A comparison of three design tree based search algorithms for the detection of engineering parts constructed with CATIA V5 in large databases

Abstract

This paper presents three different search engines for the detection of CAD-parts in large databases. The analysis of the contained information is performed by the export of the data that is stored in the structure trees of the CAD-models. A preparation program generates one XML-file for every model, which in addition to including the data of the structure tree, also owns certain physical properties of each part. The first search engine is specializes in the discovery of standard parts, like screws or washers. The second program uses certain user input as search parameters, and therefore has the ability to perform personalized queries. The third one compares one given reference part with all parts in the database, and locates files that are identical, or similar to, the reference part. All approaches run automatically, and have the analysis of the structure tree in common. Files constructed with CATIA V5, and search engines written with Python have been used for the implementation. The paper also includes a short comparison of the advantages and disadvantages of each program, as well as a performance test.

Content-based CAD assembly model retrieval: Survey and future challenges

“…Indeed, the similarity evaluation relies on the type of knowledge that the user wants to gain, and this influences what can be considered similar. Those issues are even more challenging when considering assemblies of CAD models; (ii) to get a meaningful similarity evaluation and to filter the results, extrinsic information is not enough, thus it is necessary to extract and use intrinsic information; (iii) the size of the databases has grown up exponentially in the last few years and a DMU can incorporate more than 1 million parts representing several terabytes of data [5], thus it is increasingly challenging to handle a large amount of produced data and to develop efficient searching and browsing methods and tools [6].…”