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神经网络在逆向工程中进行三维实体特征识别
引用本文:卞向娟,龚友平,刘加海.神经网络在逆向工程中进行三维实体特征识别[J].机械,2006,33(7):33-35.
作者姓名:卞向娟  龚友平  刘加海
作者单位:1. 浙江科技学院,求是应用技术学院,浙江,杭州,310027
2. 浙江大学,化工机械研究所,浙江,杭州,310027
3. 浙江大学,信息学院,浙江,杭州,310027
摘    要:介绍了一种基于神经网络直接从测量数据中提取三维实体特征的方法,包括以下几个部分:(1)点云边点识别和区域分割;(2)对点云边点进行拟合,形成特征边,并进行特征编码;采用ANN进行特征识别;(3)由边特征信息提取特征参数,构造三维实体特征。由神经网络方法直接提取实体特征使逆向工程集成制造系统的建立更为方便。

关 键 词:逆向工程  特征识别  数据处理  神经网络
文章编号:1006-0316(2006)07-0033-03
收稿时间:2006-03-06
修稿时间:2006-03-06

Solid Feature Recognition for Reverse Engineering using Neural Networks
BIAN Xiang-juan,GONG You-ping,LIU Jia-hai.Solid Feature Recognition for Reverse Engineering using Neural Networks[J].Machinery,2006,33(7):33-35.
Authors:BIAN Xiang-juan  GONG You-ping  LIU Jia-hai
Affiliation:1.Zhejiang University of Science and Technology, Hangzhou 310027, China; 2.Zhejiang University, Hangzhou 310027, China
Abstract:This paper proposes a novel methodology for extracting solid features directly from a set of 3D scanned points.It uses the concepts of feature-based technology and artificial neural networks(ANNs).The use of ANNs has enabled the development of a flexible feature-based RE application that can be trained to deal with various features.The following four main tasks were investigated and implemented(:1).Edge detection and segmentation(2) ANN-based feature recognizer.(3) Construct solid modules with extracted parameters.The method to extract solid features using ANNs makes convenient to integrated reverse engineering process.
Keywords:reverse engineering  feature recognition  data processing  artificial neural networks
本文献已被 CNKI 维普 万方数据 等数据库收录!
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