Repository logo
Communities & Collections
Research Outputs
Fundings & Projects
People
Statistics
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. CRIS
  3. Publications
  4. Monitoring System Based on an IoT Platform for an AFPM Generator
Details

Monitoring System Based on an IoT Platform for an AFPM Generator

Journal
Communications in Computer and Information Science
Date Issued
2023
Author(s)
Cumbajín M.
Sánchez, Patricio  
Facultad de Ingenierías  
Ortiz O.
Gordón C.
Type
Conference Paper
DOI
10.1007/978-3-031-24985-3_37
URL
https://cris.indoamerica.edu.ec/handle/123456789/8441
Abstract
In the present work, a monitoring platform is made for an Axial Flow Permanent Magnet (AFPM) Generator without magnetic core, the objective is to permanently monitor the values that come from the generator, where the generator variables have been acquired through an open source development board called Arduino MEGA, which sends the data to a Raspberry PI, where they are displayed and stored so that they can be processed. The variables are displayed using the graphical node-red environment that offers a very eye-catching dashboard, which will be displayed on a 7 in. liquid-crystal display screen. All the data obtained is stored in a database that will allow its use for specific purposes. The monitoring platform has been built with the ability to monitor the speed of the rotors, the voltage and the current of a phase and thus be able to process the total power supplied by the generator. As a result, the monitoring system is a promise component for Pico Hydro power station to control the power all the time provided by the Axial Flow Permanent Magnet Generator. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Subjects

Antenna array; Energy...

Investigación Indoamérica

Logo Universidad Tecnológica Indoamérica
  • Accessibility settings
  • Privacy policy
  • End User Agreement
  • Send Feedback

Hosting & Support by

Built with DSpace-CRIS software - Extension maintained and optimized by 4science

COAR Notify