Gas turbine reliability estimation to reduce the risk of failure occurrence with a comparative study between the two-parameter Weibull distribution and a new modified Weibull distribution

• Autorzy: Djeddi Ahmed Zohair , Hafaifa Ahmed , Iratni Abdelhamid , Kouzou Abdellah

Identyfikatory

DOI

10.29354/diag/146240

• Języki publikacji: EN

Abstrakty

EN

Responding to the needs of quality and robustness of analysis and management of degradation of equipment, to increase their life cycle and to expand these facilities to become more and more sophisticated and agronomic. This work proposes a contribution to increase the survival of a gas turbine, installed in a gascompression plant, with a comparative study between the two-parameter Weibull distribution. A new modified Weibull distribution was proposed also to reduce the risk of occurrence of failure in this rotating machine. A Statistical analysis and validation on the synthesis of turbine's reliability data and failures were considered, with a particular focus on the use of this data to increase the availability of this type of machine. So, developing a maintenance plan based on their reliability indices for scheduled inspections.

Słowa kluczowe

EN

failure analysis; malfunction analysis; availability; reliability estimation; failure occurrence; maintenance plan; gas turbine; two-parameter Weibull; modified Weibull

PL

analiza uszkodzeń; dostępność; ocena niezawodności; turbina gazowa

• Wydawca: Polskie Towarzystwo Diagnostyki Technicznej
• Czasopismo: Diagnostyka
• Rocznik: 2022
• Tom: Vol. 23, No. 1
• Strony: no. art. 2022107
• Opis fizyczny: Bibliogr. 48 poz., rys., tab.

Twórcy

autor

Djeddi Ahmed Zohair

• Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Algeria
• Gas Turbine Joint Research Team, University of Djelfa, Djelfa 17000 DZ, Algeria

autor

Hafaifa Ahmed

• Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Algeria
• Gas Turbine Joint Research Team, University of Djelfa, Djelfa 17000 DZ, Algeria

autor

Iratni Abdelhamid

• Faculty of Science and Technology, University of Bordj Bou Arreridj, 34030 DZ, Algeria

autor

Kouzou Abdellah

• Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Algeria
• Gas Turbine Joint Research Team, University of Djelfa, Djelfa 17000 DZ, Algeria

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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).