Variation and Grey GM(1, 1) Prediction of Melting Peak Temperature of Polypropylene During Ultraviolet Radiation Aging

1st International Workshop on Materials Science and Mechanical Engineering

材料科学;机械制造

Chen, K.^1 ; Zhang, T.Y.^2 ; Zhang, F.^2 ; Zhang, Z.R.^3

School of Bailie Mechanical Engineering, Lanzhou City University, Lanzhou, China^1

Center of Information and Network, Lanzhou City University, Lanzhou, China^2

School of Electronic and Information Engineering, Lanzhou City University, Lanzhou, China^3

关键词: Data driven modelling;    Differential scanning calorimeters;    Grey system theory;    Maximum relative errors;    Potential variations;    Prediction accuracy;    Prediction equations;    Ultraviolet radiation aging;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/281/1/012034/pdf
DOI  :  10.1088/1757-899X/281/1/012034

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

Grey system theory regards uncertain system in which information is known partly and unknown partly as research object, extracts useful information from part known, and thereby revealing the potential variation rule of the system. In order to research the applicability of data-driven modelling method in melting peak temperature (Tm) fitting and prediction of polypropylene (PP) during ultraviolet radiation aging, the Tmof homo-polypropylene after different ultraviolet radiation exposure time investigated by differential scanning calorimeter was fitted and predicted by grey GM(1, 1) model based on grey system theory. The results show that the Tmof PP declines with the prolong of aging time, and fitting and prediction equation obtained by grey GM(1, 1) model is Tm= 166.567472exp(-0.00012t). Fitting effect of the above equation is excellent and the maximum relative error between prediction value and actual value of Tmis 0.32%. Grey system theory needs less original data, has high prediction accuracy, and can be used to predict aging behaviour of PP.