文章摘要
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 NameAffiliationE-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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