Research on Fast Process Benchmark Preparation Technology of Aero-Engine Casting Blades

CUI Chuanhui; LI Yimeng; CHEN Zhitong; ZHU Zhengqing

doi:10.16080/j.issn1671-833x.2023.19.067

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Research on Fast Process Benchmark Preparation Technology of Aero-Engine Casting Blades

更新时间：2025-10-30

- Research on Fast Process Benchmark Preparation Technology of Aero-Engine Casting Blades
- Aeronautical Manufacturing Technology Vol. 66, Issue 19, Pages: 67-74(2023)
- 作者机构：
  
  1. 北京航空航天大学,北京,100191
  2. 聊城大学,聊城,252000
  3. 中国航空制造技术研究院,北京,100024
- 作者简介：
- 基金信息：
- DOI：10.16080/j.issn1671-833x.2023.19.067
  CLC：
- Published：2023
- 稿件说明：
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崔传辉，李翊萌，陈志同，朱正清. 航空发动机铸造叶片工艺基准快速制备技术研究[J]. 航空制造技术, 2023, 66(19): 67-74.

CUI Chuanhui, LI Yimeng, CHEN Zhitong, ZHU Zhengqing. Research on Fast Process Benchmark Preparation Technology of Aero-Engine Casting Blades[J]. Aeronautical Manufacturing Technology, 2023, 66(19): 67-74.
崔传辉，李翊萌，陈志同，朱正清. 航空发动机铸造叶片工艺基准快速制备技术研究[J]. 航空制造技术, 2023, 66(19): 67-74. DOI： 10.16080/j.issn1671-833x.2023.19.067.

CUI Chuanhui, LI Yimeng, CHEN Zhitong, ZHU Zhengqing. Research on Fast Process Benchmark Preparation Technology of Aero-Engine Casting Blades[J]. Aeronautical Manufacturing Technology, 2023, 66(19): 67-74. DOI： 10.16080/j.issn1671-833x.2023.19.067.

摘要

高效数控加工是航空发动机叶片生产的发展趋势。针对目前铸造叶片数控加工中因基准不确定、难以实现高效加工的问题，提出了一种工艺基准快速制备技术。首先，通过在机测量或专用量具快速获取叶片型面数据。其次，设计含惩罚项的适应度函数，并采用改进的粒子群算法配准叶片型面数据及叶片理论模型。然后，以叶片叶身型面为基准在叶片榫头或辅助夹具上制备出工艺基准，保证后续数控加工中叶片装夹的准确性、快速性及可靠性。最后，经过实例验证，该技术可快速、高精度地实现铸造叶片基准的制备，满足了铸造叶片的高效生产需求。

Abstract

Efficient numerical control (NC) machining is the development trend of aero-engine blade production. In this thesis

a fast process benchmark preparation technology is proposed to solve the problem that it is difficult to achieve efficient machining due to the lack of benchmarks in the current NC machining of casting blades. Firstly

the blade profile data is quickly obtained by on-machine measurement or special measuring tools. Secondly

the fitness function with penalty term is designed

and the improved particle swarm optimization (PSO) algorithm is used to register the blade profile data and the blade theoretical model. Then

the process benchmark is prepared on the blade tenon or auxiliary fixture based on the blade body profile to ensure the accuracy

rapidity and reliability of blade clamping in subsequent NC machining. Finally

it is verified by examples that this technology can quickly and accurately realize the preparation of casting blade benchmarks

which meets the high-efficiency production requirements of casting blades.

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