|
|||||
|
|
| 用BP神经网络预测数控铣削变形 | |
| 引用本文： | 唐东红,孙厚芳,王洪艳. 用BP神经网络预测数控铣削变形[J]. 制造技术与机床, 2007, 0(8): 48-50 |
| 作者姓名： | 唐东红 孙厚芳 王洪艳 |
| 作者单位： | 1. 北京理工大学机械与车辆工程学院,北京,100081;装甲兵工程学院机械工程系,北京,100072 2. 北京理工大学机械与车辆工程学院,北京,100081 3. 装甲兵工程学院机械工程系,北京,100072 |
| 摘 要： | 铣削变形问题一直是影响薄壁件加工精度的瓶颈问题。由于引起铣削变形的因素较多以及铣削过程本身的复杂性,使得铣削参数与变形量之间的关系很难用准确的解析式来表示。因此借助神经网络的非线性映射能力,建立了变形量与铣削参数之间的非线性映射模型。结果显示:所建立的神经网络模型具有较高的精度和良好的泛化能力。该研究为进一步的铣削参数优化提供了保障。 |
| 关 键 词： | 铣削变形 BP神经网络 变形预测 |
| 修稿时间： | 2007-04-25 |
Milling Deformation Forecast with BP Neural Network |
|
| TANG Donghong,SUN Houfang,WANG Hongyan. Milling Deformation Forecast with BP Neural Network[J]. Manufacturing Technology & Machine Tool, 2007, 0(8): 48-50 | |
| Authors: | TANG Donghong SUN Houfang WANG Hongyan |
| Affiliation: | School of Machinery and Automobile Engineering, Beijing Institute of Technology, Beijing 100081, CHN; Department of Machinery Engineering, The Academy of Armored Forces Engineering, Beijing 100072, CHN |
| Abstract: | Processing deformation in the course of numerical control milling is a key problem of influencing the thin-walled workpiece's machining precision.Because of the complicacy of milling processing and many factors of causing deformation,it is difficult to obtain an exact analytical formula to express the intricate relationship of milling parameters and deformation.So with the help of ANN's powerful non-linear mapping ability,this paper has established a non-linear mapping model between milling parameters and deformation.Results show that the model is feasible and effective.This research will provide foundation for further optimization of milling parameters. |
| Keywords: | Milling Deformation BP Neural Networks Deformation Forecast |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |