A Comprehensive Review of Emerging Trends in Aircraft Structural Prognostics and Health Management

Author:

Khalid Salman1,Song Jinwoo1ORCID,Azad Muhammad Muzammil1ORCID,Elahi Muhammad Umar1,Lee Jaehun1,Jo Soo-Ho1ORCID,Kim Heung Soo1ORCID

Affiliation:

1. Department of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pil-dong 1 Gil, Jung-gu, Seoul 04620, Republic of Korea

Abstract

This review paper addresses the critical need for structural prognostics and health management (SPHM) in aircraft maintenance, highlighting its role in identifying potential structural issues and proactively managing aircraft health. With a comprehensive assessment of various SPHM techniques, the paper contributes by comparing traditional and modern approaches, evaluating their limitations, and showcasing advancements in data-driven and model-based methodologies. It explores the implementation of machine learning and deep learning algorithms, emphasizing their effectiveness in improving prognostic capabilities. Furthermore, it explores model-based approaches, including finite element analysis and damage mechanics, illuminating their potential in the diagnosis and prediction of structural health issues. The impact of digital twin technology in SPHM is also examined, presenting real-life case studies that demonstrate its practical implications and benefits. Overall, this review paper will inform and guide researchers, engineers, and maintenance professionals in developing effective strategies to ensure aircraft safety and structural integrity.

Funder

National Research Foundation of Korea

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference142 articles.

1. Torhorst, S., Hölzel, N.B., and Gollnick, V. (2014, January 8–10). Identification and Evaluation of the Potentials of Prognostics and Health Management in Future Civil Aircraft. Proceedings of the PHM Society European Conference, Nantes, France.

2. Toward a Methodology of Requirements Definition for Prognostics and Health Management System to Support Aircraft Predictive Maintenance;Li;Aerosp. Sci. Technol.,2020

3. PHM-Oriented Integrated Fusion Prognostics for Aircraft Engines Based on Sensor Data;Xu;IEEE Sens. J.,2013

4. Scott, M.J., Verhagen, W.J., Bieber, M.T., and Marzocca, P. (2022). A Systematic Literature Review of Predictive Maintenance for Defence Fixed-Wing Aircraft Sustainment and Operations. Sensors, 22.

5. Van den Bergh, J., De Bruecker, P., Beliën, J., and Peeters, J. (2013). Aircraft Maintenance Operations: State of the Art, Faculteit Economie en Bedrijfswetenschappen. HUB Research Paper 201309.

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