Rotating machines diagnostics with use of LabView
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F13%3A43920577" target="_blank" >RIV/49777513:23520/13:43920577 - isvavai.cz</a>
Výsledek na webu
<a href="http://hdl.handle.net/11025/21203" target="_blank" >http://hdl.handle.net/11025/21203</a>
DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Rotating machines diagnostics with use of LabView
Popis výsledku v původním jazyce
Presented work deals with rotating machines diagnostics, namely wind turbines. The paper provides information about the configuration of specific offshore wind turbines placed in the wind farm Alpha Ventus. Further, the meaning of condition-based maintenance is explained and the general structure of health monitoring system is described as well as the most common faults in conjunction with their symptoms. The following part explains the data processing with a view to feature extraction from vibration data and feature reduction to identify the most relevant ones. Based on introduced knowledge, a technique for fault diagnostics is suggested. In the practical part, the experimental vibration data are examined and a case study based on real data is presented and the proposed diagnostic approach is tested. Finally, a guide to the application implemented in LabView, which provided the data analysis, is introduced.
Název v anglickém jazyce
Rotating machines diagnostics with use of LabView
Popis výsledku anglicky
Presented work deals with rotating machines diagnostics, namely wind turbines. The paper provides information about the configuration of specific offshore wind turbines placed in the wind farm Alpha Ventus. Further, the meaning of condition-based maintenance is explained and the general structure of health monitoring system is described as well as the most common faults in conjunction with their symptoms. The following part explains the data processing with a view to feature extraction from vibration data and feature reduction to identify the most relevant ones. Based on introduced knowledge, a technique for fault diagnostics is suggested. In the practical part, the experimental vibration data are examined and a case study based on real data is presented and the proposed diagnostic approach is tested. Finally, a guide to the application implemented in LabView, which provided the data analysis, is introduced.
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
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OECD FORD obor
20205 - Automation and control systems
Návaznosti výsledku
Projekt
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Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2013
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů