New preemptive arc-fault detection techniques in medium-voltage switchgear and motor controls

John A. Kay, G. Amjad Hussain, Matti Lehtonen, Lauri Kumpulainen

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)

Abstract

For forest-products-based industries, the significant benefits of preemptive arc-flash protection and online condition monitoring of electrical equipment are not well known. This paper provides a summary of the research surrounding the development and testing of new advanced sensor technologies for this purpose. This paper builds on the authors' initial research and their supporting publications providing more extensive and detailed field measurements supporting the preemptive detection of significant defects that can lead to an arc-flash event. The early detection of impending faults and the prediction of future arc-flash occurrences in medium voltage (MV) switchgears and motor control centers (MCCs) can be very beneficial. The development of new sensor technologies both for partial discharge measurement and thermal detection are discussed and evaluated. The two most common noncontact causes leading to an arc-flash event in MV switchgears and MCCs are insulation degradation and thermal stresses. This paper will highlight very detailed results measured under both of these conditions in laboratory and actual installed conditions. An effective signal processing method, which is used for extracting the essential indication data and for the integration of this system into existing protection programmable logic control or supervisory control and data acquisition (SCADA) systems, is outlined.
Original languageEnglish
Pages (from-to)740-750
JournalIEEE Transactions on Industry Applications
Volume52
Issue number1
DOIs
Publication statusPublished - 2016
MoE publication typeA1 Journal article-refereed

Fingerprint

Electric switchgear
Fault detection
Electric potential
SCADA systems
Partial discharges
Sensors
Condition monitoring
Thermal stress
Insulation
Signal processing
Degradation
Defects
Testing
Industry

Keywords

  • arc flash
  • arcing fault
  • discrete wavelet transform (DWT)
  • motor control center (MCC)
  • nonintrusive sensors
  • online condition monitoring
  • proactive techniques
  • signal processing
  • switchgear

Cite this

Kay, John A. ; Hussain, G. Amjad ; Lehtonen, Matti ; Kumpulainen, Lauri. / New preemptive arc-fault detection techniques in medium-voltage switchgear and motor controls. In: IEEE Transactions on Industry Applications. 2016 ; Vol. 52, No. 1. pp. 740-750.
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abstract = "For forest-products-based industries, the significant benefits of preemptive arc-flash protection and online condition monitoring of electrical equipment are not well known. This paper provides a summary of the research surrounding the development and testing of new advanced sensor technologies for this purpose. This paper builds on the authors' initial research and their supporting publications providing more extensive and detailed field measurements supporting the preemptive detection of significant defects that can lead to an arc-flash event. The early detection of impending faults and the prediction of future arc-flash occurrences in medium voltage (MV) switchgears and motor control centers (MCCs) can be very beneficial. The development of new sensor technologies both for partial discharge measurement and thermal detection are discussed and evaluated. The two most common noncontact causes leading to an arc-flash event in MV switchgears and MCCs are insulation degradation and thermal stresses. This paper will highlight very detailed results measured under both of these conditions in laboratory and actual installed conditions. An effective signal processing method, which is used for extracting the essential indication data and for the integration of this system into existing protection programmable logic control or supervisory control and data acquisition (SCADA) systems, is outlined.",
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New preemptive arc-fault detection techniques in medium-voltage switchgear and motor controls. / Kay, John A.; Hussain, G. Amjad; Lehtonen, Matti; Kumpulainen, Lauri.

In: IEEE Transactions on Industry Applications, Vol. 52, No. 1, 2016, p. 740-750.

Research output: Contribution to journalArticleScientificpeer-review

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