Automatic Order of Data Points in RE Using Neural Networks

Authors:
Xueming He;Chenggang Li;Yujin Hu;Rong Zhang;Simon X. Yang;Gauri S. Mittal
Affiliations:
School of Mechanical Science and Engineering, Huazhong University of Science and, Technology, Wuhan, 4300743 and School of Mechanical Engineering, Jiangnan University, Wuxi, China 214122;School of Mechanical Science and Engineering, Huazhong University of Science and, Technology, Wuhan, 4300743;School of Mechanical Science and Engineering, Huazhong University of Science and, Technology, Wuhan, 4300743;School of Science, Jiangnan University, Wuxi, China 214122;School of Engineering, University of Guelph, Guelph, Canada N1G2W1;School of Engineering, University of Guelph, Guelph, Canada N1G2W1
Venue:
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Year:
2008

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Abstract

In this paper, a neural network-based algorithm is proposed to explore the order of the measured data points in surface fitting. In computer-aided design, the ordered points serves as the input to fit smooth surfaces so that a reverse engineering (i.e. RE) system can be established for 3D sculptured surface design. The geometry feature recognition capability of back-propagation neural networks is explored in this paper. Scan or measuring number and 3D coordinates are used as the inputs of the proposed neural networks to determine the curve to which each data point belongs and the order number of data point in the same curve. In the segmentation process, the neural network output is segment number; while the segment number and sequence number in the same curve are the outputs when sequencing the points in the same curve. After evaluating a large number of trials with various neural network architectures, two optimal models are selected for segmentation and sequence. The proposed model can easily adapt for new data from another sequence for surface fitting. In comparison to Lin et al.'s (1998) method, the proposed algorithm neither needs to calculate the angle formed by each point and its two previous ones nor causes any chaotic phenomenon.