A data-driven predictive maintenance strategy based on accurate failure prognostics

• Autorzy: Chen Chuang , Wang Cunsong , Lu Ningyun , Jiang Bin , Xing Yin

Identyfikatory

DOI

10.17531/ein.2021.2.19

• Języki publikacji: EN

Abstrakty

EN

Maintenance is fundamental to ensure the safety, reliability and availability of engineering systems, and predictive maintenance is the leading one in maintenance technology. This paper aims to develop a novel data-driven predictive maintenance strategy that can make appropriate maintenance decisions for repairable complex engineering systems. The proposed strategy includes degradation feature selection and degradation prognostic modeling modules to achieve accurate failure prognostics. For maintenance decision-making, the perfect time for taking maintenance activities is determined by evaluating the maintenance cost online that has taken into account of the failure prognostic results of performance degradation. The feasibility and effectiveness of the proposed strategy is confirmed using the NASA data set of aero-engines. Results show that the proposed strategy outperforms the two benchmark maintenance strategies: classical periodic maintenance and emerging dynamic predictive maintenance.

Słowa kluczowe

EN

predictive maintenance; failure prognostics; performance degradation; maintenance cost

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2021
• Tom: Vol. 23, no. 2
• Strony: 387--394
• Opis fizyczny: Bibliogr. 23 poz., rys., tab.

Twórcy

autor

Chen Chuang

• College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

autor

Wang Cunsong

• College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

autor

Lu Ningyun

• College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

autor

Jiang Bin

• College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

autor

Xing Yin

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).