IoT Application in Transformer Fault Prognosis Using Vibration Signal

M. Bagheri, V. Nurmanova, A. Zollanvari, S. Nezhivenko, B. T. Phung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Among various methods developed to monitor transformer condition and diagnose transformer electrical and mechanical issues, vibration monitoring is economical and suitable for real-time implementation. Amplitude, intensity, harmonic components and direction of the vibration signals can assist in identifying the condition of the transformer windings. In this study, a model capable of predicting the transformer short circuit in initial stage is developed using vibration signals. Moreover, insulation damage, and transformer over and under excitation is also studied. Real-time diagnosis is achieved using cloud computing and IoT protocols which enable data transfer, storage, and retrieval for all authorized users.

Original languageEnglish
Title of host publicationICHVE 2018 - 2018 IEEE International Conference on High Voltage Engineering and Application
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538650868
DOIs
Publication statusPublished - Feb 13 2019
Event2018 IEEE International Conference on High Voltage Engineering and Application, ICHVE 2018 - Athens, Greece
Duration: Sep 10 2018Sep 13 2018

Publication series

NameICHVE 2018 - 2018 IEEE International Conference on High Voltage Engineering and Application

Conference

Conference2018 IEEE International Conference on High Voltage Engineering and Application, ICHVE 2018
CountryGreece
CityAthens
Period9/10/189/13/18

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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