Research on blade statistics measurement registration planning technology

IF 1.9 3区工程技术 Q3 ENGINEERING, MANUFACTURING

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture Pub Date : 2023-07-05 DOI:10.1177/09544054231182549

Yun Zhang, Z. Xu, Jingqing Liu, Zhitong Chen, Zhengqing Zhu

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引用次数: 0

Abstract

Blade has the characteristics of high machining quality of complex curved surface. If there is no benchmark before machining, it is impossible to judge whether the blades before machining are qualified. Therefore, it is necessary to analyze the blade measurement data. Due to the large measurement point error and disordered distribution, it is necessary to optimize the blade registration. Therefore, blade model registration and positioning is particularly important in blade shape detection and analysis. First, preregistration is carried out based on the six point optimization selection of the blade. After preregistration, the selection method of registration control point set based on theoretical model and statistical error is proposed, planning the registration datum point set on the blade model. The registration control point set is obtained through the registration operation between the measurement data and the registration reference point set. Finally, based on the stability and reliability of important sampling sensitivity and statistical error, obtain the probability density function of error normal distribution statistics samples and important samples. The selection of statistical control points and the rationality of the objective function were verified. The stability/reliability of the statistical alignment point selection is proved to be feasible. The statistical registration deviation is [0.015,0.026] mm, and the ICP registration deviation is [0.031,0.035] mm. The average deviation of statistics registration is about 0.013 mm smaller than the average deviation of ICP registration. The deviation of statistical sampling points is about 0.0214 mm, and that of traditional sampling points is about 0.0275 mm. The deviation of statistical sampling points is about 0.0061 mm smaller than that of traditional sampling points. It meets the requirements of rapid, high efficiency and high precision measurement for aeroengine blades.

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叶片统计测量配准规划技术研究

叶片具有复杂曲面加工质量高的特点。如果在加工前没有基准，就无法判断加工前的叶片是否合格。因此，有必要对叶片测量数据进行分析。由于测点误差大且分布无序，对叶片配准进行优化是必要的。因此，叶片模型的配准与定位在叶片形状检测与分析中显得尤为重要。首先，基于叶片的六点优化选择进行预配准。在预配准后，提出了基于理论模型和统计误差的配准控制点集选择方法，在叶片模型上规划配准基准点集。通过测量数据与配准参考点集的配准操作，得到配准控制点集。最后，基于重要样本的灵敏度和统计误差的稳定性和可靠性，得到统计样本和重要样本正态分布误差的概率密度函数。验证了统计控制点的选取和目标函数的合理性。验证了统计对准点选择方法的稳定性和可靠性。统计配准偏差为[0.015,0.026]mm, ICP配准偏差为[0.031,0.035]mm，统计配准的平均偏差比ICP配准的平均偏差小0.013 mm左右。统计采样点的误差约为0.0214 mm，传统采样点的误差约为0.0275 mm。统计采样点的误差比传统采样点的误差约小0.0061 mm。满足了航空发动机叶片快速、高效、高精度测量的要求。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 工程技术-工程：机械

CiteScore

5.10

自引率

30.80%

发文量

167

审稿时长

5.1 months

期刊介绍： Manufacturing industries throughout the world are changing very rapidly. New concepts and methods are being developed and exploited to enable efficient and effective manufacturing. Existing manufacturing processes are being improved to meet the requirements of lean and agile manufacturing. The aim of the Journal of Engineering Manufacture is to provide a focus for these developments in engineering manufacture by publishing original papers and review papers covering technological and scientific research, developments and management implementation in manufacturing. This journal is also peer reviewed. Contributions are welcomed in the broad areas of manufacturing processes, manufacturing technology and factory automation, digital manufacturing, design and manufacturing systems including management relevant to engineering manufacture. Of particular interest at the present time would be papers concerned with digital manufacturing, metrology enabled manufacturing, smart factory, additive manufacturing and composites as well as specialist manufacturing fields like nanotechnology, sustainable & clean manufacturing and bio-manufacturing. Articles may be Research Papers, Reviews, Technical Notes, or Short Communications.