Fault severity detection of ball bearings and efficiency of one-period analysis in early fault diagnosis of rotating machinery

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Fault severity detection of ball bearings and efficiency of one-period analysis in early fault diagnosis of rotating machinery

Popis výsledku v původním jazyce

This paper investigates several number of methods: Wavelet Packet Energy (WPE), Time-domain features and Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA) which are efficient of extracting features in fault diagnosis of rotating machinery. The database, which is attained via Bearing Data Center of Case Western Reserve University (CWRU), includes signal samples related to the different faulty cases and severity levels of bearing type 6205-2RS JEM. Throughout the research, combination of different faulty sample signals which are segmented into different number of periods, one of which is so called one-period analysis, of rotation of the motor are used in order to classify early faults of bearings and five class severity levels of ball bearings. Upon using proposed approaches, an outstanding classification performance of 100% and 99,7% are observed in specificity of early faults by the use of one-period analysis and five severity level classification of ball faults, respectively.

Název v anglickém jazyce

Fault severity detection of ball bearings and efficiency of one-period analysis in early fault diagnosis of rotating machinery

Popis výsledku anglicky

This paper investigates several number of methods: Wavelet Packet Energy (WPE), Time-domain features and Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA) which are efficient of extracting features in fault diagnosis of rotating machinery. The database, which is attained via Bearing Data Center of Case Western Reserve University (CWRU), includes signal samples related to the different faulty cases and severity levels of bearing type 6205-2RS JEM. Throughout the research, combination of different faulty sample signals which are segmented into different number of periods, one of which is so called one-period analysis, of rotation of the motor are used in order to classify early faults of bearings and five class severity levels of ball bearings. Upon using proposed approaches, an outstanding classification performance of 100% and 99,7% are observed in specificity of early faults by the use of one-period analysis and five severity level classification of ball faults, respectively.

Druh

D - Stať ve sborníku

CEP obor

JQ - Strojní zařízení a nástroje

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Vibroengineering Procedia

ISBN

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ISSN

2345-0533

e-ISSN

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Počet stran výsledku

6

Strana od-do

76-81

Název nakladatele

JVE International

Místo vydání

Kaunas

Místo konání akce

Brno

Datum konání akce

31. 8. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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