Optimized variational mode decomposition for improved bearing fault diagnosis and performance evaluation

• Autorzy: Lakikza Abderrahmane , Cheghib Hocine , Kahoul Nabil

Identyfikatory

DOI

10.24425/ame.2024.152615

• Języki publikacji: EN

Abstrakty

EN

This research presents an enhanced methodology for diagnosing bearing faults using Variational Mode Decomposition (VMD) based on L-Kurtosis analysis. The proposed method focuses on selecting optimal parameters for VMD to extract the mode containing the most information related to the fault. The selection of these parameters is based on comparing the energy ratio of each mode and the absolute difference in L-Kurtosis between the Intrinsic Mode Function (IMF) with the highest energy and the original signal. The extracted mode is further refined using a specified kurtosis rate threshold to ensure the most relevant significant modes are captured. The proposed methodology was tested using real fault data from the CWRU, XJTUSY, and a realworld wind turbine dataset related to electric motors and wind turbine systems. The results demonstrated high accuracy in fault detection compared to other methods such as the Gini Index, correlation, and traditional decomposition techniques like EMD (Empirical Mode Decomposition). Furthermore, due to the simple computational nature of the improved VMD method, it is faster and more efficient compared to methods that rely on complex calculations or frequency band analysis, making it suitable for applications requiring real-time, reliable fault diagnosis.

Słowa kluczowe

EN

bearing fault; variational mode decomposition; L-Kurtosis; energy ratio; diagnosis

PL

uszkodzenie łożyska; dekompozycja w trybie wariacyjnym; L-Kurtoza; stosunek energii; diagnostyka

• Wydawca: Komitet Budowy Maszyn PAN
• Czasopismo: Archive of Mechanical Engineering
• Rocznik: 2024
• Tom: LXXI, nr 4
• Strony: 467--495
• Opis fizyczny: Bibliogr. 25 poz., fot., tab., wykr.

Twórcy

autor

Lakikza Abderrahmane

• Electromechanical Systems Laboratory, Badji Mokhtar-Annaba University, Annaba, Algeria

• https://orcid.org/0009-0000-1238-3609

autor

Cheghib Hocine

• Electromechanical Systems Laboratory, Badji Mokhtar-Annaba University, Annaba, Algeria

• https://orcid.org/0000-0002-1737-8099

autor

Kahoul Nabil

• Electromechanical Systems Laboratory, Badji Mokhtar-Annaba University, Annaba, Algeria

• https://orcid.org/0000-0002-7156-727X

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025)