物理学报2024，Vol.73Issue(16)：152-161,10.DOI:10.7498/aps.73.20240482
基于机器学习的磁流变弹性体磁致储能模量的快速准确表征
Fast and accurate characterization of magnetorheological elastomers based on machine learning
摘要
Abstract
Magnetorheological elastomers(MREs)are smart materials with a wide range of applications,particularly in reducing vibrations and noise.Traditional methods of testing their magnetically-induced properties,although thorough,are labor-intensive and time-consuming.In this work,we introduce an innovative method that harnesses machine learning to rapidly characterize MREs by using a smallest dataset,thus simplifying the characterization process.Initially,12 types of MREs are prepared and tested on a shear rheometer with a controllable magnetic field.From these data,we strategically select five representative data points from each sample to form a training dataset.Using this dataset,we develop a support vector regression(SVR)model to characterize the magnetically-induced storage modulus of the MRE.The SVR model exhibits remarkable accuracy,with a correlation coefficient(R2)of 0.998 or higher,exceeding the precision of traditional models.The training time of this model is very brief,only 0.02 seconds,thus greatly accelerating the characterization speed of MRE.Moreover,the SVR model demonstrates strong generalization ability,maintaining a high correlation coefficient of 0.998 or greater even when silicone oil is added to the MREs or tested under various loading frequencies.In a word,the machine learning model not only accelerates the evaluation process but also provides a valuable reference for developing innovative MREs,marking a significant advancement in the field of smart materials research.关键词
磁流变弹性体/支持向量回归/磁致储能模量Key words
magnetorheological elastomers/support vector regression/magnetically-induced modulus引用本文复制引用
任航,赵丹,董立强,刘少刚,杨金水..基于机器学习的磁流变弹性体磁致储能模量的快速准确表征[J].物理学报,2024,73(16):152-161,10.基金项目
国家自然科学基金(批准号:52275098,52075111,51675111)资助的课题. Project supported by the National Natural Science Foundation of China(Grant Nos.52275098,52075111,51675111). （批准号:52275098,52075111,51675111）
