TY - JOUR
T1 - A Comprehensive Review of Emerging Trends in Aircraft Structural Prognostics and Health Management
AU - Khalid, Salman
AU - Song, Jinwoo
AU - Azad, Muhammad Muzammil
AU - Elahi, Muhammad Umar
AU - Lee, Jaehun
AU - Jo, Soo Ho
AU - Kim, Heung Soo
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/9
Y1 - 2023/9
N2 - 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.
AB - 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.
KW - aircraft maintenance
KW - data-driven approaches
KW - digital twin technology
KW - health management
KW - model-based approaches
KW - structural prognostics
UR - http://www.scopus.com/inward/record.url?scp=85176463916&partnerID=8YFLogxK
U2 - 10.3390/math11183837
DO - 10.3390/math11183837
M3 - Review article
AN - SCOPUS:85176463916
SN - 2227-7390
VL - 11
JO - Mathematics
JF - Mathematics
IS - 18
M1 - 3837
ER -