Semantic Based Retrieval For Heterogeneous3D CAD Models

It has become a common way in modern manufacturing enterprises to organize multi-disciplinary and geographically distributed engineers working together for product development temporally. These engineers use a variety of CAD systems to design products, thus a large number of heterogeneous CAD models are archived in enterprise databases. When developing new products, if proper CAD models can be found for design reuse, cost reduction and efficiency improvement can be achieved. However, it is difficult to search CAD models which meet engineers’ requirements from heterogeneous CAD model database. This dissertation focuses on issues about semantic based retrieval for heterogeneous3D CAD models, with its main contents being as follows:(1) A semantic based retrieval approach for heterogeneous CAD models is proposed.The proposed approach uses ontology mapping techniques to generate the uniform representation as semantic descriptors for heterogeneous CAD models; and automatically classifies CAD models to form hierarchical index structure with the aid of deep learning techniques. CAD model retrieval driven by classification is achieved, therefore the searching space is narrowed down and the retrieval performance is improved. In addition, improved VSM method and heuristic graph matching method is used to measure similarities between CAD models in a multi-mode way. Therefore various kinds of retrieval requirements from engineers are met.(2) A layered CAD feature ontology is constructed.This paper analyzes and concludes evaluation criteria of domain ontology, then constructs a CAD feature ontology for meeting the evaluation criteria. A layered representation structure is used in the constructed CAD feature ontology, which consists of B-rep layer, common feature ontology (CFO) layer and application feature ontology (AFO) layer. The CFO layer is divided into core version and extended version. The core version of CFO is constructed by referencing international standard-STEP part Ⅲ, in order to be specialized and authorized, and satisfy a variety of application requirements in CAD domain; the extended version of CFO is extended and modified specifically for heterogeneous CAD model retrieval.(3) An ontology based uniform description generation method for heterogeneous CAD models is proposed.Based on CAD feature ontology, the proposed method uses ontology mapping techniques and semantic reasoning techniques to generate the uniform semantic descriptors of heterogeneous CAD models for similarity measurement. When conducting ontology mapping from AFO to CFO, considering the specific internal and external structure of feature concepts, the proposed method chooses and combines multiple mappers, and evaluates similarities from multiple facets. Therefore the accuracy of ontology mapping is improved and the complex correspondences between feature concepts are identified. In addition, for guaranteeing the correctness and abundance of the semantic descriptors, the proposed method carries out semantic reasoning by formalizing domain knowledge into SWRL rules. Therefore contents of the uniform descriptions for heterogeneous CAD models are richer and more correct.(4) A classification and indexing method for CAD model based on deep learning technique is proposed.The proposed method first selects and extracts distinctive features from CAD models, then preprocesses them as high-dimensional input vectors for category recognition. Furthermore, by analogy with the thinking process of engineers, a deep neural network classifier for3D CAD models is constructed with the aid of deep learning techniques. To get an optimal solution, multiple strategies are appropriately chosen and applied in the training phase, which makes the constructed classifier achieve better performance. The proposed method applies deep learning techniques to automatically classify CAD models. Based on classification, a hierarchical index structure in CAD model database is formed. Therefore the classification accuracies and retrieval efficiencies of CAD models are improved.(5) A multi-mode similarity measurement method for3D CAD model is proposed. The proposed method uses improved VSM technique to measure similarities between CAD models in a vector-based way, inclining to recall and the efficiency; also uses heuristic graph match technique to measure similarities in a graph-based way, inclining to precision. The proposed method can satisfy engineers with different kinds of retrieval requirements.Based on the above studies, a prototype system named OB-HCMR is developed. The experimental results are provided to validate the main ideas of the proposed approaches.