In the present investigation, the relation of pre-ageing temperature and pre-ageing time to mechanical properties was studied, and a model was established to predict the mechanical properties of AA6005 Al alloy. Compa...In the present investigation, the relation of pre-ageing temperature and pre-ageing time to mechanical properties was studied, and a model was established to predict the mechanical properties of AA6005 Al alloy. Compared with the experimental results, the deviation of the proposed model was limited to 8.1%, which showed reasonable accuracy of forecasting. It was found that the performance of AA6005 alloy was better at higher pre-ageing temperature with shorter pre-ageing time than that at T6 temper. The microstructure of the alloy was observed by transmission electron microscopy, and the results showed that high dislocation density and precipitate density existed at 160 ℃ and 200 ℃ pre-ageing, which were in good agreement with the model.展开更多
This research develops a new mathematical modeling method by combining industrial big data and process mechanism analysis under the framework of generalized additive models(GAM)to generate a practical model with gener...This research develops a new mathematical modeling method by combining industrial big data and process mechanism analysis under the framework of generalized additive models(GAM)to generate a practical model with generalization and precision.Specifically,the proposed modeling method includes the following steps.Firstly,the influence factors are screened using mechanism knowledge and data-mining methods.Secondly,the unary GAM without interactions including cleaning the data,building the sub-models,and verifying the sub-models.Subsequently,the interactions between the various factors are explored,and the binary GAM with interactions is constructed.The relationships among the sub-models are analyzed,and the integrated model is built.Finally,based on the proposed modeling method,two prediction models of mechanical property and deformation resistance for hot-rolled strips are established.Industrial actual data verification demonstrates that the new models have good prediction precision,and the mean absolute percentage errors of tensile strength,yield strength and deformation resistance are 2.54%,3.34%and 6.53%,respectively.And experimental results suggest that the proposed method offers a new approach to industrial process modeling.展开更多
基金Projects(51575539, U1837207) supported by the National Natural Science Foundation of ChinaProject(2020RC2002)supported by the Science and Technology Innovation Program of Hunan Province,ChinaProject(2021JJ40774)supported by Natural Science Foundation of Hunan Province,China。
文摘In the present investigation, the relation of pre-ageing temperature and pre-ageing time to mechanical properties was studied, and a model was established to predict the mechanical properties of AA6005 Al alloy. Compared with the experimental results, the deviation of the proposed model was limited to 8.1%, which showed reasonable accuracy of forecasting. It was found that the performance of AA6005 alloy was better at higher pre-ageing temperature with shorter pre-ageing time than that at T6 temper. The microstructure of the alloy was observed by transmission electron microscopy, and the results showed that high dislocation density and precipitate density existed at 160 ℃ and 200 ℃ pre-ageing, which were in good agreement with the model.
基金Project(51774219)supported by the National Natural Science Foundation of China
文摘This research develops a new mathematical modeling method by combining industrial big data and process mechanism analysis under the framework of generalized additive models(GAM)to generate a practical model with generalization and precision.Specifically,the proposed modeling method includes the following steps.Firstly,the influence factors are screened using mechanism knowledge and data-mining methods.Secondly,the unary GAM without interactions including cleaning the data,building the sub-models,and verifying the sub-models.Subsequently,the interactions between the various factors are explored,and the binary GAM with interactions is constructed.The relationships among the sub-models are analyzed,and the integrated model is built.Finally,based on the proposed modeling method,two prediction models of mechanical property and deformation resistance for hot-rolled strips are established.Industrial actual data verification demonstrates that the new models have good prediction precision,and the mean absolute percentage errors of tensile strength,yield strength and deformation resistance are 2.54%,3.34%and 6.53%,respectively.And experimental results suggest that the proposed method offers a new approach to industrial process modeling.
