Due to its highly favorable physical and chemical properties,titanium and titanium alloy are widely used in a variety of industries.Because of the low output of a single batch,plate cold rolling without tension is the...Due to its highly favorable physical and chemical properties,titanium and titanium alloy are widely used in a variety of industries.Because of the low output of a single batch,plate cold rolling without tension is the most common rolling production method for titanium alloy.This method is lack of on-line thickness closed-loop control,with carefully thickness setting models for precision.A set of high-precision thickness setting models are proposed to suit the production method.Because of frequent variations in rolling specification,a model structural for the combination of analytical models and statistical models is adopted to replace the traditional self-learning method.The deformation resistance and friction factor,the primary factors which affect model precision,are considered as the objectives of statistical modeling.Firstly,the coefficient fitting of deformation resistance analytical model based on over-determined equations set is adopted.Additionally,a support vector machine(SVM)is applied to the modeling of the deformation resistance and friction factor.The setting models are applied to a 1450 plate-coiling mill for titanium alloy plate rolling,and then thickness precision is found consistently to be within 3%,exceeding the precision of traditional setting models with a self-learning method based on a large number of stable rolling data.Excellent application performance is obtained.The proposed research provides a set of high-precision thickness setting models which are well adapted to the characteristics of titanium alloy plate cold rolling without tension.展开更多
A model of deformation resistance during hot strip rolling was established based on generalized additive model.Firstly,a data modeling method based on generalized additive model was given.It included the selection of ...A model of deformation resistance during hot strip rolling was established based on generalized additive model.Firstly,a data modeling method based on generalized additive model was given.It included the selection of dependent variable and independent variables of the model,the link function of dependent variable and smoothing functional form of each independent variable,estimating process of the link function and smooth functions,and the last model modification.Then,the practical modeling test was carried out based on a large amount of hot rolling process data.An integrated variable was proposed to reflect the effects of different chemical compositions such as carbon,silicon,manganese,nickel,chromium,niobium,etc.The integrated chemical composition,strain,strain rate and rolling temperature were selected as independent variables and the cubic spline as the smooth function for them.The modeling process of deformation resistance was realized by SAS software,and the influence curves of the independent variables on deformation resistance were obtained by local scoring algorithm.Some interesting phenomena were found,for example,there is a critical value of strain rate,and the deformation resistance increases before this value and then decreases.The results confirm that the new model has higher prediction accuracy than traditional ones and is suitable for carbon steel,microalloyed steel,alloyed steel and other steel grades.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.51304017)National Key Technology R&D Program of the 12th Five-year Plan of China(Grant Nos.2012BAF04B02,2011BAE23B04)Fundamental Research Funds for Central Universities,China(Grant No.FRF-SD-12-013B)
文摘Due to its highly favorable physical and chemical properties,titanium and titanium alloy are widely used in a variety of industries.Because of the low output of a single batch,plate cold rolling without tension is the most common rolling production method for titanium alloy.This method is lack of on-line thickness closed-loop control,with carefully thickness setting models for precision.A set of high-precision thickness setting models are proposed to suit the production method.Because of frequent variations in rolling specification,a model structural for the combination of analytical models and statistical models is adopted to replace the traditional self-learning method.The deformation resistance and friction factor,the primary factors which affect model precision,are considered as the objectives of statistical modeling.Firstly,the coefficient fitting of deformation resistance analytical model based on over-determined equations set is adopted.Additionally,a support vector machine(SVM)is applied to the modeling of the deformation resistance and friction factor.The setting models are applied to a 1450 plate-coiling mill for titanium alloy plate rolling,and then thickness precision is found consistently to be within 3%,exceeding the precision of traditional setting models with a self-learning method based on a large number of stable rolling data.Excellent application performance is obtained.The proposed research provides a set of high-precision thickness setting models which are well adapted to the characteristics of titanium alloy plate cold rolling without tension.
基金supported by National Natural Science Foundation of China (51774219)Science and Technology Research Program of Hubei Ministry of Education(D20161103)Youth Science and technology Program of Wuhan(2016070204010099)
文摘A model of deformation resistance during hot strip rolling was established based on generalized additive model.Firstly,a data modeling method based on generalized additive model was given.It included the selection of dependent variable and independent variables of the model,the link function of dependent variable and smoothing functional form of each independent variable,estimating process of the link function and smooth functions,and the last model modification.Then,the practical modeling test was carried out based on a large amount of hot rolling process data.An integrated variable was proposed to reflect the effects of different chemical compositions such as carbon,silicon,manganese,nickel,chromium,niobium,etc.The integrated chemical composition,strain,strain rate and rolling temperature were selected as independent variables and the cubic spline as the smooth function for them.The modeling process of deformation resistance was realized by SAS software,and the influence curves of the independent variables on deformation resistance were obtained by local scoring algorithm.Some interesting phenomena were found,for example,there is a critical value of strain rate,and the deformation resistance increases before this value and then decreases.The results confirm that the new model has higher prediction accuracy than traditional ones and is suitable for carbon steel,microalloyed steel,alloyed steel and other steel grades.