Feature recognition for structural aerospace sheet metal parts

Abstract

With the advances in the aerospace industry, specialized tools, e.g. specialized modelling tools for aerospace sheet metal, have been developed to help at various stages of the product lifecycle. Although structural sheet metal parts form a significant portion of airplanes, there is no specialized automated feature recognition (AFR) method dedicated to them. AFR provides unparalleled contributions to various tasks in product lifecycle management, e.g. computer aided process planning, data retrieval and model difference identification. Despite the presence of a number of AFR methods for sheet metal parts, none of them are tuned to recognize the design semantics of the aerospace industry. This work proposes the first AFR method to recognize aerospace sheet metal features and design semantics to elevate the level of abstraction of the information from 3D STEP models. The proposed approach is to first preprocess the 3D STEP model in order to classify the topological elements of the boundary model (B rep model) and create relevant novel face sets and subtypes of faces, face boundaries and edges. Then, rule-based steps are used to recognize aerospace sheet metal features. The extracted features are described by their geometry, their relationship with other features and their pertinent parameters. As a result, the engineering semantics of 3D B-rep models of aerospace sheet metal parts are extracted and could be used for many applications like design reuse and model comparison.