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一种在产品曲面上分布测量点的新方法。

A New Method of Distribution of Measurement Points on Curvilinear Surfaces of Products.

作者信息

Magdziak Marek

机构信息

The Faculty of Mechanical Engineering and Aeronautics, Rzeszów University of Technology, al. Powstańców Warszawy 12, 35-959 Rzeszów, Poland.

出版信息

Sensors (Basel). 2019 Jun 13;19(12):2667. doi: 10.3390/s19122667.

DOI:10.3390/s19122667
PMID:31200514
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6630661/
Abstract

The article presents the method of selecting scanning lines along which coordinate measurements, performed by using, e.g., a coordinate measuring machine working in the single point probing mode, of free-form surfaces of measured workpieces may be conducted. Additionally, the proposed method supports the user of a coordinate measuring system during defining the number of measurement points distributed along selected scanning lines, thus deciding on the final distribution of measurement points on a measured surface of a product. The proposed method enables distributing measurement points in the parts of a measured product characterized by the worst quality of manufacturing. Moreover, the new method is very automated, therefore it affects the increase in the efficiency of coordinate measurements. The effect of using the new method is the non-uniform distribution of measurement points located on free-form surfaces. The presented algorithm takes into account the lengths of selected cross-sections of a measured curvilinear surface of an object, its geometrical complexity and the accuracy of the probe radius correction process. The decision regarding the number of measurement points is made on the basis of the accuracy analysis of the calculations of the corrected measurement points obtained during the probe radius correction process and the accuracy of the substitute model representing a measured curvilinear surface. Two methods of the correction process were used. The accuracy of the applied methods of the probe radius compensation process was estimated on the basis of the deviations calculated between corrected measurement points and scanning lines. The selection of scanning lines and the number of measurement points was realized by using the expert system based on the fuzzy logic. The paper presents the results of both simulation and experimental investigations. The numerical calculations were performed for two selected free-form surfaces. The verification of the developed algorithm was carried out during experimental investigations based on a measurement of a selected free-form surface. The conducted research was aimed at verifying the correctness of the distribution of measurement points generated using the proposed method. In the case of real measurements, measurement points should be located in the places of surfaces of products characterized by the largest deviations of manufacturing. The results of the conducted investigations confirm the usefulness of the developed algorithm for defining the distribution of measurement points on curvilinear surfaces in the coordinate measuring technique. Moreover, the way of implementation of the developed method of the distribution of measurement points in selected commercial measurement software is presented, thus enabling the use of the new method in the industry.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/510bb4119c09/sensors-19-02667-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/fcbc4eb756ec/sensors-19-02667-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/6c1b50fb38d0/sensors-19-02667-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/0dc25d71d993/sensors-19-02667-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/05a2b74b4c57/sensors-19-02667-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/57c4dcaae399/sensors-19-02667-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/8ce4e78114ec/sensors-19-02667-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/87bc79da0ca4/sensors-19-02667-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/e91340acd624/sensors-19-02667-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/5325d5f8e336/sensors-19-02667-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/f67c33225c4e/sensors-19-02667-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/93823effa797/sensors-19-02667-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/1d168de16d2c/sensors-19-02667-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/934c43e57a38/sensors-19-02667-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/4f5a24b27321/sensors-19-02667-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/04e703592480/sensors-19-02667-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/d6088368c89b/sensors-19-02667-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/510bb4119c09/sensors-19-02667-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/fcbc4eb756ec/sensors-19-02667-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/6c1b50fb38d0/sensors-19-02667-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/0dc25d71d993/sensors-19-02667-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/05a2b74b4c57/sensors-19-02667-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/57c4dcaae399/sensors-19-02667-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/8ce4e78114ec/sensors-19-02667-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/87bc79da0ca4/sensors-19-02667-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/e91340acd624/sensors-19-02667-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/5325d5f8e336/sensors-19-02667-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/f67c33225c4e/sensors-19-02667-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/93823effa797/sensors-19-02667-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/1d168de16d2c/sensors-19-02667-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/934c43e57a38/sensors-19-02667-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/4f5a24b27321/sensors-19-02667-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/04e703592480/sensors-19-02667-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/d6088368c89b/sensors-19-02667-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ced/6630661/510bb4119c09/sensors-19-02667-g017.jpg
摘要

本文介绍了一种选择扫描线的方法,沿着这些扫描线,可以使用例如工作在单点探测模式下的坐标测量机对被测工件的自由曲面进行坐标测量。此外,所提出的方法在定义沿选定扫描线分布的测量点数量时为坐标测量系统的用户提供支持,从而确定产品被测表面上测量点的最终分布。所提出的方法能够在被测产品制造质量最差的部分分布测量点。此外,新方法自动化程度很高,因此会提高坐标测量的效率。使用新方法的结果是位于自由曲面上的测量点分布不均匀。所提出的算法考虑了物体被测曲线曲面选定横截面的长度、其几何复杂性以及探头半径校正过程的精度。关于测量点数量的决策是基于在探头半径校正过程中获得的校正测量点计算的精度分析以及表示被测曲线曲面的替代模型的精度做出的。使用了两种校正过程方法。基于校正测量点与扫描线之间计算出的偏差来估计所应用的探头半径补偿过程方法的精度。扫描线的选择和测量点的数量是通过基于模糊逻辑的专家系统实现的。本文给出了模拟和实验研究的结果。对两个选定的自由曲面进行了数值计算。基于对选定自由曲面的测量,在实验研究过程中对所开发算法进行了验证。所进行的研究旨在验证使用所提出方法生成的测量点分布的正确性。在实际测量中,测量点应位于产品表面制造偏差最大的位置。所进行的研究结果证实了所开发算法在坐标测量技术中定义曲线曲面上测量点分布的有用性。此外,还介绍了在选定的商业测量软件中实现所开发的测量点分布方法的方式,从而使新方法能够在工业中得到应用。

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