Literature DB >> 33572829

A Review of Techniques for RSS-Based Radiometric Partial Discharge Localization.

David W Upton1, Keyur K Mistry2, Peter J Mather3, Zaharias D Zaharis4, Robert C Atkinson5, Christos Tachtatzis5, Pavlos I Lazaridis3.   

Abstract

The lifespan assessment and maintenance planning of high-voltage power systems requires condition monitoring of all the operational equipment in a specific area. Electrical insulation of electrical apparatuses is prone to failure due to high electrical stresses, and thus it is a critical aspect that needs to be monitored. The ageing process of the electrical insulation in high voltage equipment may accelerate due to the occurrence of partial discharge (PD) that may in turn lead to catastrophic failures if the related defects are left untreated at an initial stage. Therefore, there is a requirement to monitor the PD levels so that an unexpected breakdown of high-voltage equipment is avoided. There are several ways of detecting PD, such as acoustic detection, optical detection, chemical detection, and radiometric detection. This paper focuses on reviewing techniques based on radiometric detection of PD, and more specifically, using received signal strength (RSS) for the localization of faults. This paper explores the advantages and disadvantages of radiometric techniques and presents an overview of a radiometric PD detection technique that uses a transistor reset integrator (TRI)-based wireless sensor network (WSN).

Entities:  

Keywords:  RSS; WSN; field trials; localization algorithm; partial discharge; radiometric detection

Year:  2021        PMID: 33572829      PMCID: PMC7866259          DOI: 10.3390/s21030909

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  Partial Discharge and Internet of Things: A Switchgear Cell Maintenance Application Using Microclimate Sensors.

Authors:  Radu Fechet; Adrian I Petrariu; Adrian Graur
Journal:  Sensors (Basel)       Date:  2021-12-15       Impact factor: 3.576

  1 in total

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