This paper is published in Volume-6, Issue-5, 2020
Area
Electronics and Instrumentation Engineering
Author
Vignesh M.
Co-authors
N. M Jothi Swaroopan, T.K Vignesh, Sharan Y.B
Org/Univ
R.M.K. Engineering College, Tamil Nadu, India, India
Pub. Date
22 September, 2020
Paper ID
V6I5-1206
Publisher
Keywords
Distribution Transformer, Global Service Mobile, Arduino, Analog to Digital Converter, Programmed Microcontroller, Transformer Health.

Citationsacebook

IEEE
Vignesh M., N. M Jothi Swaroopan, T.K Vignesh, Sharan Y.B. Transformer fault identification and load sharing using the internet of things, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Vignesh M., N. M Jothi Swaroopan, T.K Vignesh, Sharan Y.B (2020). Transformer fault identification and load sharing using the internet of things. International Journal of Advance Research, Ideas and Innovations in Technology, 6(5) www.IJARIIT.com.

MLA
Vignesh M., N. M Jothi Swaroopan, T.K Vignesh, Sharan Y.B. "Transformer fault identification and load sharing using the internet of things." International Journal of Advance Research, Ideas and Innovations in Technology 6.5 (2020). www.IJARIIT.com.

Abstract

This paper is about the design and implementation of a mobile embedded system to monitor and record key parameters of a distribution transformer like load currents, and ambient temperature. The idea of an online monitoring system integrates a Global Service Mobile (GSM) Modem, with a standalone Arduino and different sensors. It is installed at the distribution transformer site and the above parameters are recorded using the analog to digital converter (ADC) of the embedded system. The obtained parameters are processed and recorded in the system memory. If any abnormality or an emergency occurs the system sends SMS (short message service) messages to the mobile phones containing information about the abnormality according to some predefined instructions programmed in the microcontroller at the same Time the data’s of transformers health will automatically be uploaded to the cloud for future analysis. This mobile system will help the transformers to operate smoothly and identify problems before any catastrophic failure.