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基于最小二乘的復雜曲面檢測方法研究
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遼寧省數控機床信息物理融合與智能制造重點(diǎn)實(shí)驗室,,,,,

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TG659

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國家自然科學(xué)基金(61603262,61403071),沈陽(yáng)工學(xué)院i5智能制造研究所項目(i5201701)


Research on Complex Surface Detection Based on Least Squares
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    摘要:

    提出一種基于數模打點(diǎn)、陣列粘貼、迭代法建立坐標系、改進(jìn)最小二乘法運算的復雜曲面檢測方法。給出了六點(diǎn)迭代法建立復雜曲面檢測坐標系的算法步驟,再結合3-2-1法進(jìn)行了坐標系的創(chuàng )建。提出利用陣列粘貼等方法進(jìn)行檢測點(diǎn)的快速生成并對復雜曲面進(jìn)行檢測,并采用本文給出的改進(jìn)最小二乘法進(jìn)行計算機數據處理。本文檢測方法有效克服了傳統方法測量時(shí),測頭易發(fā)生干涉,同時(shí)存在檢測項目多、檢測效率低等缺點(diǎn),能有效提高復雜曲面檢測的精度并縮短檢測時(shí)間。通過(guò)多次的檢測分析,結果表明本文提出的方法易于編程,測量迅速,測量結果準確、可靠。借助于本文方法可以解決從事檢測行業(yè)及相關(guān)人員在三維檢測中的短板,提高檢測的效率和解決問(wèn)題的能力。

    Abstract:

    A complex surface detection method based on numerical simulation, array pasting, iterative method to establish coordinate system and improved least square method is proposed. The six-point iterative method is given to establish the algorithmic steps of the complex surface detection coordinate system. Then the 3-2-1 method is used to create the coordinate system. This paper proposes the method of array sticking and other methods to detect the point quickly and detect the complex surface. The improved Least Square Method proposed in this paper is used for computer data processing. The detection method in this paper effectively overcomes the shortcomings of the probe when the traditional method is used for measuring, and it has the disadvantages of multiple detection items and low detection efficiency, which can effectively improve the accuracy of complex surface detection and shorten the detection time. Through multiple tests and analysis, the results show that the proposed method is easy to program, the measurement is rapid, and the measurement results are accurate and reliable. With this method, we can solve the short board in the detection industry and related personnel in the three-dimensional detection, improve the detection efficiency and ability to solve problems.

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劉業(yè)峰,王婷,趙元,孫福英,張磊,段旭明.基于最小二乘的復雜曲面檢測方法研究計算機測量與控制[J].,2018,26(12):52-57.

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  • 收稿日期:2018-05-19
  • 最后修改日期:2018-07-02
  • 錄用日期:2018-07-03
  • 在線(xiàn)發(fā)布日期: 2018-12-21
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