Isbn: 9786202678742 - partial discharge recognition using artificial neural network (8 risultati)

Perfeziona la tua ricerca

  • Libri (8)

  • Nuovo (8)

a

Fascia di prezzo personalizzata (EUR)

a

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2020

      6202678747 / 9786202678742

      • Brossura

      Da: Books Puddle, New York, NY, U.S.A.Books Puddle

      Venditore con 4 stelle
      Contatta il venditore

      Condizione: Nuovo

      EUR 67,58

      EUR 3,44 spedizione 
      Spedito in U.S.A.

      Quantità: 4 disponibili

      Condizione: New.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing Jul 2020, 2020

      6202678747 / 9786202678742

      • Brossura
      • Print on Demand

      Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

      Venditore con 5 stelle
      Contatta il venditore

      Condizione: Nuovo

      EUR 39,90

      EUR 23,00 spedizione 
      Spedito da Germania a U.S.A.

      Quantità: 2 disponibili

      Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Partial discharge (PD) seriously affects the reliability of the distribution system due to electrical stress and the duration of the installation. Recent technology advance brings the analysis of the PD act as the guideline and maintenance strategy can be carried out when a parameter exceeding the predefined level. This book presents an artificial neural network (ANN) modelling in detecting the PD signal. PD signals are generated from experimental laboratory and simulation by using electromagnetic transient program-alternative transient program (EMTP-ATP). There are two analyses are carried out; classification and de-noising of PD signal. The first analysis used the straight forward procedure in PD signal classification. Second analysis presents the de-noising of PD signal using three different techniques; ANN, fast Fourier transforms (FFT) and discrete wavelet transform (DWT). The de-noising algorithm is implemented to discover a clean PD signal from disrupted signal. The performance of the de-nosing techniques was evaluated by comparing the signal to noise ratio (SNR). The result of this analysis shows ANN is the best de-noising technique compare to others. 80 pp. Englisch.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2020

      6202678747 / 9786202678742

      • Brossura
      • Print on Demand

      Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

      Venditore con 4 stelle
      Contatta il venditore

      Condizione: Nuovo

      EUR 66,31

      EUR 7,58 spedizione 
      Spedito da Regno Unito a U.S.A.

      Quantità: 4 disponibili

      Condizione: New. Print on Demand.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2020

      6202678747 / 9786202678742

      • Brossura
      • Print on Demand

      Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

      Venditore con 4 stelle
      Contatta il venditore

      Condizione: Nuovo

      EUR 68,01

      EUR 9,95 spedizione 
      Spedito da Germania a U.S.A.

      Quantità: 4 disponibili

      Condizione: New. PRINT ON DEMAND.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2020

      6202678747 / 9786202678742

      • Brossura
      • Print on Demand

      Da: moluna, Greven, Germaniamoluna

      Venditore con 5 stelle
      Contatta il venditore

      Condizione: Nuovo

      EUR 34,25

      EUR 48,99 spedizione 
      Spedito da Germania a U.S.A.

      Quantità: Più di 20 disponibili

      Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Isa MuzamirMuzamir Isa was born in Malaysia in 1979. He received Doctoral (Ph.D) degree from Aalto University, Helsinki, Finland. His research interests are partial discharge measurement, detection and location technique, and power s.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2020

      6202678747 / 9786202678742

      • Brossura
      • Print on Demand

      Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

      Venditore con 5 stelle
      Contatta il venditore

      Condizione: Nuovo

      EUR 58,59

      EUR 30,50 spedizione 
      Spedito da Germania a U.S.A.

      Quantità: 1 disponibili

      Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Partial discharge (PD) seriously affects the reliability of the distribution system due to electrical stress and the duration of the installation. Recent technology advance brings the analysis of the PD act as the guideline and maintenance strategy can be carried out when a parameter exceeding the predefined level. This book presents an artificial neural network (ANN) modelling in detecting the PD signal. PD signals are generated from experimental laboratory and simulation by using electromagnetic transient program-alternative transient program (EMTP-ATP). There are two analyses are carried out; classification and de-noising of PD signal. The first analysis used the straight forward procedure in PD signal classification. Second analysis presents the de-noising of PD signal using three different techniques; ANN, fast Fourier transforms (FFT) and discrete wavelet transform (DWT). The de-noising algorithm is implemented to discover a clean PD signal from disrupted signal. The performance of the de-nosing techniques was evaluated by comparing the signal to noise ratio (SNR). The result of this analysis shows ANN is the best de-noising technique compare to others.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing Jul 2020, 2020

      6202678747 / 9786202678742

      • Brossura
      • Print on Demand

      Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

      Venditore con 5 stelle
      Contatta il venditore

      Condizione: Nuovo

      EUR 39,90

      EUR 60,00 spedizione 
      Spedito da Germania a U.S.A.

      Quantità: 1 disponibili

      Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Partial discharge (PD) seriously affects the reliability of the distribution system due to electrical stress and the duration of the installation. Recent technology advance brings the analysis of the PD act as the guideline and maintenance strategy can be carried out when a parameter exceeding the predefined level. This book presents an artificial neural network (ANN) modelling in detecting the PD signal. PD signals are generated from experimental laboratory and simulation by using electromagnetic transient program-alternative transient program (EMTP-ATP). There are two analyses are carried out; classification and de-noising of PD signal. The first analysis used the straight forward procedure in PD signal classification. Second analysis presents the de-noising of PD signal using three different techniques; ANN, fast Fourier transforms (FFT) and discrete wavelet transform (DWT). The de-noising algorithm is implemented to discover a clean PD signal from disrupted signal. The performance of the de-nosing techniques was evaluated by comparing the signal to noise ratio (SNR). The result of this analysis shows ANN is the best de-noising technique compare to others.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2020

      6202678747 / 9786202678742

      • Brossura
      • Print on Demand

      Da: preigu, Osnabrück, Germaniapreigu

      Venditore con 5 stelle
      Contatta il venditore

      Condizione: Nuovo

      EUR 35,60

      EUR 70,00 spedizione 
      Spedito da Germania a U.S.A.

      Quantità: 5 disponibili

      Taschenbuch. Condizione: Neu. Partial Discharge Recognition Using Artificial Neural Network | Muzamir Isa (u. a.) | Taschenbuch | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202678742 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.