| 基于RBF通过样件外形反求天线罩模具复杂曲面的方法 |
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| 引用本文： | 于霖冲,焦俊婷,白广忱.基于RBF通过样件外形反求天线罩模具复杂曲面的方法[J].制造技术与机床,2005(7):19-21. |
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| 作者姓名： | 于霖冲 焦俊婷 白广忱 |
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| 作者单位： | 1. 嘉应学院,广东,梅州,514015;北京航空航天大学,北京,100083
2. 北京航空航天大学,北京,100083 |
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| 摘 要： | 通过天线罩样件的外形数据,结合天线罩制造过程中的变形数据,反求天线罩模具复杂曲面.RBF神经网络具有很强的非线性逼近能力,模具曲面的重构精度高并且网络训练速度快.将RBF网络输出数据输入到CITIA的数字曲面编辑器对模具曲面进行造型,该方法具有很高的实用推广价值.
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| 关 键 词： | 模具 曲面造型 反求 |
| 修稿时间： | 2004年10月27 |
Surface Model of Reverse Engineering Mould via Sample Based on RBF |
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| YU Linchong,JIAO Junting,BAI Guangchen.Surface Model of Reverse Engineering Mould via Sample Based on RBF[J].Manufacturing Technology & Machine Tool,2005(7):19-21. |
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| Authors: | YU Linchong JIAO Junting BAI Guangchen |
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| Abstract: | The aim of the research is to reconstruction mould surface via shape data of sample radar-dome collected by reverse engineering technology. Radial Basis Function (RBF) neural network has strong capability of nonlinear approximation with high reconstructing accuracy and fast training rate. The surface model of radar-dome mould can be get by inputting the results of RBF into CATIA digital surface editor. This method is valuable to practice and generalize. |
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| Keywords: | RBF CATIA |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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