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基 于 叶 端 定 时 的 转 子 叶 片 动 应 变 重 构不 确 定 性 量 化

  • Xi'an Jiaotong University
  • Aero Engine Corporation of China

科研成果: 期刊稿件文章同行评审

5 引用 (Scopus)

摘要

Based on the theory of blade non‑contact dynamic strain reconstruction,research on the uncertainty quantification method of dynamic strain reconstruction was carried out. Accord‑ ing to the variance composition theorem, a model of the blade reconstructed dynamic strain un‑ certainty for quantitative analysis was established. A simulated rotor blade was used as the research object,and the rotation experiment was carried out. The circumferential Fourier Fitting was used to obtain the amplitude of measuring point under different blade tip timing sensor layouts, and the maximum entropy method was adopted to fit the probability density function of the amplitude distribution,which could be used to determine the uncertainty parameters of the blade‑tip‑timing vibration measurement. The finite element model of the blade was modified by combining the Kriging proxy model and the resonant frequency of the test. The displacement‑strain conversion factors of the key measuring points were obtained,and the uncertainty parameters of the conver‑ sion factor considering the uncertainty of the resonance speed and measuring point position were obtained. The mean value, standard uncertainty and inclusion interval of the reconstructed dynamic strain were obtained and compared with the measured data of the strain gauge. Results showed that except for the measuring point A of No. 5 blade,the measured dynamic strains were all within the 95% confidence interval of the reconstructed dynamic strain, and the dynamic strain reconstruction error of the strain gauges of all blades didn’t exceed 15%.

投稿的翻译标题Uncertainty quantification of rotor blade dynamic strain reconstruction based on blade tip timing
源语言繁体中文
页(从-至)1456-1468
页数13
期刊Hangkong Dongli Xuebao/Journal of Aerospace Power
37
7
DOI
出版状态已出版 - 1 7月 2022

关键词

  • Kriging proxy model
  • blade tip timing
  • dynamic strain reconstruction
  • maximum entropy method
  • uncertainty quantification

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