基于非参数多元统计过程控制的叶身型面加工误差控制方法

Profile machining error control method based on nonparametric multivariate statistical process control

Abstract

The invention discloses a profile machining error control method based on nonparametric multivariate statistical process control. The profile machining error control method is used for solving the technical problem that an existing profile machining error control method is poor in control accuracy. The technical scheme includes that the profile machining error control method based on nonparametric multivariate statistical process control is characterized by comprising the following steps: conducting process monitoring by means of data driving, timely conducting monitoring to the fluctuations of a process, and giving an alarm when the process is out of control; in a blade machining process, aiming at the characteristics of the complexity of profile quality characteristic and the high dimension of measured data, analyzing the requirements of deformation and tolerance changing, wherein deformation and tolerance changing often happen on a profile, and establishing quality control matrixes of profile outlines and bending and torsion deformation by means of the method of subsection of section lines; According to light weight processing to profile sampling points, conducting dimension reduction preprocessing to measured data by means of the method of equal-precision dissociation, and conducting screening to measured samples according to different accuracy requirements. By means of the profile machining error control method based on nonparametric multivariate statistical process control, the profile machining error control accuracy is improved.
本发明公开了一种基于非参数多元统计过程控制的叶身型面加工误差控制方法,用于解决现有叶身型面加工误差控制方法控制精度差的技术问题。技术方案是采用数据驱动进行过程监控,对过程的波动及时进行监控,当过程失控时进行报警。在叶片的加工过程中,针对叶型质量特性的复杂性和测量数据的高维的特点,分析叶身常发生的变形和变公差要求,采用截面线分段的方法建立起叶身的轮廓和弯扭变形的质量控制矩阵。对叶身型面采样点的轻量化处理,采用等精度离散的方法对测量数据进行降维预处理,按照不同的精度要求对测量样本进行筛选。提高了叶身型面加工误差的控制精度。

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Cited By (1)

    Publication numberPublication dateAssigneeTitle
    CN-103440416-ADecember 11, 2013西北工业大学基于扩展误差流的叶片加工过程误差预测方法