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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2023, Vol. 44 ›› Issue (6): 427203-427203.doi: 10.7527/S1000-6893.2022.27203

• Material Engineering and Mechanical Manufacturing • Previous Articles    

Statistics on geometric uncertainties of casting blades in low-pressure turbines

Jiaqi LUO1(), Zeshuai CHEN1, Zhengping ZOU2,3, Fei ZENG4, Pengcheng DU2   

  1. 1.School of Aeronautics and Astronautics,Zhejiang University,Hangzhou 310027,China
    2.Research Institute of Aero-Engine,Beihang University,Beijing 102206,China
    3.National Key Laboratory of Science and Technology on Aero-Engine and Aero-Thermodynamics,Beihang University,Beijing 102206,China
    4.AECC Hunan Aviation Powerplant Research Institute,Zhuzhou 412002,China
  • Received:2022-03-28 Revised:2022-04-21 Accepted:2022-05-30 Online:2022-06-09 Published:2022-06-08
  • Contact: Jiaqi LUO E-mail:jiaqil@zju.edu.cn
  • Supported by:
    National Science and Technology Major Project(J2019-II-0012-0032);National Natural Science Foundation of China(51976183)

Abstract:

It has been well known that there are different sources for geometric deviations of casting turbine blades. Statistical study of geometric deviations benefits not only the discovery of deviation sources and statistical modelling, but also the evaluation of blade geometric accuracy. This paper gives a statistical study of on geometric uncertainties of casting blades in low-pressure turbines. First, the geometric deviations of one thousand casting blades in the low-pressure turbine are preliminary studied. By principal component analysis, the basic modes of geometric deviations are extracted, and the main sources are distinguished, including movement error, twist error and profile error. Then, an error decomposition method based on the optimization strategy is introduced, which can be used to extract different kinds of errors. Statistical study finds that the Probability Density Functions (PDFs) of global geometric deviations are close to Gauss distributions. Finally, blade profile deviations are statistically analyzed. The results demonstrate that in comparison with the original casting blades, the geometric dispersion degree and the profile tolerance error of the corrected blades without global geometric deviations are significantly decreased, and the percentage of qualified blades is significantly increased. Besides, statistical study on profile tolerance at some specified positions on the blade demonstrates that the probability density functions of profile tolerance are also close to Gauss distributions.

Key words: geometric variation, uncertainty, low-pressure turbine, deviation decomposition, blade profile error, probability statistics

CLC Number: