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發(fā)動(dòng)機葉片機器人精密砂帶磨削精度檢測技術(shù)
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西安交通大學(xué) 城市學(xué)院

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陜西省教育廳專(zhuān)項科學(xué)研究項目《面向復雜曲面的工業(yè)機器人拋光接觸狀態(tài)分析及拋光路徑規劃研究》(19JK0496)。


Precision inspection technology for precision grinding of engine blade robot
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    摘要:

    當前精密砂帶磨削精度檢測技術(shù)檢測準確率低,檢測效率差。為了解決上述問(wèn)題,引用發(fā)動(dòng)機機器人研究了一種新的精密砂帶磨削精度檢測技術(shù),對其精度數據進(jìn)行采集,將采集出的系統數據作為基礎信息來(lái)源,獲取葉片零部件的點(diǎn)云信息,處理機器人的工作主坐標系,通過(guò)三維激光掃描獲取葉片機器人的準確信息,同時(shí)配以打磨剖光操作,以PCA算法解析,進(jìn)一步將數據集簡(jiǎn)化,根據數據主要分布規律選擇合適的算法加工位置與范圍,在三維空間中,將點(diǎn)分別對應坐標軸中的點(diǎn)進(jìn)行匹配,通過(guò)對磨削接觸面的輪廓以及磨削表面完整性進(jìn)行分析,以實(shí)現對發(fā)動(dòng)機葉片機器人精密砂帶磨削精度的檢測。實(shí)驗結果表明,相較于傳統檢測技術(shù),發(fā)動(dòng)機葉片機器人精密砂帶磨削精度檢測技術(shù)檢測精度提高了31.28%,檢測誤差降低了15.21%。

    Abstract:

    The current precision belt grinding precision detection technology has low detection accuracy and poor detection efficiency. In order to solve the above problems, a new precision grinding belt grinding precision detection technology was studied with reference to the engine robot. The accuracy data was collected, and the collected system data was used as the basic information source to obtain the point cloud information of the blade parts. The main coordinate system of the working robot is processed, and the accurate information of the blade robot is obtained by 3D laser scanning. At the same time, the polishing operation is performed, and the PCA algorithm is used to analyze, further simplify the data set, and select the appropriate algorithm processing position according to the main distribution law of the data. Scope, in the three-dimensional space, the points are matched to the points in the coordinate axes respectively, and the contour of the grinding contact surface and the surface integrity of the grinding are analyzed to realize the precision of the grinding precision of the engine blade robot . The experimental results show that compared with the traditional detection technology, the detection precision of the precision grinding belt grinding precision detection technology of engine blade robot is improved by 31.28%, and the detection error is reduced by 15.21%.

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引用本文

李娜娜,萬(wàn)中.發(fā)動(dòng)機葉片機器人精密砂帶磨削精度檢測技術(shù)計算機測量與控制[J].,2020,28(7):39-44.

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  • 收稿日期:2019-11-22
  • 最后修改日期:2019-12-09
  • 錄用日期:2019-12-09
  • 在線(xiàn)發(fā)布日期: 2020-07-14
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