安徽大学学报（自然科学版）2024，Vol.48Issue(6)：78-85,8.DOI:10.3969/j.issn.1000-2162.2024.06.011
机器学习分析和预测橡胶圈老化性能
Study and prediction on aging of rubber rings by machine learning
摘要
Abstract
The hot air aging test was used to analyze the change rules of elongation at break of acrylate rubber O-ring,fluorine rubber O-ring and nitrile rubber O-ring.Based on the experimental data,models were established to predict the change rules of elongation at break of the rubber rings with aging time by using machine learning method.The results showed that the machine learning technology combined with the data augmentation method of Savitzky-Golay filtering method and Piecewise Linear Interpolation method and eXtreme Gradient Boosting algorithm could accurately predict the aging law and long-term aging performance of rubber rings.As verified by experimental test data,the machine learning prediction models have more significant accuracy and applicability in the aging prediction of rubber rings elongation at break compared with the traditional fitting functions.关键词
热空气老化/机器学习/断裂伸长率/预测/试验验证Key words
hot air aging/machine learning/elongation at break/prediction/experimental verification分类
化学化工引用本文复制引用
王芳婷,吴尚,徐帅帅,伍斌,夏茹,钱家盛,陈鹏,苗继斌..机器学习分析和预测橡胶圈老化性能[J].安徽大学学报（自然科学版）,2024,48(6):78-85,8.基金项目
国家自然科学基金面上项目(22378001) （22378001）
安徽省自然科学基金面上项目(2018085ME153) （2018085ME153）
