Data Acquisition System for the Modern Induction Motor Drive applications

D. Kouril, Jakub Bača, M. Sobek, M. Kuchar, Jan Strossa
{"title":"Data Acquisition System for the Modern Induction Motor Drive applications","authors":"D. Kouril, Jakub Bača, M. Sobek, M. Kuchar, Jan Strossa","doi":"10.1109/EPE51172.2020.9269184","DOIUrl":null,"url":null,"abstract":"This paper describes a hardware and software solution for data acquisition [1]–[4] for implementation in the field of modern sensorless control methods of induction motor drive [5], where especially adaptive control methods based on Artificial Neural Network (ANN) require a large amount of training data for their operation. Also in industrial applications nowadays, diagnostic systems are often used. These systems work on the principle of data acquisition and enable detection of unwanted faults during stable operation of automated technologies and data collection of quantities that are accessible to superior systems and seemingly unrelated to a motor drive control, such as information about the temperatures and mechanical state. In this way, for example, it is possible to overall increase productivity and safety over the lifetime of the automated technology. This article is divided into several parts. In the first part, based on the requirements, analysis, and design of a suitable solution for data acquisition and advantages over other solutions is performed. The second part of the paper deals with the hardware design of the data acquisition system solution. The third part is focused on the software design and implementation in the LabVIEW and MATLAB environment. The last part of the article is devoted to the analysis of experimental results.","PeriodicalId":177031,"journal":{"name":"2020 21st International Scientific Conference on Electric Power Engineering (EPE)","volume":"31 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 21st International Scientific Conference on Electric Power Engineering (EPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPE51172.2020.9269184","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This paper describes a hardware and software solution for data acquisition [1]–[4] for implementation in the field of modern sensorless control methods of induction motor drive [5], where especially adaptive control methods based on Artificial Neural Network (ANN) require a large amount of training data for their operation. Also in industrial applications nowadays, diagnostic systems are often used. These systems work on the principle of data acquisition and enable detection of unwanted faults during stable operation of automated technologies and data collection of quantities that are accessible to superior systems and seemingly unrelated to a motor drive control, such as information about the temperatures and mechanical state. In this way, for example, it is possible to overall increase productivity and safety over the lifetime of the automated technology. This article is divided into several parts. In the first part, based on the requirements, analysis, and design of a suitable solution for data acquisition and advantages over other solutions is performed. The second part of the paper deals with the hardware design of the data acquisition system solution. The third part is focused on the software design and implementation in the LabVIEW and MATLAB environment. The last part of the article is devoted to the analysis of experimental results.
数据采集系统在现代感应电机驱动中的应用
本文介绍了一种数据采集[1]-[4]的硬件和软件解决方案,以实现现代感应电机驱动[5]的无传感器控制方法,特别是基于人工神经网络(ANN)的自适应控制方法需要大量的训练数据才能运行。在当今的工业应用中,也经常使用诊断系统。这些系统的工作原理是数据采集,能够在自动化技术稳定运行期间检测不必要的故障,并收集高级系统可以访问的数量的数据,这些数据似乎与电机驱动控制无关,例如有关温度和机械状态的信息。例如,通过这种方式,可以在自动化技术的生命周期内全面提高生产率和安全性。本文分为几个部分。在第一部分中,根据需求,分析和设计了一个适合数据采集的解决方案以及与其他解决方案相比的优势。论文的第二部分是数据采集系统方案的硬件设计。第三部分重点介绍了在LabVIEW和MATLAB环境下的软件设计与实现。文章的最后一部分是对实验结果的分析。
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