Research On The Methods And Key Technologies Of Product Conceptual Design Driven By Biological Information

Improving conceptual design methods and technologies that contribute to the generation of innovative solutions is a key research topic in the field of product development.Due to inherent limitations,the conceptual design methods that typically use empirical-and domain-knowledge are difficult to produce highly innovative solutions.It has been shown that the cross-domain knowledge can provide designers with a unique design perspective,which is an effective means to promote innovative solutions.As an important innovation resource,biological information contains a sizeable amount of design knowledge with significant engineering value.In product conceptual design,the application of such knowledge is conducive to enhancing the innovation of solutions.It is of great significance to enhance the market competitiveness of products.However,there are multiple challenges in applying biological information to product conceptual design,due to the lack of corresponding process models,cross-domain information mapping mechanisms and design knowledge extraction methods.In order to addresse these issues,this dissertation studies the methods and key technologies of Product Conceptual Design Driven by Biological Information(PCDDBI),which is supported by the State Key Program of National Natural Science of China ?Research on key problems in the innovative design theory and method of electromechanical systems?.Firstly,the related researches are reviewed and the issues in the researches are summarized.In addition,the innovation mechanism of PCDDBI is systematically analyzed from four aspects.Besides the two process models for PCDDBI are constructed which take into account the core cognitive stages of analogical reasoning and the implicit characteristics of knowledge in biological information.Moreover,considering the complexity of function,a functional cross domain mapping mechanism based on semantic and contextual attributes is proposed,and a mathematical calculation method is presented.Furthermore,the structure knowledge and function knowledge in an example of biological information are analyzed.Then a structure-function knowledge extraction method is proposed,which combines dependency parsing and keyword extraction.Through analyzing the distribution of physical quantity in biological information,a method for extracting scientific laws contained in biological information based on human-machine cooperation is presented.Finally,based on the models and the methods proposed above,a computer aided design software toolkit is developed.The main research works and contribution of this dissertation are as follows:(1)The theoretical foundation for PCDDBI was established.Firstly,the three types of design knowledge including structure,function and scientific law which are contained in biological information were analyzed.Moreover,by introducing the basis of analogy,the explanation and the inspiration of analogy in conceptual design were summarized.As a major source of distant analogies,biological information can provide inspirations for designers to produce novel ideas.Motivated by this consideration,the innovation mechanism of PCDDBI was systematically analyzed from four aspects.Finally,according to the different starting points,two process models for PCDDBI were constructed.Particularly,the process models take into account the core cognitive stages of analogical reasoning and the implicit characteristics of knowledge in biological information.In principle,these process models could be used as product conceptual design methods and provide specific guidance for PCDDBI.(2)A functional cross domain mapping mechanism based on semantic and contextual attributes was proposed.The cross domain information mapping from engineering to biology is fundamental for finding biological information related to user requirements.Firstly,the main characteristics and types of the mapping elements were summarized,which target on building the bridge between engineering domain and biological domain.Since function plays a critical role in conceptual design,its cross domain mapping is critical for PCDDBI.In addition,considering the complexity of function,a functional cross domain mapping mechanism based on semantic and contextual attributes was proposed.Meanwhile,a mathematical calculation method that quantifies the mechanism was presented.In order to assist designers in searching biological information related to engineering functions,a method of pushing keywords based on the functional cross-domain mapping mechanism was put forward.Furthermore,the possibility of the method was demonstrated by a preliminary validation and a design case.(3)A structure-function knowledge extraction method was proposed,which combines dependency parsing and keyword extraction.We analyzed the structure knowledge and the function knowledge contained in an example of biological information,as well as the structure-function knowledge associated with them both.Meanwhile,six specific types of dependency relations were identified,which are related to the three kinds of knowledge.Then the structure-function knowledge extraction method was proposed,which combines dependency parsing and keyword extraction.The dependency parsing computes dependency relations between pairs of words in a sentence.Through the specific types of dependency relations,the potential knowledge including structures and functions can be identified.The keyword extraction is to obtain the terms that represent the subject of biological information.These terms target on filtering the identified knowledge,which ensures that the extracted structures and functions are all related to the subject.Among them,the structures and functions with association relationships are further combined into structure-function knowledge.Meanwhile,the knowledge is expressed in a structured form so that designers use it to generate innovative solutions.The proposed method was preliminarily evaluated based on randomly selected biological information,and the method was further tested by a comparative experiment.(4)A method for extracting scientific laws contained in biological information text based on human-machine cooperation was put forward.Through the collection of physical quantity and biological information,we analyzed the distribution of the former in the latter,which provides support for the inversion of scientific laws contained in biological information by using physical quantity.Then the scientific law knowledge extraction method was proposed,which includes biological information analysis,scientific law inversion and scientific law chain aggregation.In order to realize the method,a scientific law inversion model was presented,a physical quantity ontology knowledge base and a scientific law knowledge base were constructed,and a scientific law chain synthesis model was proposed.Finally,the feasibility and application process of the method was demonstrated by a case study.(5)A computer aided design software toolkit-BIDT was developed,which is based on the models and methods proposed above.Some modules in the toolkit and their application in product conceptual design are demonstrated through a case study for the improvement design of fan noise reduction.This paper provides feasible methods and tools for the product conceptual design using biological information.Meanwhile,some promising techniques were achieved.