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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2022, Vol. 43 ›› Issue (9): 625100.doi: 10.7527/S1000-6893.2021.25100

• Special Topic: Operation Safety of Aero-engine • Previous Articles     Next Articles

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

FAN Yongsheng1, YANG Xiaoguang1, SHI Duoqi1, TAN Long1, HUANG Weiqing2   

  1. 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:2020-12-14 Revised:2021-01-10 Online:2022-09-15 Published:2021-03-09
  • Supported by:
    National Science and Technology Major Project (2017-IV-0012-0049, J2019-IV-0017-0085); National Natural Science Foundation of China (51775019, 12172021)

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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