3D solid model retrieval for engineering reuse based on local feature correspondence

For engineering applications, a new design can be developed efficiently from an existing design with the same features, functions, and manufacturing properties. Although several techniques have been developed for assessing the similarity among models, most methods focus on the global shape of models. This work presents an innovative retrieval architecture that can be utilized to acquire similar mechanical artifacts based on the local feature correspondence. This work defines an attributed graph for a B-rep structure to retain the geometric and topological data from Standard for the Exchange of Product model data (STEP) format. Local feature correspondence is evaluated by identifying the size of the common subgraph from the graph descriptor. This work applies a novel scheme, called independent maximal cliques (IMC) detection, and a simulated annealing algorithm to solve the graph-matching problem. The association graph, which is used for IMC detection, is constructed from two attributed graphs while retaining their attributes. All independent maximal cliques, which represent the maximum number of common features between models, are identified using simulated annealing. Therefore, the retrieval framework can achieve the engineering goal of model reuse by measuring the local feature correspondence between solid models via IMC detection. The experimental results, obtained from the retrieval system built on the product data management (PDM) system, demonstrates the practicality of this work for 3D model retrieval for engineering reuse based on local feature correspondence.