基于深度知识的创新性计算机辅助创新系统研究  

Research on innovative computer-aided innovation systems based on depth knowledge

作　　者：任工昌[1,2] 李平平[3] 鲁麒[1] 于峰海[1] 

机构地区：[1]陕西科技大学机电工程学院,陕西西安710021 [2]三一重工股份有限公司,湖南长沙410100 [3]陕西科技大学设计与艺术学院,陕西西安710021

出　　处：《机械设计》2014年第2期15-19,共5页Journal of Machine Design

基　　金：国家自然科学基金资助项目(51175314);"十二五"国家科技支撑计划资助项目(2012BAF02B01)

摘　　要：针对我国制造业中轻工产品设计的特点和目前以TRIZ为核心的计算机辅助创新系统(Computer Aided Innovation,CAI)待解决的科学问题,通过从专利及各个学科的科技文献资料中获取深度知识进行知识库扩充和更新方法的研究,构建了CAI深度知识数据库的扩充和相应的运用机制;同时,通过对TRIZ、头脑风暴法、克服思维惯性等方法的分析与研究,构建了基于CAI的创新性概念设计过程模型。以此为依据,提出了具有创新性、操作性和指导性的基于深度知识的产品创新设计系统模型,并在辅助订钉器的创新设计中验证了该系统模型的有效性与合理性。Against the characteristics of light industry products of China＇s manufacturing industry and scientific issues to be resolved in the TRIZ-core computer-aided innovation systems（CAI）, through research on knowledge base expansion and update methods to obtain the depth knowledge from patents and disciplines in scientific and technological literatures,the expansion of the CAI depth knowledge database and mechanisms were constructed. Simultane- ously,through the analysis and research of TRIZ,brainstorming and methods to overcome the inertia of thinking, innovative conceptual design model based on CAI was constructed. As a basis ,a product innovation design system model of innovation, maneuverability and guidance based on the depth of knowledge was proposed, and it verifies the effectiveness and rationality of the system model in innovative design of auxiliary stapler device.

关 键 词：CAI TRIZ 深度知识挖掘 头脑风暴法 克服思维惯性 

分 类 号：TH122[机械工程—机械设计及理论] TP301[自动化与计算机技术—计算机系统结构]