Classifying material type and mechanical properties using artificial neural network

Intan Maisarah Abd Rahim, F. Mat, S. Yaacob, R. Siregar
{"title":"Classifying material type and mechanical properties using artificial neural network","authors":"Intan Maisarah Abd Rahim, F. Mat, S. Yaacob, R. Siregar","doi":"10.1109/CSPA.2011.5759874","DOIUrl":null,"url":null,"abstract":"This paper focused on experimental data and study for the testing of the material mechanical properties using vibration technique. By applying vibration analysis and testing on the material, we could determine the natural frequencies, the damping ratio and mode shapes of the structure. However, in this study, we only considering the natural frequencies of the material as the input data needed for training. As an extension for the study, the system tested with various method of neural network training algorithm. The Levenberg-Marquardt Backpropagation used as the algorithm in an artificial neural network system developed.","PeriodicalId":282179,"journal":{"name":"2011 IEEE 7th International Colloquium on Signal Processing and its Applications","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 7th International Colloquium on Signal Processing and its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSPA.2011.5759874","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

This paper focused on experimental data and study for the testing of the material mechanical properties using vibration technique. By applying vibration analysis and testing on the material, we could determine the natural frequencies, the damping ratio and mode shapes of the structure. However, in this study, we only considering the natural frequencies of the material as the input data needed for training. As an extension for the study, the system tested with various method of neural network training algorithm. The Levenberg-Marquardt Backpropagation used as the algorithm in an artificial neural network system developed.
利用人工神经网络对材料类型和力学性能进行分类
本文针对振动技术测试材料力学性能的实验数据进行了研究。通过对材料的振动分析和测试,可以确定结构的固有频率、阻尼比和模态振型。然而,在本研究中,我们只考虑材料的固有频率作为训练所需的输入数据。作为本研究的延伸,用神经网络的各种训练算法对系统进行了测试。将Levenberg-Marquardt反向传播算法应用于人工神经网络系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信