STRUCTURAL HEALTH MONITORING IN AEROSPACE STRUCTURES: CURRENT INSPECTION METHODS, TECHNOLOGIES, AND FUTURE TRENDS

Eroğlu E.

in: International Research in the Field of Aerospace Engineering, ASSOC. PROF. DR. HAŞIM KAFALI, Editor, Eğitim Yayınevi, İstanbul, pp.15-39, 2025

  • Publication Type: Book Chapter / Chapter Research Book
  • Publication Date: 2025
  • Publisher: Eğitim Yayınevi
  • City: İstanbul
  • Page Numbers: pp.15-39
  • Editors: ASSOC. PROF. DR. HAŞIM KAFALI, Editor
  • Eskisehir Osmangazi University Affiliated: Yes

Abstract


1. INTRODUCTION

1.1 Damage and Safety Requirements in Aerospace Structures

Aerospace structures are subjected to variable and strenuous loading conditions throughout their 

operational lifespans (Boller, 2008; Payne, 1976) Cyclic mechanical loads during flight, thermal 

cycling, humidity, and corrosive environments can lead to critical defects, particularly in 

metallic  and  composite  structures.  These  include  fatigue  cracks, delamination, fastener 

failures, and Barely Visible Impact Damage (BVID). (Diamanti & Soutis, 2010a; Qinetiq, 2012) Such 

damage types pose significant risks to flight safety by directly compromising structural 

integrity.(Seneviratne & Tomblin, 2010)

Traditional aviation maintenance philosophy relies on periodic inspections performed at specific 

flight hour intervals or cycle counts (Aviation Rulemaking Advisory Committee (ARAC), 2024; “New 

Materials for Next-Generation Commercial Transports,” 1996). However, the increasing use of 

composite materials in modern aircraft, coupled with complex geometries and high operational 

tempos, has highlighted the limitations of conventional maintenance in terms of cost, time, and 

accessibility. (Muñoz, n.d.) This shift has necessitated the development of more continuous, 

automated, and real-time monitoring approaches (Cusati

et al., 2022; Diamanti & Soutis, 2010b)

1.2 Evolution from Non-Destructive Testing to Structural Health
Monitoring
Non-Destructive Testing (NDT) methods such as ultrasonic testing,
radiography, magnetic particle, and eddy current enable defect detection
without compromising the structure's utility. While these techniques have
been successfully utilized for decades, they are inherently periodic and
human-dependent, lacking continuous monitoring capabilities. (Köseoğlu,
2025; Negi et al., 2025)
Structural Health Monitoring (SHM) has emerged as an evolution of
the classical NDT approach. SHM systems aim to continuously monitor
structural conditions and detect damage at an incipient stage via integrated
sensors. This paradigm shifts maintenance strategies from "scheduled
maintenance" toward "Condition-Based Maintenance (CBM)" and
"Predictive Maintenance" frameworks. (Negi et al., 2025)
1.3 Definition and Scope of Structural Health Monitoring SHM is
defined as the integration of sensors, data acquisition, and analysis systems
designed to evaluate the current state of a structure, monitor changes over
time, and identify damage. (Martins et al., 2020; Scarselli & Nicassio,
2025) In literature, SHM is frequently categorized according to Rytter’s
four-level damage detection hierarchy (Rytter, 1993; Scarselli & Nicassio,
2025; Scott W. Doebling et al., 1996; Sohn et al., 1996):
• Level 1 (Detection): Is there damage?
• Level 2 (Localization): Where is the damage?
• Level 3 (Assessment): How severe is the damage?
• Level 4 (Prediction): What is the remaining useful life (RUL)?
In aerospace applications, the scope of SHM extends beyond mere
damage detection to include load monitoring, residual life estimation, and
structural behavior validation (Zhang et al., 2022). Thus, SHM provides a
more holistic system approach compared to classical NDT (Ballarin et al.,
2025; Romano et al., 2019).
The objective of this book chapter is to provide a comprehensive review
and comparative evaluation of current SHM-based inspection methods in
aerospace structures. The chapter first introduces the fundamental
components of SHM systems, followed by an in-depth analysis of wavebased,
vibration-based, and data-driven SHM approaches. Finally, current challenges, certification processes, and future research trends are
discussed.