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《Die & Mould Industry》 2012-01
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Application of fuzzy neural network in intelligent multiple defects diagnosis for injection molding

CHEN Chen 1,WANG Hong-ji 1,XU Ying-qiang1,ZHOU Jie-kui1,ZHOU Yi2(1.School of Material Science and Engineering,Hefei University of Technology,Hefei 230009,China;2.Anhui ECHOM Science &Technology Co.LTD,Hefei 230601,China)  
In view of the ambiguity and uncertainty in solving the cause of injection molding,a method combining fuzzy theory and neural network for judging and determining the cause was proposed,which is because of the advantages of neural network in obtaining the non-linear mapping relationship between multidimensional eigenvector and output vector,and the strong ability of fuzzy technology in dealing with imprecise information.The whole process of the diagnosis was presented in detail.Based on the above theory and application platform of Visual Prolog,an intelligent system for the multiple defects diagnosis in injection molding was developed,and an application example was given.
【Fund】: 国家科技型中小企业技术创新基金(11C26213401942)
【CateGory Index】: TQ320.662
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