Volume 37, Number 4, August 2019
|Page(s)||767 - 773|
|Published online||23 September 2019|
Research on Influence of CMM Sampling Points on Detection of Feature Parameters for Turbine Blade
School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, China
Sampling plan is an essential part for measuring profile of turbine blade with coordinates measuring machine(CMM), and the detection of feature parameters is a key component of turbine blade inspection. However, the influence of the sampling strategy on the blade feature parameters evaluation has been rarely studied. In order to understand the correlation between the sampling strategy and the accuracy of blade profile feature parameters, firstly, the extraction methods of turbine blade feature parameters were proposed, and these methods were compiled into an executable program TBGeoInspect. Secondly, based on the level principle, the unified mathematical representations of uniform sampling, curvature-based sampling, chord deviation sampling, weighted curvature-based sampling, and curvature-arc length sampling were given. The effect of these five sampling algorithms on the accuracy of turbine blade profile feature parameters was gained through simulation and experiment results of blade sampling. The results validate that the uncertainty of turbine blade feature parameters and sectional curve fitting error are lowest with curvature-arc length sampling method under the same number of sampling points.
Key words: turbine blade / feature parameter / mean camber line / wall thickness / sampling strategy
关键字 : 涡轮叶片 / 特征参数 / 中弧线 / 壁厚 / 采样
© 2019 Journal of Northwestern Polytechnical University. All rights reserved.
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