Viscoelastic Performance Prediction of EPDM Based on Elman Neural Network |
Received:September 20, 2017 Revised:September 20, 2017 |
DOI: |
Key Words: Elman neural network; viscoelastic properties; EPDM; performance prediction. |
Author Name | Affiliation | E-mail | ZENG XIANKUI | 青岛科技大学 机电工程学院 | zxk1967@163.com | liyingru* | 青岛科技大学 机电工程学院 | 617524011@qq.com | HUANG NIANCHANG | 青岛科技大学 机电工程学院 | | ZHANG JIE | 青岛科技大学 机电工程学院 | | BAO LIPING | 青岛科技大学 机电工程学院 | |
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Abstract: |
In this paper, the relationship between the EPDM formula and the viscoelastic properties of EPDM was studied experimentally. The Elman neural network prediction model was established to predict the dynamic viscoelastic properties (Storage modulus, loss modulus, loss factor) of the compound at 85 ℃ and 15% strain. 16 sets of experimental data were obtained by orthogonal experiment design, and Elman neural network was trained by 1-14 data. The remaining 15-16 data were used to detect the prediction ability of Elman neural network. Four sets of experimental data were designed to detect Elman neural network prediction ability. The results show that the elastic error of the Elman neural network is less than 4%, and the model can accurately predict the viscoelastic properties of the EPDM compound. |
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