| 基于神经网络的反求测量系统的标定 |
| |
| 引用本文： | 陈剑虹,刘振凯,乔志林,卢秉恒. 基于神经网络的反求测量系统的标定[J]. 中国制造业信息化, 1999, 0(3) |
| |
| 作者姓名： | 陈剑虹 刘振凯 乔志林 卢秉恒 |
| |
| 作者单位： | 西安交通大学 |
| |
| 摘 要： | 在层去图象法测量系统中，由于诸多因素的影响，物体的空间坐标与截面图象坐标之间存在着复杂的非线性映射关系。如果采用完全理想条件和线性几何失真方法来标定系统，则会影响测量精度，为此提出了一种基于神经网络的标定方法，显著地提高了测量系统的精度。
|
| 关 键 词： | 反求工程 标定 层去图象法 神经网络 |
Calibration Methods Based on Neural Network for Cross-sectional Imaging Measurement System |
| |
| Chen Jianhong Liu Zhenkai Qiao Zhilin Lu Bingheng. Calibration Methods Based on Neural Network for Cross-sectional Imaging Measurement System[J]. Manufacture Information Engineering of China, 1999, 0(3) |
| |
| Authors: | Chen Jianhong Liu Zhenkai Qiao Zhilin Lu Bingheng |
| |
| Abstract: | There is complex nonlinear mapping between the object space and image space due to many factors in cross-sectional imaging measurement system. The measurement accuracy will be low if the ideal or linear conditions are used to calibrate the system. A calibration method based on neural network is presented. The results show a remarkable improvement of the measurement accuracy. |
| |
| Keywords: | Reverse engineering Calibration Neural network Cross-sectional imaging measurement |
| 本文献已被 CNKI 等数据库收录！ |
