Predicting the martensite transformation start-temperature of low alloy steel based on fuzzy identification北京科技大学学报：英文版论文
【题名】：Predicting the martensite transformation start-temperature of low alloy steel based on fuzzy identification北京科技大学学报：英文版论文(Predicting the martensite transformation start-temperature of low alloy steel based on fuzzy identificationBeiJingKeJiDaXueXueBao：YingWenBanLunWen) 【关键词】：马氏体 低合金钢 模糊识别 预测模型 初始温度 【keywords】：MaShiTi DiHeJinGang MoHuShiBie YuCeMoXing ChuShiWenDu 【作者】：YueJiang ZhongdaYin PengchaoKang YongLiu      【来源】： 知识词典 【期刊名称】：北京科技大学学报：英文版(BeiJingKeJiDaXueXueBao：YingWenBan) 【国际标准刊号】：1005-8850        【国内统一刊号】：11-3473/T 【作者单位】：SchoolofMaterialsScienceandEngineering,HarbinInstituteofTechnology,Harbin150001,China(SchoolofMaterialsScienceandEngineering,HarbinInstituteofTechnology,Harbin150001,China) 【分类号】：TG142.33 TG142.24      【页码】：-462-468      【出版年】：2004.5 【下载地址】：下载pdf全文         A method of fuzzy identification based on T-S fuzzy model was proposed for predicting temperature Ms from chemical composition, austenitizing temperature and time for low alloy steel. The degree of membership of each sample was calculated with fuzzy clustering algorithm. Kalman filtering was used to identify the consequent parameters. Compared with the results obtained by empirical models based on the same data, the results by the fuzzy method showed good precision. The accuracy of the fuzzy model is almost 6 times higher than that of the best empirical model. The influence of alloying elements, austenitizing temperature and time on Ms was analyzed quantitatively by using the fuzzy model. It is shown that there exists a nonlinear relationship between the contents of alloying elements in steels and their Ms, and the effects of austenitizing temperature and time on Ms temperature cannot be neglected.
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