About: Advanced Detection, Isolation and Accomodation of Sensor Failures by Means of Artificial Neural Network.     Goto   Sponge   NotDistinct   Permalink

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Description
  • Příspěvek popisuje použití umělé neuronové sítě jako rychlého a přesného diagnostického nástroje pro identifikaci poruchy senzoru. Síť je také schopna určit, který ze sledovaných senzorů degraduje. Bylo odzkoušeno několik architektur neuronových sítí za účelem optimalizace architektury pro daný účel. Parametry motoru byly simulovány pomocí počítačovým programem. Tak byla získána sada dat pro učení a ověřování sítě. (cs)
  • This paper sets out to apply Artificial Neural Networks to provide a fast and accurate diagnostic tool for the identification of sensor faults. The network is also able to provide information of which sensor signal is degraded. Several architectures for networks were assessed to find the optimum design for the application. The engine performance was simulated by a computer program. This gave the data sets for the training and validation of the networks.
  • This paper sets out to apply Artificial Neural Networks to provide a fast and accurate diagnostic tool for the identification of sensor faults. The network is also able to provide information of which sensor signal is degraded. Several architectures for networks were assessed to find the optimum design for the application. The engine performance was simulated by a computer program. This gave the data sets for the training and validation of the networks. (en)
Title
  • Advanced Detection, Isolation and Accomodation of Sensor Failures by Means of Artificial Neural Network.
  • Pokročilá detekce, izolace a přizpůsobení chybných úda (cs)
  • Advanced Detection, Isolation and Accomodation of Sensor Failures by Means of Artificial Neural Network. (en)
skos:prefLabel
  • Advanced Detection, Isolation and Accomodation of Sensor Failures by Means of Artificial Neural Network.
  • Pokročilá detekce, izolace a přizpůsobení chybných úda (cs)
  • Advanced Detection, Isolation and Accomodation of Sensor Failures by Means of Artificial Neural Network. (en)
skos:notation
  • RIV/00010669:_____/06:#0000298!RIV07-MSM-00010669
http://linked.open.../vavai/riv/strany
  • 8-12
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1M0501)
http://linked.open...iv/cisloPeriodika
  • 3
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 464223
http://linked.open...ai/riv/idVysledku
  • RIV/00010669:_____/06:#0000298
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Gas turbine engine; sensor; diagnostics; artificial neural network (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • CZ - Česká republika
http://linked.open...ontrolniKodProRIV
  • [FC6A040BB2AE]
http://linked.open...i/riv/nazevZdroje
  • CZECH AEROSPACE Proceedings
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 20006
http://linked.open...iv/tvurceVysledku
  • Lamka, Jaromír
issn
  • 1211-877X
number of pages
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