Filtered Leakage Current Measurement for Various Loads
Thepurpose of this study was to determine the link between induction voltages from various electrical loads. We used a residual current device (RCD) circuit that operates with a capacitor as a DC voltage reading tool. The circuit reads the value of the leakage current generated by the sensing coi...
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doaj-1224f806ad1b4564bfad093842210fc32021-05-03T04:52:09ZengUniversitas IndonesiaInternational Journal of Technology2086-96142087-21002021-04-0112240141110.14716/ijtech.v12i2.43024302Filtered Leakage Current Measurement for Various LoadsErwin Sutanto0Silvi Nurwahyuni1Riky Tri Yunardi2Guillermo Escrivá-Escrivá3Biomedical Engineering, Faculty of Science and Technology, Universitas Airlangga, Kampus C, Jalan Mulyosari, Surabaya60115, IndonesiaDepartment of Engineering, Faculty of Vocational, Universitas Airlangga, Campus B, Jalan Srikana 65, Surabaya 60286, IndonesiaDepartment of Engineering, Faculty of Vocational, Universitas Airlangga, Campus B, Jalan Srikana 65, Surabaya 60286, IndonesiaInstitute of Energy Engineering, Universitat Politècnica de València, Camino de Vera, s/n, Edificio 8E, escalera F, 2 opiso, 46022 Valencia, SpainThepurpose of this study was to determine the link between induction voltages from various electrical loads. We used a residual current device (RCD) circuit that operates with a capacitor as a DC voltage reading tool. The circuit reads the value of the leakage current generated by the sensing coil from the RCD. It also uses the Blynk framework as an online monitoring system and a WeMos D1-R2 microcontroller to connect to the server using Wi-Fi. Using this system, the dataset was collected in a Python server and utilized with a machine learning technique to draw a correlation between the load power and reading voltage. This will help improve the mistakes of a common RCD cut-off point, which is usually defined only at a specific induced voltage. For the different types, an LED lamp and typical electric fan were used as loads in the experiment. Meanwhile, for a similar type of load, three different LED lamps were characterized using machine learning to show the correlation. From the comparison, a threshold voltage of around 1V and three different gradients with increases of more than 10% are found for LED lamps with loads of 3W, 5W, and 9W.The results show that the relationship depends on the type of its power supply.https://ijtech.eng.ui.ac.id/article/view/4302circuit breakerelectrical loadsfiltered signalleakage currentmachine learning |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Erwin Sutanto Silvi Nurwahyuni Riky Tri Yunardi Guillermo Escrivá-Escrivá |
spellingShingle |
Erwin Sutanto Silvi Nurwahyuni Riky Tri Yunardi Guillermo Escrivá-Escrivá Filtered Leakage Current Measurement for Various Loads International Journal of Technology circuit breaker electrical loads filtered signal leakage current machine learning |
author_facet |
Erwin Sutanto Silvi Nurwahyuni Riky Tri Yunardi Guillermo Escrivá-Escrivá |
author_sort |
Erwin Sutanto |
title |
Filtered Leakage Current Measurement for Various Loads |
title_short |
Filtered Leakage Current Measurement for Various Loads |
title_full |
Filtered Leakage Current Measurement for Various Loads |
title_fullStr |
Filtered Leakage Current Measurement for Various Loads |
title_full_unstemmed |
Filtered Leakage Current Measurement for Various Loads |
title_sort |
filtered leakage current measurement for various loads |
publisher |
Universitas Indonesia |
series |
International Journal of Technology |
issn |
2086-9614 2087-2100 |
publishDate |
2021-04-01 |
description |
Thepurpose of this study was to determine the link between induction
voltages from various electrical loads. We used a residual current device (RCD)
circuit that operates with a capacitor as a DC voltage reading tool. The
circuit reads the value of the leakage current generated by the sensing coil
from the RCD. It also uses the Blynk framework as an online monitoring system
and a WeMos D1-R2 microcontroller to connect to the server using Wi-Fi. Using
this system, the dataset was collected in a Python server and utilized with a
machine learning technique to draw a correlation between the load power and
reading voltage. This will help improve the mistakes of a common RCD cut-off
point, which is usually defined only at a specific induced voltage. For the
different types, an LED lamp and typical electric fan were used as loads in the
experiment. Meanwhile, for a similar type of load, three different LED lamps
were characterized using machine learning to show the correlation. From the
comparison, a threshold voltage of around 1V and three different gradients with
increases of more than 10% are found for LED lamps with loads of 3W, 5W, and
9W.The results show that the relationship depends on the type of its power
supply. |
topic |
circuit breaker electrical loads filtered signal leakage current machine learning |
url |
https://ijtech.eng.ui.ac.id/article/view/4302 |
work_keys_str_mv |
AT erwinsutanto filteredleakagecurrentmeasurementforvariousloads AT silvinurwahyuni filteredleakagecurrentmeasurementforvariousloads AT rikytriyunardi filteredleakagecurrentmeasurementforvariousloads AT guillermoescrivaescriva filteredleakagecurrentmeasurementforvariousloads |
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