引用本文: | 梁建成,李圣怡,温熙森,等.在线估计表面粗糙度的神经网络多传感器融合方法.[J].国防科技大学学报,1995,17(2):43-47.[点击复制] |
Liang Jiancheng,Li Shengyi,Wen Xisen,et al.Multisensor Fusion Via Neural Networks for On-line Estimating Surface Roughness[J].Journal of National University of Defense Technology,1995,17(2):43-47[点击复制] |
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在线估计表面粗糙度的神经网络多传感器融合方法 |
梁建成, 李圣怡, 温熙森, 杨林, 吴学忠 |
(国防科技大学 机械电子工程与仪器系 湖南 长沙 410073)
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摘要: |
针对机床智能加工对加工状况监测的要求,文中提出一种在线估计表面粗糙的神经网络多传感器融合方法,用该方法可获得表面粗糙度的较好估计。文中论述了该方法的特征提取,维数压缩和归一化等预处理方法,神经网络的构造及训练等内容。仿真表明,该方法是可行和有效的。 |
关键词: 表面粗糙度 神经网络 多传感器融合 估计 |
DOI: |
投稿日期:1995-01-05 |
基金项目:国家自然科学基金资助项目 |
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Multisensor Fusion Via Neural Networks for On-line Estimating Surface Roughness |
Liang Jiancheng, Li Shengyi, Wen Xisen, Yang Lin, Wu Xuezhong |
(Department of Mechatronics and Instruments)
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Abstract: |
An on-line surface roughness estimating method based on multisensor fusion via neural networks is presented for the requirement of machine tool intelligent machining. The better estimation of surface roughness can be obtained by the method. The feature selection、dimension compression、normalization and neural networks construction of the method are discussed in this paper. The simulation results show that the proposed method is feasible and effective. |
Keywords: surface roughness neural network multisensor fusion estimation |
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