Data acquisition system for the modern induction motor drive applications

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10247570" target="_blank" >RIV/61989100:27240/20:10247570 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9269184" target="_blank" >https://ieeexplore.ieee.org/document/9269184</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/EPE51172.2020.9269184" target="_blank" >10.1109/EPE51172.2020.9269184</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Data acquisition system for the modern induction motor drive applications

Popis výsledku v původním jazyce

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. (C) 2020 IEEE.

Název v anglickém jazyce

Data acquisition system for the modern induction motor drive applications

Popis výsledku anglicky

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. (C) 2020 IEEE.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2020 21st International Scientific Conference on Electric Power Engineering (EPE) : conference proceedings : 19-21 October 2020, Prague, Czech Republic

ISBN

978-1-72819-480-6

ISSN

2376-5623

e-ISSN

—

Počet stran výsledku

5

Strana od-do

—

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Praha

Datum konání akce

19. 10. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—