智能混凝土强度测量装置

Bushra Abro, B. Lal, M. Aamir, Shanker Lal Meghwar, F. A. Memon, Zameer Hussain
{"title":"智能混凝土强度测量装置","authors":"Bushra Abro, B. Lal, M. Aamir, Shanker Lal Meghwar, F. A. Memon, Zameer Hussain","doi":"10.1109/ICETECC56662.2022.10069766","DOIUrl":null,"url":null,"abstract":"The measurement of compressive strength is the most important in construction industries. Conventionally used devices such as UTM (Universal Testing Machine) are costly, time-consuming, produce a lot of waste material, and produce environmental pollution. In addition, hectic processes used to be carried out, such as standard cubes were cast and tested at varying curing ages (7,14,21,28 days). In this research, we designed a smart prototype device that can measure the strength of concrete mix based on ANN (Artificial Neural Network). Using the designed system, it is possible to measure concrete’s fixed compressive strength by varying the ingredients’ proportions (cement, coarse aggregates, fine aggregates, and water). Historical concrete mix data (50) is collected from the Concrete and Structural Laboratory, Mehran University of Engineering and Technology Jamshoro, and sorted out as per ANN requirements. The system used 80% of data for training purposes and 20% for testing and validation using high accuracy (96%) historical data and further connected to a cloud storage network to collect measurement data. This device will help the construction industry make quick project choices and save material waste.","PeriodicalId":364463,"journal":{"name":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Smart Concrete Strength Measurement Device\",\"authors\":\"Bushra Abro, B. Lal, M. Aamir, Shanker Lal Meghwar, F. A. Memon, Zameer Hussain\",\"doi\":\"10.1109/ICETECC56662.2022.10069766\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The measurement of compressive strength is the most important in construction industries. Conventionally used devices such as UTM (Universal Testing Machine) are costly, time-consuming, produce a lot of waste material, and produce environmental pollution. In addition, hectic processes used to be carried out, such as standard cubes were cast and tested at varying curing ages (7,14,21,28 days). In this research, we designed a smart prototype device that can measure the strength of concrete mix based on ANN (Artificial Neural Network). Using the designed system, it is possible to measure concrete’s fixed compressive strength by varying the ingredients’ proportions (cement, coarse aggregates, fine aggregates, and water). Historical concrete mix data (50) is collected from the Concrete and Structural Laboratory, Mehran University of Engineering and Technology Jamshoro, and sorted out as per ANN requirements. The system used 80% of data for training purposes and 20% for testing and validation using high accuracy (96%) historical data and further connected to a cloud storage network to collect measurement data. This device will help the construction industry make quick project choices and save material waste.\",\"PeriodicalId\":364463,\"journal\":{\"name\":\"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICETECC56662.2022.10069766\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETECC56662.2022.10069766","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

抗压强度的测量在建筑行业中是最重要的。常规使用的设备,如UTM(万能试验机),成本高,耗时长,产生大量的废料,并产生环境污染。此外,过去还进行了一些繁忙的过程,例如铸造标准立方体并在不同的固化时间(7、14、21、28天)下进行测试。在本研究中,我们设计了一种基于人工神经网络的混凝土配合比强度测量智能原型装置。使用设计的系统,可以通过改变成分的比例(水泥、粗骨料、细骨料和水)来测量混凝土的固定抗压强度。历史混凝土配合比数据(50)来自Jamshoro Mehran工程技术大学混凝土与结构实验室,并根据人工神经网络要求进行整理。该系统将80%的数据用于培训目的,20%用于测试和验证,使用高精度(96%)的历史数据,并进一步连接到云存储网络以收集测量数据。该设备将帮助建筑行业快速选择项目,节省材料浪费。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Smart Concrete Strength Measurement Device
The measurement of compressive strength is the most important in construction industries. Conventionally used devices such as UTM (Universal Testing Machine) are costly, time-consuming, produce a lot of waste material, and produce environmental pollution. In addition, hectic processes used to be carried out, such as standard cubes were cast and tested at varying curing ages (7,14,21,28 days). In this research, we designed a smart prototype device that can measure the strength of concrete mix based on ANN (Artificial Neural Network). Using the designed system, it is possible to measure concrete’s fixed compressive strength by varying the ingredients’ proportions (cement, coarse aggregates, fine aggregates, and water). Historical concrete mix data (50) is collected from the Concrete and Structural Laboratory, Mehran University of Engineering and Technology Jamshoro, and sorted out as per ANN requirements. The system used 80% of data for training purposes and 20% for testing and validation using high accuracy (96%) historical data and further connected to a cloud storage network to collect measurement data. This device will help the construction industry make quick project choices and save material waste.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
CROPBot: Customized Rigid Organic Plantation Robot Sentiment Analysis on Hydroponic Technology Application for Urban Farming Limitations Multi-Active Multi-Datacenter Distributed Database Architecture Design based-on Secondary Development Zookeeper Assessing Security threats Perception of LayeredInternet of Things using Multiple Linear Regression Model Performance Comparison of Outer and Inner Rotor Flux Reversal Machine for Direct Drive Application
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1