多目标约束的精锻叶片几何重构优化算法

新型航空发动机已部分采用精密锻造工艺提高叶片的制造精度和效率。然而，精锻后的叶身型面与设计模型存在几何偏差，导致依据设计模型加工后的进/排气边与精锻的叶身型面不能很好地匹配。为了解决该问题，提出一种面向精锻叶片自适应加工的几何重构方法。首先，建立基于公差约束配准的目标函数，并采用粒子群优化（PSO）算法求解目标函数。其次，提出基于叶身变形趋势预测进/排气边轮廓的光顺重构算法。最后，通过精锻叶片自适应数控加工实验对提出的方案和算法进行验证。实验结果表明，该方案可以有效重构出合格的工艺模型，满足精锻叶片的精密数控加工要求。

Multi-objective optimization algorithm for geometric reconstruction of precision forged blade

The precision forging technology is the favored means to improve the machining accuracy and efficiency of aero-engine blade manufacturing. However, there is still a certain geometric deviation between the forged blade surface and the design model, causing the edges of the blade machined based on the design model cannot match well with the blade body. To solve this issue, a geometric reconstruction method for adaptive machining of the precision forged blade is proposed. The objective function of match is established based on the tolerance constraint, and the Particle Swarm Optimization (PSO) algorithm for solving this objective function is presented. A smoothing reconstruction algorithm is proposed to predict the profile of the edge shape based on deformation trend of the blade surface. Experiments verify effectiveness of the approach and algorithm proposed in this paper. The results show that this method can reconstruct a qualified model for high-efficiency and precision requirements of adaptive machining of the precision forged blade. This approach is finally verified with a precision forged blade by the adaptive CNC machining.