神经网络在逆向工程中进行三维实体特征识别

Solid Feature Recognition for Reverse Engineering using Neural Networks

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。

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.