摘要
为了解决燃气轮机叶片后缘轮廓参数辨识的难题,提出了自适应迭代最小二乘法。通过三维激光测量系统得到叶片后缘三维轮廓点云数据,测量精度±5μm,使用该算法对后缘所有截面进行拟合,拟合精度±0.001 mm。通过在不同程度高斯噪声下仿真后缘测量数据,对比分析了两种算法的拟合效果。自适应迭代最小二乘法对叶片后缘轮廓的高精度、高效率参数辨识有着重要意义。
In order to solve the problem of the parameter identification of gas turbine blade trailing edge profile,an adaptive and iterative least-square is presented.The blade trailing edge three dimensional profile point cloud data are obtained through three-dimensional laser measurement system,the measuring precision is ±5μm,the algorithms is used to fit all cross-section of trailing edge,the fitting precision is ±0.001 mm.The results of two kinds of algorithms are compared and analyzed based on simulation measured-data of trailing edge under varying degrees of Gaussian noise.Adaptive and iterative least-square is of great significance to the highprecision and efficient parameter identification of gas turbine blade trailing edge profile.
出处
《测控技术》
CSCD
2016年第4期39-42,共4页
Measurement & Control Technology
基金
国家自然科学基金(11072063)
关键词
叶片后缘
最小二乘法
三维激光测量
参数辨识
trailing edge of blades
least-square
three-dimensional laser measurement
parameter identification
