Final electromagnetic stirring(F-EMS)and thermal soft reduction(TSR)are techniques that improve the inner quality of continuous casting billets,but they have rarely been applied simultaneously.The application effects ...Final electromagnetic stirring(F-EMS)and thermal soft reduction(TSR)are techniques that improve the inner quality of continuous casting billets,but they have rarely been applied simultaneously.The application effects of F-EMS and TSR were compared,and a process integrating F-EMS and TSR was adopted for a billet continuous caster.A heat transfer model was established to calculate the thermal behavior of 82A tire cord steel billet.The locations of F-EMS and TSR were determined,followed by conducting a series of plant trials,involving F-EMS alone,TSR alone,and the integrated process of F-EMS and TSR.The results showed that F-EMS or TSR could effectively improve the inner quality of the billet under their respective suitable working conditions.Moreover,F-EMS was found to be more helpful in terms of improving central segregation,while TSR tended to improve V-segregation,central porosity,and pipe.The integration of F-EMS and TSR allowed the advantages of each technique to be utilized,thereby better improving the inner quality.Among all the working conditions,82A steel billet showed optimum inner quality when the current of F-EMS was 240 A and the cooling intensity of TSR was 2.2 m^(3) h^(−1).These findings demonstrate that the integration of F-EMS and TSR is promising for application on continuous casting billets.展开更多
The aim of this research was to determine the rice protein content utilizing a NIR imaging system.The developed imaging system utilized a NIR camera which installed automatically exchanged filters with the wavelength ...The aim of this research was to determine the rice protein content utilizing a NIR imaging system.The developed imaging system utilized a NIR camera which installed automatically exchanged filters with the wavelength range from 870 nm to 1014 nm.Multiple liner regression(MLR),partial least square regression(PLSR),and artificial neural network(ANN)models were employed as data analysis methods for 6.18%-9.43%rice protein detections within both the NIR imaging system and commercial NIRS.A total of 180 rice samples were used in this study,of which 120 random samples were selected as a calibration set for the MLR and PLSR models.Moreover,for establishing the back-propagation ANN model,the same 120 samples were divided into two parts,80 samples were used for network training and the other 40 were established as the monitoring set.To compare with the results of MLR,PLSR,and ANN models,the remaining 60 of the total 180 samples were established as the validation set.Applying an MLR linear regression model composed of five wavelengths;the NIR imaging system successfully detected rice protein content.The predicting results of r_(val)^(2) and SEP were 0.769 and 0.294%,respectively.In PLSR model,utilizing the imaging system obtained the results of r_(val)^(2)=0.782,and SEP=0.274%within the wavelength range from 870 nm to 1014 nm.Five significant wavelengths selected by the MLR model were the same as the input data of the ANN model,and the prediction results were r_(val)^(2)=0.806,and SEP=0.266%.The prediction results indicated that the developed NIR imaging system has the advantages of simple,convenient operation,and high detection accuracy as well as it presents commercial potential in non-destructive detection of rice protein content.展开更多
基金the financial support provided by the independent subject of State Key Laboratory of Advanced MetallurgyUniversity of Science and Technology Beijing,China,grant number 41617003,which enabled the successful completion of the study.
文摘Final electromagnetic stirring(F-EMS)and thermal soft reduction(TSR)are techniques that improve the inner quality of continuous casting billets,but they have rarely been applied simultaneously.The application effects of F-EMS and TSR were compared,and a process integrating F-EMS and TSR was adopted for a billet continuous caster.A heat transfer model was established to calculate the thermal behavior of 82A tire cord steel billet.The locations of F-EMS and TSR were determined,followed by conducting a series of plant trials,involving F-EMS alone,TSR alone,and the integrated process of F-EMS and TSR.The results showed that F-EMS or TSR could effectively improve the inner quality of the billet under their respective suitable working conditions.Moreover,F-EMS was found to be more helpful in terms of improving central segregation,while TSR tended to improve V-segregation,central porosity,and pipe.The integration of F-EMS and TSR allowed the advantages of each technique to be utilized,thereby better improving the inner quality.Among all the working conditions,82A steel billet showed optimum inner quality when the current of F-EMS was 240 A and the cooling intensity of TSR was 2.2 m^(3) h^(−1).These findings demonstrate that the integration of F-EMS and TSR is promising for application on continuous casting billets.
文摘The aim of this research was to determine the rice protein content utilizing a NIR imaging system.The developed imaging system utilized a NIR camera which installed automatically exchanged filters with the wavelength range from 870 nm to 1014 nm.Multiple liner regression(MLR),partial least square regression(PLSR),and artificial neural network(ANN)models were employed as data analysis methods for 6.18%-9.43%rice protein detections within both the NIR imaging system and commercial NIRS.A total of 180 rice samples were used in this study,of which 120 random samples were selected as a calibration set for the MLR and PLSR models.Moreover,for establishing the back-propagation ANN model,the same 120 samples were divided into two parts,80 samples were used for network training and the other 40 were established as the monitoring set.To compare with the results of MLR,PLSR,and ANN models,the remaining 60 of the total 180 samples were established as the validation set.Applying an MLR linear regression model composed of five wavelengths;the NIR imaging system successfully detected rice protein content.The predicting results of r_(val)^(2) and SEP were 0.769 and 0.294%,respectively.In PLSR model,utilizing the imaging system obtained the results of r_(val)^(2)=0.782,and SEP=0.274%within the wavelength range from 870 nm to 1014 nm.Five significant wavelengths selected by the MLR model were the same as the input data of the ANN model,and the prediction results were r_(val)^(2)=0.806,and SEP=0.266%.The prediction results indicated that the developed NIR imaging system has the advantages of simple,convenient operation,and high detection accuracy as well as it presents commercial potential in non-destructive detection of rice protein content.
