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王兵, 林涛, 陈善本. 漏焊智能检测系统中的知识获取[J]. 焊接学报, 2001, (3): 29-32.
引用本文: 王兵, 林涛, 陈善本. 漏焊智能检测系统中的知识获取[J]. 焊接学报, 2001, (3): 29-32.
WANG Bing, LIN Tao, CHEN Shan-ben. Knowledge Acquiring in Intelligent Detecting System for Lack of Weld[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2001, (3): 29-32.
Citation: WANG Bing, LIN Tao, CHEN Shan-ben. Knowledge Acquiring in Intelligent Detecting System for Lack of Weld[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2001, (3): 29-32.

漏焊智能检测系统中的知识获取

Knowledge Acquiring in Intelligent Detecting System for Lack of Weld

  • 摘要: 在智能系统中,知识获取是极为重要的,它在一定程度上反映了系统智能水平的高低。在知识获取的过程中应用软计算方法是当前国内外研究人员的研究热点。粗糙集理论作为一种新兴的软计算方法具有极大的应用潜力,已经广泛应用于模式识别、医疗诊断、医疗数据分析、图像处理、质量控制、故障诊断、数据挖掘和过程控制等许多领域中。在本检测系统中,由于具体条件的限制和人为因素的影响,传统的方法不能满足要求,必须用智能的方法加以解决。而解决问题的关键在于如何有效地获取检测过程中的知识,从而实现智能检测。将粗糙集理论应用于相关初步知识的获取,再由神经网络对所获取的初步知识进行优化,可以提高知识获取的效率。本文给出了该智能检测系统中运用粗糙集理论获取相关初步知识的方法。

     

    Abstract: It is the most important to acquire knowledge in intelligent systems and it reflects the intelligence level of the system.To apply soft computingtools to acquire knowledge is a focus of researchers from all over the world.As a new soft computingtool,the rough set theory has enormous potential in applying and it has been widely applied in lots of fields such as pattern recognition,medical diagnosis,medical data analysis,image processing,quality control,fault diagnosis,data mining,process control and so on.In our detecting system,traditional methods could not satisfy requirements for the restricition of real conditions and factors of operators and intelligent methods must be adopted.In order to realize the intelligent detecting,how to dffectively acquire knowledge is the key problem.to apply the rough set theory to acquire a correlative elementary knowledge and then optimize the knowledge by neural networks can improve the efficiency of acquiring knowledge.The method of acquiring the correlative elementary knowledge with rough set theory in our intelligent detecting system is given in this paper.

     

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