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Description
  • Článek je zaměřen na diagnostiku poruch stochastického nelineárního systému využitím Bayesovy statistiky. Předložená metodika spočívá v pravděpodobnostním zobrazení měřených dat do tzv. poruchové proměnné, která učinkuje jako indikátor uvažovaných módů. Navržená metodika je numericky jednoduchá a vhodná pro diagnostiku poruch v reálném čase. Metodika byla úspěšně ověřována na laboratorní tepelné soustavě. (cs)
  • The paper focuses on fault diagnosis (FDI) in stochastic nonlinear systems using Bayesian statistics. The main concept of this approach relies on a probabilistic model to estimate the occurrences of faults by probabilities. The methodology consists in probabilistic mapping of the measured data into a fault variable, which acts as an indicator of considered modes of the systems. One of the main advantages of the proposed FDI approach is the ability to perform real-time supervised training in which the parameters of the fault probability table are updated in real time. The suggested methodology is very simple for numerical calculations and enables one to include heuristic knowledge about the faults. The practical aspects of the proposed FDI algorithm were successfully tested in real time using a laboratory heating system.
  • The paper focuses on fault diagnosis (FDI) in stochastic nonlinear systems using Bayesian statistics. The main concept of this approach relies on a probabilistic model to estimate the occurrences of faults by probabilities. The methodology consists in probabilistic mapping of the measured data into a fault variable, which acts as an indicator of considered modes of the systems. One of the main advantages of the proposed FDI approach is the ability to perform real-time supervised training in which the parameters of the fault probability table are updated in real time. The suggested methodology is very simple for numerical calculations and enables one to include heuristic knowledge about the faults. The practical aspects of the proposed FDI algorithm were successfully tested in real time using a laboratory heating system. (en)
Title
  • Real-time Fault Diagnosis Using Probability Distribution of Faults
  • Diagnostika poruch v reálném čase využitím rozdělení pravděpodobnosti poruch (cs)
  • Real-time Fault Diagnosis Using Probability Distribution of Faults (en)
skos:prefLabel
  • Real-time Fault Diagnosis Using Probability Distribution of Faults
  • Diagnostika poruch v reálném čase využitím rozdělení pravděpodobnosti poruch (cs)
  • Real-time Fault Diagnosis Using Probability Distribution of Faults (en)
skos:notation
  • RIV/68407700:21220/06:02123247!RIV08-MSM-21220___
http://linked.open.../vavai/riv/strany
  • 165;166
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
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
  • 496562
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21220/06:02123247
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Bayesian statistics; Fault; diagnosis (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [FE79E5A660CB]
http://linked.open...v/mistoKonaniAkce
  • Vienna
http://linked.open...i/riv/mistoVydani
  • Vienna
http://linked.open...i/riv/nazevZdroje
  • Annals of DAAAM for 2006 & Proceedings
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Hofreiter, Milan
  • Garajayewa, G.
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • DAAAM International
https://schema.org/isbn
  • 3-901509-57-7
http://localhost/t...ganizacniJednotka
  • 21220
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