Rotor assembly is a core tache in the whole process of aero-engine manufacturing. Preventing out-of-tolerance of concentricity is one of the primary tasks. Conventional assembly approaches are based on a manual test with the dial indicator, depending on experience appraises, which lack systematic and quantitative precision design theory. As a result, two issues need to be solved: the modeling problem of complicated geometric variations in three-dimensions, as well as the abnormal distribution of ubiquitous actual deviations. This work attempts to propose a novel probabilistic approach for three-dimensional variation analysis in rotor assembly. Based on rotor’s revolving characteristics and multistage stacking process, Jacobian–Torsor model is adopted to establish the variation propagation, and Pearson distribution family is used to derive the probability density function, which can quickly determine the variation distribution pattern and efficiently perform statistical variation analysis. A real case of mechanical assemblies consisting of revolving axisymmetric components is concerned. The results show that the suggested method has a similar accuracy, but much higher efficiency than conventional methods. Calculations agree with the experimentations, and the probability distribution type of the part’s variation has an appreciable impact on the final assembly precision.

转子总成是航空发动机制造全过程的核心环节。防止超出同心度公差是主要任务之一。传统的装配方式是通过百分表手工测试，依靠经验评价，缺乏系统化、定量化的精密设计理论。因此，需要解决两个问题：三维复杂几何变化的建模问题，以及无处不在的实际偏差的异常分布。这项工作试图为转子装配中的三维变化分析提出一种新的概率方法。根据转子的旋转特性和多级叠加过程，采用Jacobian-Torsor模型建立变化传播，使用皮尔逊分布族推导概率密度函数，可以快速确定变异分布模式，高效进行统计变异分析。涉及由旋转轴对称部件组成的机械组件的真实案例。结果表明，所提出的方法具有相似的准确度，但比传统方法具有更高的效率。计算与实验相符，零件变异的概率分布类型对最终装配精度有明显影响。结果表明，所提出的方法具有相似的准确度，但比传统方法具有更高的效率。计算与实验相符，零件变异的概率分布类型对最终装配精度有明显影响。结果表明，所提出的方法具有相似的准确度，但比传统方法具有更高的效率。计算与实验相符，零件变异的概率分布类型对最终装配精度有明显影响。