服役涡轮叶片筏化判废：定量表征及阈值确定

范永升; 杨晓光; 石多奇; 谭龙; 黄渭清

doi:10.7527/S1000-6893.2021.25100

航空学报 >

2022 , Vol. 43 >Issue 9: 625100 - 625100

DOI: https://doi.org/10.7527/S1000-6893.2021.25100

航空发动机运行安全专栏

服役涡轮叶片筏化判废：定量表征及阈值确定

范永升 ,
杨晓光 ,
石多奇 ,
谭龙 ,
黄渭清

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1. 北京航空航天大学能源与动力工程学院, 北京 102206;
2. 北京理工大学机械与车辆学院, 北京 100081

收稿日期: 2020-12-14

修回日期: 2021-01-10

网络出版日期: 2021-04-27

基金资助

国家科技重大专项(2017-IV-0012-0049, J2019-IV-0017-0085)；国家自然科学基金(51775019, 12172021)

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Rafting-waste judgement of serviced turbine blades: quantitative characterization and threshold determination

FAN Yongsheng ,
YANG Xiaoguang ,
SHI Duoqi ,
TAN Long ,
HUANG Weiqing

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1. School of Energy and Power Engineering, Beihang University, Beijing 102206, China;
2. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China

Received date: 2020-12-14

Revised date: 2021-01-10

Online published: 2021-04-27

Supported by

National Science and Technology Major Project (2017-IV-0012-0049, J2019-IV-0017-0085); National Natural Science Foundation of China (51775019, 12172021)

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摘要

由单晶/定向凝固镍基高温合金制造的航空发动机涡轮叶片, 服役时微观组织不可避免地发生一种称之为“筏化”的变化, 降低叶片的力学性能, 是发动机涡轮叶片大修判废和大修间隔确定的重要考虑因素。提出了基于数字图像算法的微观组织特征提取算法, 并用于提取不同筏化状态涡轮叶片材料的微观组织特征, 进而建立了筏化程度的定量表征参数。随后, 通过对不同筏化程度的高温合金开展高温疲劳试验, 建立了筏化因子与疲劳性能衰减的定量关联, 获得了涡轮叶片服役筏化的量化状态阈值, 从疲劳性能退化的角度建立了服役涡轮叶片微观组织筏化判废的基本方法, 为解决过去筏化程度与力学性能衰减关系不清楚、筏化判废采用图像目视观察定性对比不确定性大等问题确定了科学基础和技术路径。最后, 针对某型航空发动机不同服役时长的高压一级涡轮叶片应用此方法, 获得了真实服役涡轮叶片不同位置筏化程度的定量分布情况。

关键词： 涡轮叶片; 筏化; 服役; 图像处理; 高温疲劳; 定量表征; 阈值

本文引用格式

范永升 , 杨晓光 , 石多奇 , 谭龙 , 黄渭清 . 服役涡轮叶片筏化判废：定量表征及阈值确定[J]. 航空学报, 2022 , 43(9) : 625100 -625100 . DOI: 10.7527/S1000-6893.2021.25100

Abstract

The microstructure of the turbine blades made by single crystal/directionally solidified Ni-based superalloys inevitably undergoes a degradation called rafting during service, which reduces the mechanical properties of the blade. Thus, rafting is an important factor in scrapping of turbine blades and in determining the overhaul interval. In the present work, an approach for microstructural feature extraction was developed based on the digital image algorithm to extract the microstructure characteristics of the turbine blades in different rafting states. Then, a quantitative characterization parameter of rafting extent is determined. The relationship between the quantitative rafting parameter and mechanical property deterioration was established by carrying out high temperature fatigue tests of the superalloys with different rafting states, which aims to solve the problems of uncertain relationship between rafting states and performance deterioration, and the poor accuracy of the artificial image comparison in the past. From the point of view of fatigue performance degradation, the present work established a basic method for microstructural rafting judgment of turbine blades in service. Finally, the proposed method was applied to a high pressure first-stage turbine blade with different service periods, and the quantitative distribution of rafting states of the real service blade was obtained.

Key words： turbine blade; rafting; service; image processing; high temperature fatigue; quantitative characterization; threshold

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