High-precision profile reconstruction is a key issue in the profile detection and visualization of aero-engine blades. A method based on adaptive step size bat algorithm (ASSBA) for blade profile reconstruction and an adaptive mesh model for visualization analysis of the key machining errors are proposed. Firstly, the original bat algorithm (BA) is improved to introduce the global stage and local search stage. Then, combined with the node layer characteristics of the blade measurement data, the ASSBA is used to fit the optimal surface. Further, the adaptive mesh is planned on the blade profile to extract various evaluation parameters. Finally, the algorithm analysis and verification are carried out based on a certain type of blade. The results show this reconstruction method can get the fitted surface more quickly and accurately than other iterative methods. Simultaneously, the visualization method and corresponding software system can intuitively visualize the blade profile error, the twist deformation error, the swept deformation error, the bending deformation error and the cross-section line profile error.

中文翻译：

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基于自适应步长蝙蝠算法和加工误差可视化的航空发动机叶片轮廓重建

高精度剖面重建是航空发动机叶片剖面检测和可视化的关键问题。提出了一种基于自适应步长蝙蝠算法(ASSBA)的叶片轮廓重建方法和用于关键加工误差可视化分析的自适应网格模型。首先对原有的蝙蝠算法（BA）进行改进，引入全局阶段和局部搜索阶段。然后结合叶片测量数据的节点层特征，利用ASSBA拟合最优表面。此外，在叶片轮廓上规划自适应网格以提取各种评估参数。最后，针对某类叶片进行了算法分析和验证。结果表明，与其他迭代方法相比，该重建方法能够更快、更准确地得到拟合曲面。同时，可视化方法和相应的软件系统可以直观地可视化叶片轮廓误差、扭曲变形误差、扫掠变形误差、弯曲变形误差和截面线形误差。