Detection and diagnosis of bearing defects using vibration signal processing

• Autorzy: Bouaouiche Karim , Menasria Yamina , Khalfa Dalila

Identyfikatory

DOI

10.24425/ame.2023.146849

• Języki publikacji: EN

Abstrakty

EN

This work presents an analysis of vibration signals for bearing defects using a proposed approach that includes several methods of signal processing. The goal of the approach is to efficiently divide the signal into two distinct components: a meticulously organized segment that contains relatively straightforward information, and an inherently disorganized segment that contains a wealth of intricately complex data. The separation of the two component is achieved by utilizing the weighted entropy index (WEI) and the SVMD algorithm. Information about the defects was extracted from the envelope spectrum of the ordered and disordered parts of the vibration signal. Upon applying the proposed approach to the bearing fault signals available in the Paderborn university database, a high amplitude peak can be observed in the outer ring fault frequency (45.9 Hz). Likewise, for the signals available in XJTU-SY, a peak is observed at the fault frequency (108.6 Hz).

Słowa kluczowe

EN

vibration signal; bearing; signal processing; envelope spectrum; fault frequency

PL

sygnał wibracyjny; łożysko; przetwarzanie sygnałów; częstotliwość usterek

• Wydawca: Komitet Budowy Maszyn PAN
• Czasopismo: Archive of Mechanical Engineering
• Rocznik: 2023
• Tom: LXX, nr 3
• Strony: 433--452
• Opis fizyczny: Bibliogr. 34 poz., rys., tab.

Twórcy

autor

Bouaouiche Karim

• Electromechanical Engineering Laboratory, Badji Mokhtar University, Annaba, Algeria

• https://orcid.org/0000-0003-0740-3681

autor

Menasria Yamina

• Electromechanical Engineering Laboratory, Badji Mokhtar University, Annaba, Algeria

• https://orcid.org/0000-0003-0807-7822

autor

Khalfa Dalila

• Electromechanical Engineering Laboratory, Badji Mokhtar University, Annaba, Algeria

• https://orcid.org/0000-0002-9298-7660

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).