Data Acquisition Module Design for Remote Monitoring of Uninterruptible Power Supply and Regression Models of Battery Life

Year 2020, Ejosat Special Issue 2020 (HORA), 279 - 283, 15.08.2020

Metehan Avkıran Vedat Gül Savaş Şahin İbrahim Tanağardıgil

https://doi.org/10.31590/ejosat.779967

Cited By: 1

Abstract

In this study, the design of embedded system-based data acquisition card is implemented for uninterruptible power supply (UPS) for providing dataset of power, current, temperature, battery voltage values. The dataset is acquired with the developed data acquisition card designed with by using serial communication protocol and transmission control protocol/internet protocol. The obtained dataset is transrecevied with the its designed interface by using the Visual Studio program. Also, the battery life estimation of UPS is performed by various regression models with machine learning algorithms. Battery status, battery electrical energy consumption and temperature data were analyzed with root mean square error and R^2 score tests. Random forest regression performed better than other regression models for the obtained dataset for the battery life. The battery life estimatation might be important for UPS performance.

Keywords

data acquisition card, interface, remote monitoring, battery life, machine learning, regression models

Supporting Institution

TÜBİTAK

Project Number

1139B411901093

Thanks

This work is supported by the Scientific and Technical Research Council of Turkey (TUBITAK) under 2209B-Bachelor Final Thesis Focused on Industry Program with Project number 1139B411901093

Kesintisiz Güç Kaynağı için Uzaktan İzlemeyi Sağlayan Veri Paylaşım Modül Tasarımı ve Regresyon Modelleri ile Akü Ömrü Tahmini

Abstract

Bu çalışmada, kesintisiz güç kaynağının (UPS) elektrik güç, akım, sıcaklık, akü voltajı değerlerinin veri kümesini elde etmek için gömülü sistem tabanlı veri toplama kartı tasarımı yapılmıştır. Veri seti, seri iletişim protokolü ve iletim kontrol protokolü / internet protokolü kullanılarak tasarlanan geliştirilmiş veri toplama kartı ile elde edilir. Elde edilen veri seti, Visual Studio programı kullanılarak tasarlanan arayüzü ile aktarılmaktadır. Ayrıca, UPS'in akü ömrü tahmini, makine öğrenme algoritmalarından çeşitli regresyon modelleri tarafından gerçekleştirilmiştir. Akü durumu, akü elektrik enerjisi tüketimi ve sıcaklık verileri, ortalama karekök hatası ve R^2 testi ile analiz edilmiştir. Rassal Orman regresyonu, pil ömrü için elde edilen veri seti için diğer regresyon modellerinden daha iyi performans göstermiştir. Akü ömrünün tahmini UPS performansı için önemli olabilir.

Keywords

Veri paylaşım kartı, arayüz, uzaktan kontrol, akü ömrü, makine öğrenmesi, regresyon modeli

Project Number

1139B411901093

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