明，所提出的REM-GA方法适用于连续组合堆栈过程，可使各级零件的同心度提高50%以上，所获零件1、零件2和零件3的最佳安装角分别为6.225,3.422,5.983rad.
Using robust eigenvalue method (REM), deviation propagation model was built to describe the relationship between the plane parameters and the concentricity of high pressure compressor (HPC) rotors in aero-engine assembly through experiments. The calculated values and measured values of parts eccentricity and circle run-out of mounting face were compared and the results verified the reliability of the model. In addition, contribution analysis was realized. In order to effectively improve the concentricity of HPC rotors, genetic algorithm (GA) was adopted to determine the optimal installation angles for each part. The results showed that the proposed REM-GA method was suitable for continuous process of stacked assembly and could improve the concentricity of each part by over 50 percent, and the obtained optimal installation angles were 6.225, 3.422 and 5.983 rad respectively.
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