Intelligent Diagnosis and Learning in Centrifugal Pumps
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F04%3A03099698" target="_blank" >RIV/68407700:21230/04:03099698 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Intelligent Diagnosis and Learning in Centrifugal Pumps
Original language description
This paper addresses the problem of on-line diagnosis of cavitation in centrifugal pumps. The paper introduces an application of the Open Prediction System (OPS) to cavitation diagnosis. The application of OPS results in an algorithmic framework for diagnosis of cavitation in centrifugal pumps. The diagnosis is based on repeated evaluation of a data scan providing full record of input signals which are observed for a fixed short period of time. Experimental verification of the algorithmic framework andthe proposed methodology proved that a condition monitoring system built upon them is capable of diagnosing a wide range of cavitation conditions that can occur in a centrifugal pump, including the very early incipient cavitation.
Czech name
Není k dispozici
Czech description
Není k dispozici
Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2004
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Emerging Solutions for Future Manufacturing Systems
ISBN
0-387-22828-4
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
513-522
Publisher name
Springer
Place of publication
New York
Event location
Vídeň
Event date
Sep 27, 2004
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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