Diagnosis of power components amid the 4th industrial revolution

Mahmoud Elsisi*, Minh-Quang Tran, Mohammed Amer, Viet Q. Vu, Mohamed M.F. Darwish, Karar Mahmoud, Diaa Eldin A. Mansour, Matti Lehtonen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

2 Citations (Scopus)

Abstract

Power components are among the most expensive parts in the power and industrial sectors worldwide. Nevertheless, fault diagnosis and remote con¬trol still face a lot of challenges in providing high accuracy and fast response to protect the power components. The upgrade of the Internet of Things (IoT) in recent years has made apps smarter, and linked gadgets make them more useful in smart systems. In the meantime, IoT and machine learning (ML) are being used to give an application more intelligence and capabilities, espe¬cially since the amount of data collected is increasing. As the trend of IoT and machine learning has just begun worldwide, especially in electrical applica¬tions, it seemed important to present a comprehensive overview of the cur¬rent actions and trends, including the regulatory limits and reservations about smart energy systems. In this sense, this chapter is concerned with smart energy systems, which have been investigated using both machine learning and the Internet of Things. The aim of this chapter is to demonstrate recent advances in IoT and machine learning to troubleshoot smart energy systems. The chapter deals with fault diagnosis and remote control for smart energy systems based on advanced digital twin platforms and machine learning tech¬niques that are more suitable for modern smart grids and fourth-generation (4G) and fifth-generation (5G) networks. Following the trend of the fourth industrial trend (named Industry 4.0), the use of online condition monitor¬ing systems has accelerated the process of fault diagnosis for smart energy systems. Finally, in support of Industry 4.0, several case studies covering online fault diagnosis and cybersecurity are presented, including gas-insu¬lated switchgear, power transformers, and induction machines.

Original languageEnglish
Title of host publicationPower Systems Amid the 4th Industrial Revolution
PublisherRiver Publishers
Pages59-90
Number of pages32
ISBN (Electronic)9788770226752
ISBN (Print)9788770226769
Publication statusPublished - 9 Mar 2024
MoE publication typeA3 Book section, Chapters in research books

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