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FAULT DIAGNOSTICS OF ACOUSTIC SIGNALS OF LOADED SYNCHRONOUS MOTOR USING SMOFS-25-EXPANDED AND SELECTED CLASSIFIERS.

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Title: FAULT DIAGNOSTICS OF ACOUSTIC SIGNALS OF LOADED SYNCHRONOUS MOTOR USING SMOFS-25-EXPANDED AND SELECTED CLASSIFIERS.
Alternate Title: Dijagnostika greške akustičkih signala opterećenog sinkronog motora primjenom SMOFS-25-EXPANDED i odabranih klasifikatora.
Authors: Glowacz, Adam1 adglow@agh.edu.pl
Source: Technical Gazette / Tehnički Vjesnik. Sep/Oct2016, Vol. 23 Issue 5, p1365-1372. 8p.
Subjects: Fault diagnosis, Acoustic signal processing, Synchronous electric motors, Electric power system faults, Nearest neighbor analysis (Statistics)
Abstract (English): A system of fault diagnostics of loaded synchronous motor was proposed. Proposed system was based on acoustic signals of loaded synchronous motor. A new method of feature extraction SMOFS-25-EXPANDED (shorted method of frequencies selection-25-Expanded) was proposed. Presented method was analysed for 3 classifiers: LDA (Linear Discriminant Analysis), NN (Nearest Neighbour), SOM (Self-organizing Map). Analysis was carried out for real incipient states of loaded synchronous motor. Acoustic signals generated by motor were used in analysis. The following states of motor were analysed: healthy motor, motor with shorted stator coil, motor with shorted stator coil and broken coil, motor with shorted stator coil and two broken coils. These states are caused by natural degradation of rotating synchronous motor. The results of recognition were good. Proposed method of acoustic signal recognition can be used to protect loaded synchronous motors. [ABSTRACT FROM AUTHOR]
Abstract (Croatian): Predlaže se sustav dijagnostike greške opterećenog sinkronog motora. Predloženi se sustav zasniva na akustičkim signalima opterećenog sinkronog motora. Predlaže se nova metoda određivanja karakteristika SMOFS-25-EXPANDED (shorted method of frequencies selection-25-expaned - skraćena metoda za izbor frekvencija-25-proširena). Predložena se metoda analizirala u odnosu na tri klasifikatora: LDA (Linear Discriminant Analysis - analiza linearnog diskriminatora), NN (Nearest Neighbour - najbliži susjed), SOM (Self-organizing Map - samoorganizirajuća mapa). Analiza je provedena za stvarno početna stanja opterećenog sinkronog motora. U analizi su iskorišteni akustički signali koje je stvarao motor. Analizirala su se sljedeća stanja motora: ispravan motor, motor sa skraćenim namotajem statora, motor sa skraćenim namotajem statora i prekinutim namotajem, motor sa skraćenim namotajem statora i dva prekinuta namotaja. Do takvih je stanja došlo zbog prirodne degradacije rotirajućeg sinkronog motora. Rezultati analize su dobri. Predložena metoda prepoznavanja akustičkog signala može se primijeniti za zaštitu opterećenih sinkronih motora. [ABSTRACT FROM AUTHOR]
Copyright of Technical Gazette / Tehnički Vjesnik is the property of Tehnicki Vjesnik and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: FAULT DIAGNOSTICS OF ACOUSTIC SIGNALS OF LOADED SYNCHRONOUS MOTOR USING SMOFS-25-EXPANDED AND SELECTED CLASSIFIERS.
– Name: TitleAlt
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  Data: Dijagnostika greške akustičkih signala opterećenog sinkronog motora primjenom SMOFS-25-EXPANDED i odabranih klasifikatora.
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  Data: <searchLink fieldCode="AR" term="%22Glowacz%2C+Adam%22">Glowacz, Adam</searchLink><relatesTo>1</relatesTo><i> adglow@agh.edu.pl</i>
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  Data: <searchLink fieldCode="JN" term="%22Technical+Gazette+%2F+Tehnički+Vjesnik%22">Technical Gazette / Tehnički Vjesnik</searchLink>. Sep/Oct2016, Vol. 23 Issue 5, p1365-1372. 8p.
– Name: Subject
  Label: Subjects
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  Data: <searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Acoustic+signal+processing%22">Acoustic signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Synchronous+electric+motors%22">Synchronous electric motors</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+power+system+faults%22">Electric power system faults</searchLink><br /><searchLink fieldCode="DE" term="%22Nearest+neighbor+analysis+%28Statistics%29%22">Nearest neighbor analysis (Statistics)</searchLink>
– Name: Abstract
  Label: Abstract (English)
  Group: Ab
  Data: A system of fault diagnostics of loaded synchronous motor was proposed. Proposed system was based on acoustic signals of loaded synchronous motor. A new method of feature extraction SMOFS-25-EXPANDED (shorted method of frequencies selection-25-Expanded) was proposed. Presented method was analysed for 3 classifiers: LDA (Linear Discriminant Analysis), NN (Nearest Neighbour), SOM (Self-organizing Map). Analysis was carried out for real incipient states of loaded synchronous motor. Acoustic signals generated by motor were used in analysis. The following states of motor were analysed: healthy motor, motor with shorted stator coil, motor with shorted stator coil and broken coil, motor with shorted stator coil and two broken coils. These states are caused by natural degradation of rotating synchronous motor. The results of recognition were good. Proposed method of acoustic signal recognition can be used to protect loaded synchronous motors. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label: Abstract (Croatian)
  Group: Ab
  Data: Predlaže se sustav dijagnostike greške opterećenog sinkronog motora. Predloženi se sustav zasniva na akustičkim signalima opterećenog sinkronog motora. Predlaže se nova metoda određivanja karakteristika SMOFS-25-EXPANDED (shorted method of frequencies selection-25-expaned - skraćena metoda za izbor frekvencija-25-proširena). Predložena se metoda analizirala u odnosu na tri klasifikatora: LDA (Linear Discriminant Analysis - analiza linearnog diskriminatora), NN (Nearest Neighbour - najbliži susjed), SOM (Self-organizing Map - samoorganizirajuća mapa). Analiza je provedena za stvarno početna stanja opterećenog sinkronog motora. U analizi su iskorišteni akustički signali koje je stvarao motor. Analizirala su se sljedeća stanja motora: ispravan motor, motor sa skraćenim namotajem statora, motor sa skraćenim namotajem statora i prekinutim namotajem, motor sa skraćenim namotajem statora i dva prekinuta namotaja. Do takvih je stanja došlo zbog prirodne degradacije rotirajućeg sinkronog motora. Rezultati analize su dobri. Predložena metoda prepoznavanja akustičkog signala može se primijeniti za zaštitu opterećenih sinkronih motora. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Technical Gazette / Tehnički Vjesnik is the property of Tehnicki Vjesnik and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.17559/TV-20150328135652
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      – Code: eng
        Text: English
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        PageCount: 8
        StartPage: 1365
    Subjects:
      – SubjectFull: Fault diagnosis
        Type: general
      – SubjectFull: Acoustic signal processing
        Type: general
      – SubjectFull: Synchronous electric motors
        Type: general
      – SubjectFull: Electric power system faults
        Type: general
      – SubjectFull: Nearest neighbor analysis (Statistics)
        Type: general
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      – TitleFull: FAULT DIAGNOSTICS OF ACOUSTIC SIGNALS OF LOADED SYNCHRONOUS MOTOR USING SMOFS-25-EXPANDED AND SELECTED CLASSIFIERS.
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              M: 09
              Text: Sep/Oct2016
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