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Exploring Prognostic and Diagnostic Techniques for Jet Engine Health Monitoring: A Review of Degradation Mechanisms and Advanced Prediction Strategies

Author

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  • Maria Grazia De Giorgi

    (Department of Engineering for Innovation, University of Salento, Via Monteroni, 73100 Lecce, Italy)

  • Nicola Menga

    (Department of Engineering for Innovation, University of Salento, Via Monteroni, 73100 Lecce, Italy)

  • Antonio Ficarella

    (Department of Engineering for Innovation, University of Salento, Via Monteroni, 73100 Lecce, Italy)

Abstract

Maintenance is crucial for aircraft engines because of the demanding conditions to which they are exposed during operation. A proper maintenance plan is essential for ensuring safe flights and prolonging the life of the engines. It also plays a major role in managing costs for aeronautical companies. Various forms of degradation can affect different engine components. To optimize cost management, modern maintenance plans utilize diagnostic and prognostic techniques, such as Engine Health Monitoring (EHM), which assesses the health of the engine based on monitored parameters. In recent years, various EHM systems have been developed utilizing computational techniques. These algorithms are often enhanced by utilizing data reduction and noise filtering tools, which help to minimize computational time and efforts, and to improve performance by reducing noise from sensor data. This paper discusses the various mechanisms that lead to the degradation of aircraft engine components and the impact on engine performance. Additionally, it provides an overview of the most commonly used data reduction and diagnostic and prognostic techniques.

Suggested Citation

  • Maria Grazia De Giorgi & Nicola Menga & Antonio Ficarella, 2023. "Exploring Prognostic and Diagnostic Techniques for Jet Engine Health Monitoring: A Review of Degradation Mechanisms and Advanced Prediction Strategies," Energies, MDPI, vol. 16(6), pages 1-37, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2711-:d:1097286
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    References listed on IDEAS

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    Cited by:

    1. Konstantinos Mathioudakis & Alexios Alexiou & Nikolaos Aretakis & Christoforos Romesis, 2024. "Signatures of Compressor and Turbine Faults in Gas Turbine Performance Diagnostics: A Review," Energies, MDPI, vol. 17(14), pages 1-22, July.
    2. Xiao, Dasheng & Lin, Zhifu & Yu, Aiyang & Tang, Ke & Xiao, Hong, 2024. "Data-driven method embedded physical knowledge for entire lifecycle degradation monitoring in aircraft engines," Reliability Engineering and System Safety, Elsevier, vol. 247(C).

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