Processing feature recognition and information extraction method for MBD model

Abstract

The invention provides a processing feature recognition and information extraction method for an MBD model. The method comprises the following steps: 1, analyzing the MBD model; 2, traversing the cylindrical surface, and identifying hole characteristics; 3, initializing an attribute adjacency graph storage matrix, and constructing an attribute adjacency graph; 4, traversing predefined processing features and feature sub-graphs thereof; 5, identifying all the machining feature surface sets of the type by using a sub-graph isomorphism method; 6, calculating the key geometric dimension accordingto the processing feature type; 7, extracting three-dimensional labeling information of the model; 8, extracting part annotation information; 9, interactively identifying self-defined processing characteristics; 10, visualizing a machining feature recognition result; 11, outputting a feature recognition and information extraction result in a structured manner. Through the steps, the machining feature surface set in the MBD model can be recognized, the key geometric dimension of the machining feature surface set can be automatically calculated, the three-dimensional annotation and annotation information of the part can be extracted, the final result is output in an XML form, and a good data foundation is laid for subsequent process design.

Description

technical field [0001] The invention provides an MBD model processing feature recognition and information extraction method, which is a processing feature recognition and information extraction method based on a model-based definition (Model-based Definition, MBD) model. Specifically, it refers to a processing feature recognition and information extraction method for analyzing MBD models, which can automatically decompose the input MBD model into a series of processing features, and extract the geometric information and process requirements of the processing features, so as to make decisions for subsequent processes. It provides data support and belongs to the field of Computer Aided Process Planning (CAPP). Background technique [0002] Computer Aided Process Planning (CAPP) is the bridge and link between design and manufacturing, and plays a connecting role in the process of product digital design and manufacturing, and is the key to improving the overall level of digital ...

AI Technical Summary

Problems solved by technology

However, in the existing research, the operating efficiency of the feature recognition algorithm is relatively low. At the same time, the existing achievements are mostly aimed at the CAD geometric model, and the research on the MBD model is less. The present invention overcomes the shortcomings of the above research. Application Architecture, CAA) carried out the secondary development of the modeling software CATIA (Computer Aided Three-dimensional Interactive Application, namely CATIA), and proposed a processing feature recognition and information extraction method for the MBD model

Images