Abstract
3D process plant models(PPMs) in the process industry normally consists of thousands of components. And, there are many similar local structures in the PPM. Due to the complex process flow, the topology relationship among components is very complicated. Therefore, designing a new PPM is quite time consuming. In order to shorten the design cycle, content based model retrieval for PPMs is an imperative requirement. In this paper, we propose a partial matching framework for PPMs based on graph matching aiming at improving design efficiency and realizing design reuse. The random walk algorithm is employed to distinguish similar local structures. Specifically, each PPM is represented by an undirected labeled graph. The local topological feature of each component is extracted based on the random walk algorithm. For partial matching, a subgraph isomorphism algorithm is introduced. The matching process is accelerated by using the local topological feature to generate an optimized initial state and alleviate the computation of feasible rules. Experimental results show the feasibility and effectiveness of our matching framework.
Highlights
Computer aided process plant design plays an important role in the early stage of a process plant’s life cycle which consists of planning, design, construction, operation, and disposal [1]
We proposed a partial matching framework for large scale PPMs based on random walk(RW) on graphs
We propose a partial matching framework for PPMs based on the VF2 algorithm combined with local topological features extracted by RW on graphs
Summary
Computer aided process plant design plays an important role in the early stage of a process plant’s life cycle which consists of planning, design, construction, operation, and disposal [1]. Connection points are one kind of topology modeling method for PPMs. Each connection point contains information describing the geometry parameters and engineering constraints. To the best of our knowledge, few published works deal with the partial matching of PPMs. Wen et al [2] used the topological relationship distribution to measure the overall similarity between different types of PPMs. How to discover the target partial model quickly in the complex PPM under the interference of similar local structure has not been studied. Topology relationship among components indicates the structure information, and even the process flow. In order to distinguish similar local structures and thereby accelerate the matching process, the local topological feature of each component is computed based on the RW on the extracted subgraph.
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