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author:

Liu, X. (Liu, X..) [1] | Li, J. (Li, J..) [2] | Chen, L. (Chen, L..) [3] | Cheng, G. (Cheng, G..) [4]

Indexed by:

Scopus PKU CSCD

Abstract:

A general framework for integrating extension and multi-level knowledge modeling is constructed to address the problems existing in the process of bionic prototype acquisition. The multi-level semantic relationship of the product-biological system is introduced. The extensional model of product system Function-Principle-Behavior-Structure and biology system Structure- Action-Tactic-Function case-element ontology based on the basic-element theory of the extension and its formal description method are built. The product FPBS and the biology SATF mapping relation model are established. The case-element extension set of the product-biology system is made according to the extended nature and the similar method of the basic-element is introduced in the relevant extensional set. Searching a bionic prototype based on the similarity of the two systems is proposed, and a method of extensional comprehensive evaluation is used to optimize the bionic prototype. The screen filter is taken as an example, the feasibility of the overall framework is verified. © 2019 Journal of Mechanical Engineering.

Keyword:

Bionic prototype; Extension; FPBS; Knowledge modeling; SATF; Similarity

Community:

  • [ 1 ] [Liu, X.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350116, China
  • [ 2 ] [Li, J.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350116, China
  • [ 3 ] [Chen, L.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350116, China
  • [ 4 ] [Cheng, G.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350116, China

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Source :

Journal of Mechanical Engineering

ISSN: 0577-6686

CN: 11-2187/TH

Year: 2019

Issue: 21

Volume: 55

Page: 150-160

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 7

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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