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Predicting the martensite transformation start-temperature of low alloy steel based on fuzzy identification
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作者 YueJiang ZhongdaYin PengchaoKang YongLiu 《Journal of University of Science and Technology Beijing》 CSCD 2004年第5期462-468,共7页
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 ... 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. 展开更多
关键词 fuzzy identification prediction model martensite transformation start-temperature Ms alloying element low alloy steel
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